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Shrestha, Ujjwal. "Automatic Liver and Tumor Segmentation from CT Scan Images using Gabor Feature and Machine Learning Algorithms." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1522411364001198.
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Gasslander, Maja. "Segmentation of Clouds in Satellite Images." Thesis, Linköpings universitet, Datorseende, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-128802.
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The usage of 3D modelling is increasing fast, both for civilian and military areas, such as navigation, targeting and urban planning. When creating a 3D model from satellite images, clouds canbe problematic. Thus, automatic detection ofclouds inthe imagesis ofgreat use. This master thesis was carried out at Vricon, who produces 3D models of the earth from satellite images.This thesis aimed to investigate if Support Vector Machines could classify pixels into cloud or non-cloud, with a combination of texture and color as features. To solve the stated goal, the task was divided into several subproblems, where the first part was to extract features from the images. Then the images were preprocessed before fed to the classifier. After that, the classifier was trained, and finally evaluated.The two methods that gave the best results in this thesis had approximately 95 % correctly classified pixels. This result is better than the existing cloud segmentation method at Vricon, for the tested terrain and cloud types.
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Jamborová, Soňa. "Segmentace obrazu pomocí neuronové sítě." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236925.
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This work is about suggestion of the software for neural network based image segmentation. It defines basic terms for this topics. It is focusing mainly at preperation imaging information for image segmentation using neural network. It describes and compares different aproaches for image segmentation.
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önder, gül, and aydın kayacık. "Multiview Face Detection Using Gabor Filter and Support Vector Machines." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-2152.
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Face detection is a preprocessing step for face recognition algorithms. It is the localization of face/faces in an image or image sequence. Once the face(s) are localized, other computer vision algorithms such as face recognition, image compression, camera auto focusing etc are
applied. Because of the multiple usage areas, there are many research efforts in face processing. Face detection is a challenging computer vision problem because of lighting conditions, a high degree of variability in size, shape, background, color, etc. To build fully
automated systems, robust and efficient face detection algorithms are required.
Numerous techniques have been developed to detect faces in a single image; in this project we have used a classification-based face detection method using Gabor filter features. We have designed five frequencies corresponding to eight orientations channels for extracting facial features from local images. The feature vector based on Gabor filter is used as the input of the face/non-face classifier, which is a Support Vector Machine (SVM) on a reduced feature
subspace extracted by using principal component analysis (PCA).
Experimental results show promising performance especially on single face images where 78% accuracy is achieved with 0 false acceptances.
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Almeida, Osvaldo Cesar Pinheiro de. "Técnicas de processamento de imagens para localização e reconhecimento de faces." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-22012007-160023/.
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A biometria é a ciência que estuda a mensuração dos seres vivos. Muitos trabalhos exploram as características dos seres humanos tais como, impressão digital, íris e face, a fim de desenvolver sistemas biométricos, utilizados em diversas aplicações (monitoramento de segurança, computação ubíqua, robótica). O reconhecimento de faces é uma das técnicas biométricas mais investigadas, por ser bastante intuitiva e menos invasiva que as demais. Alguns trabalhos envolvendo essa técnica se preocupam apenas em localizar a face de um indivíduo (fazer a contagem de pessoas), enquanto outros tentam identificá-lo a partir de uma imagem. Este trabalho propõe uma abordagem capaz de identificar faces a partir de quadros de vídeo e, posteriormente, reconhecê-las por meio de técnicas de análise de imagens. Pode-se dividir o trabalho em dois módulos principais: (1) - Localização e rastreamento de faces em uma seqüência de imagens ( frames), além de separar a região rastreada da imagem; (2) - Reconhecimento de faces, identificando a qual pessoa pertence. Para a primeira etapa foi implementado um sistema de análise de movimento (baseado em subtração de quadros) que possibilitou localizar, rastrear e captar imagens da face de um indivíduo usando uma câmera de vídeo. Para a segunda etapa foram implementados os módulos de redução de informações (técnica Principal Component Analysis - PCA), de extração de características (transformada wavelet de Gabor), e o de classificação e identificação de face (distância Euclidiana e Support Vector Machine - SVM). Utilizando-se duas bases de dados de faces (FERET e uma própria - Própria), foram realizados testes para avaliar o sistema de reconhecimento implementado. Os resultados encontrados foram satisfatórios, atingindo 91,92% e 100,00% de taxa de acertos para as bases FERET e Própria, respectivamente.Biometry is the science of measuring and analyzing biomedical data. Many works in this field have explored the characteristics of human beings, such as digital fingerprints, iris, and face to develop biometric systems, employed in various aplications (security monitoring, ubiquitous computation, robotic). Face identification and recognition are very apealing biometric techniques, as it it intuitive and less invasive than others. Many works in this field are only concerned with locating the face of an individual (for counting purposes), while others try to identify people from faces. The objective of this work is to develop a biometric system that could identify and recognize faces. The work can be divided into two major stages: (1) Locate and track in a sequence of images (frames), as well as separating the tracked region from the image; (2) Recognize a face as belonging to a certain individual. In the former, faces are captured from frames of a video camera by a motion analysis system (based on substraction of frames), capable of finding, tracking and croping faces from images of individuals. The later, consists of elements for data reductions (Principal Component Analysis - PCA), feature extraction (Gabor wavelets) and face classification (Euclidean distance and Support Vector Machine - SVM). Two faces databases have been used: FERET and a \"home-made\" one. Tests have been undertaken so as to assess the system\'s recognition capabilities. The experiments have shown that the technique exhibited a satisfactory performance, with success rates of 91.97% and 100% for the FERET and the \"home-made\" databases, respectively.
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Kiernan, Mary. "Implementation and design of the discrete Gabor filter for sonar texture classification." Thesis, Heriot-Watt University, 1995. http://hdl.handle.net/10399/766.
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Konuk, Baris. "Palmprint Recognition Based On 2-d Gabor Filters." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608138/index.pdf.
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In this thesis work, a detailed analysis of biometric technologies has been done and a new palmprint recognition algorithm has been implemented. The proposed algorithm
is based on 2-D Gabor filters. The developed algorithm is first tested on The Hong Kong Polytechnic University Palmprint Database in terms of accuracy, speed and template size. Then a scanner is integrated into the developed algorithm in order to acquire palm imagesin this way an online palmprint recognition system has been developed. Then a small palmprint database is formed via this system in Middle East Technical University. Results on this new database have also shown the success of the developed algorithm.
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Davis, Craig Alton Denney Thomas Stewart. "Applications of multi-channel filter banks to textured image segmentation." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Summer/Theses/DAVIS_CRAIG_12.pdf.
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Ravikumar, Rahul. "Multi-scale texture analysis of remote sensing images using gabor filter banks and wavelet transforms." Thesis, [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3175.
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Mar, Nang Seng Siri. "Vision-based classification of solder joint defects." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/37273/1/Nang_Mar_Thesis.pdf.
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Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. The solder joint inspection problem is more challenging than many other visual inspections because of the variability in the appearance of solder joints. Although many research works and various techniques have been developed to classify defect in solder joints, these methods have complex systems of illumination for image acquisition and complicated classification algorithms. An important stage of the analysis is to select the right method for the classification. Better inspection technologies are needed to fill the gap between available inspection capabilities and industry systems.
This dissertation aims to provide a solution that can overcome some of the limitations of current inspection techniques. This research proposes two inspection steps for automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localization and segmentation. The illumination normalisation approach can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image.
The “back-end” inspection involves the classification of solder joints by using Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. Further testing demonstrates the advantage of Log Gabor filter over both Discrete Wavelet Transform and Discrete Cosine Transform. Classifier score fusion is analysed for improving recognition rate. Experimental results demonstrate that the proposed system improves performance and robustness in terms of classification rates. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. In fact, the choice of suitable features allows one to overcome the problem given by the use of non complex illumination systems. The new system proposed in this research can be incorporated in the development of an automated non-contact, non-destructive and low cost solder joint quality inspection system.
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Hong, Paul S. "Octave-band Directional Decompositions." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7210.
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A new two-dimensional transform is derived and implemented that is able to discriminate with respect to angular and radial frequency. This octave-band directional filter bank (OBDFB) is maximally decimated, has a separable polyphase implmentation, provides perfect reconstruction, and can be implemented in a tree structure allowing for a somewhat arbitrary number of angular and radial divisions. This decomposition is based on the directional filter bank (DFB) and is compared to other transforms with similar properties. Additionally, the OBDFB is used in three applications. Texture segmentation results are provided with comparisons to both decimated and undecimated transforms. With hyperspectral data, the OBDFB is used to increase classification accuracy using texture augmentation and likelihood score combination. Finally, ultrasound despeckling is addressed with respect to real-time implementations, and subjective test results are presented. A non-uniform two-dimensional transform is also designed that is a modified version of the OBDFB. It is rationally sampled and maximally decimated, but it provides both angular and radial frequency passbands from the initial stage instead of making separate divisions like the OBDFB. It also does not create subband boundaries on the principal frequency axes and allows for further decomposition as well.
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Hammarqvist, Ulf. "Audio editing in the time-frequency domain using the Gabor Wavelet Transform." Thesis, Uppsala universitet, Centrum för bildanalys, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-153634.
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Visualization, processing and editing of audio, directly on a time-frequency surface, is the scope of this thesis. More precisely the scalogram produced by a Gabor Wavelet transform is used, which is a powerful alternative to traditional techinques where the wave form is the main visual aid and editting is performed by parametric filters. Reconstruction properties, scalogram design and enhancements as well audio manipulation algorithms are investigated for this audio representation.The scalogram is designed to allow a flexible choice of time-frequency ratio, while maintaining high quality reconstruction. For this mean, the Loglet is used, which is observed to be the most suitable filter choice. Re-assignmentare tested, and a novel weighting function using partial derivatives of phase is proposed. An audio interpolation procedure is developed and shown to perform well in listening tests.The feasibility to use the transform coefficients directly for various purposes is investigated. It is concluded that Pitch shifts are hard to describe in the framework while noise thresh holding works well. A downsampling scheme is suggested that saves on operations and memory consumption as well as it speeds up real world implementations significantly. Finally, a Scalogram 'compression' procedure is developed, allowing the caching of an approximate scalogram.
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Ouyang, Dingxin. "Intelligent Road Control System Using Advanced Image Processing Techniques." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1352749656.
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Sa, Gustavo Ferreira Cardoso de. "Melhorias no reconhecimento de impressões digitais baseado no metodo FingerCode." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259831.
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Orientador: Roberto de Alencar LotufoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
Made available in DSpace on 2018-08-07T11:27:50Z (GMT). No. of bitstreams: 1 Sa_GustavoFerreiraCardosode_M.pdf: 2313623 bytes, checksum: ca6abbf3a186c9d5bed2d6b1e73e3a9f (MD5) Previous issue date: 2006
Resumo: Neste trabalho são apresentadas melhorias na robustez do método FingerCode para reconhecimento de impressões digitais. No FingerCode a textura dos componentes orientados das impressões digitais são extraídas por um banco direcional de filtros Gabor. Posteriormente, os componentes orientados são setorizados e para cada setor é computado um valor. Este conjunto de valores forma o vetor de atributos. Finalmente, a média da diferença absoluta dos dois vetores de atributos é computada indicando a similaridade entre duas impressões digitais. Foram testadas várias soluções e entre as que apresentaram melhores resultados destacam-se: a substituição dos valores dos atributos através de uma função não-linear, a ponderação dos valores de atributo de acordo com características estatísticas da distribuição espacial dos valores e o cálculo de medidas estatísticas extraídas dos histogramas de distribuição de diferenças. Estas funções apresentaram um ganho significativo, principalmente para o caso dos sensores óticos com uma melhoria de aproximadamente 45% no EER. Outra contribuição apresentada foi uma nova implementação rápida do filtro Gabor 2D, que se constitui de uma onda sinusoidal modulada por um envelope gaussiano. A filtragem 2D da imagem por um banco de filtros Gabor 2D é uma das etapas de maior consumo de tempo no processamento de imagens. Na nova solução proposta, o filtro Gabor 2D é separado em dois filtros Gabor 1D ortogonais, bastando para isto que o envelope gaussiano obedeça a condição de ser circular. O processamento com o filtro separado é mais rápida do que com o filtro não-separado e o ganho na performance aumenta à medida que aumenta o tamanho da imagem ou do filtro. Também foram desenvolvidas novas técnicas de segmentação: baseada em morfologia matemática e baseada em filtros Gabor. Estas segmentações ocorrem ao nível do píxel, com ótimos resultados, principalmente após a uniformização da área através de processos morfológicos
Abstract: In this work it is introduced improvements in robustness of FingerCode method to recognize fingerprints. In the FingerCode the texture of fingerprint oriented components are extracted by a bank of directional Gabor filters. After that, the oriented components are tessellated and a value is computed for each sector. This set of values constitutes the attribute vector. Finally, the absolute difference mean between the two attribute vectors is computed that gives the similarity between two fingerprints. New solutions were tested; among them the best results were obtained by: attribute values replacement by a non-linear function, attribute values weighting by statistical characteristics of spatial distribution of values, and the calculus of statistical measures extracted from the difference distribution histograms. These functions presented a significant gain, mainly in the case of optical sensors with an improvement about 45% in EER. Another contribution presented was a new fast implementation of the 2D Gabor filter, which constitutes in a sinusoidal wave modulated by a Gaussian envelope. The 2D image filtering by a bank of 2D Gabor filters is one of the most expensive stage of image processing. In the new solution proposed, the 2D Gabor filter is separated in two orthogonal 1D Gabor filters, for this the Gaussian envelope must obey the condition of being circular. Processing with the separated filter is faster than the non-separated filter, and the gain improves as the size of image or filter increases. Also it was developed new segmentation techniques: based on mathematical morphology, and based on Gabor filters. Those segmentations occur at pixel level, with good results, mostly after the area regularization with morphological processes
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica
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Wang, Shanshan. "Study of analytic and trained dictionaries for sparse representation and its applications." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/11486.
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Inverse problems are ubiquitous in the field of medical imaging and image processing. Prominent examples include image reconstruction and image denoising. The goal of these problems is to reconstruct or restore an unknown image from a set of direct/indirect measurements. However, due to the limitation of the acquisition time or the existence of noise, the obtained measurements are often corrupted or incomplete, which introduces big challenges for the reconstruction process. In order to remove the noise or overcome the ill-posed nature caused by the insufficient measurements, it is necessary to explore the prior knowledge and utilize this to form constraints in the reconstruction process so as to make up for the missing or corrupted information. However, traditional prior knowledge regularizations and their corresponding algorithms suffer from loss of the detailed information such as texture and structure while reducing the image degradation factors. To this end, based on the physiological findings about human visual system (HVS), this thesis focuses on exploiting the prior knowledge of self-similarity and sparsity inherited in the image and has developed a series of novel algorithms via sparse representation over analytic and trained dictionaries. The main work and contributions are summarized as follows: 1) A Gabor feature based nonlocal means (GFNLM) algorithm for textured image restoration; 2) an adaptive dictionary learning based impulse noise removal (DL-INR) algorithm; 3) a Fenchel duality based dictionary learning (FD-DL) algorithm and 4) a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal and a joint entropy regularized bias removal approach.
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Zamazal, Zdeněk. "Ohodnocení okolí bodů v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236969.
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This master thesis is focused on parametrization of image point neighborhood. Some methods for point localization and point descriptors are described and summarized. Gabor filter is described in detail. The practical part of thesis is chiefly concerned with particle filter tracking system. The weight of each particle is determined by the Gabor filter.
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Ould, Amer Khadidja. "Prétraitements des images sous-marines basés sur la polarisation et le filtrage fréquentiel : application offshore Enhancing underwater optical imaging by using a low-pass polarization filter, in Optics Express 27(2), 2019." Thesis, Brest, 2019. http://www.theses.fr/2019BRES0049.
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L'étude du milieu sous-marin nécessite des avancées technologiques importantes notamment en ce qui concerne le développement des véhicules sous-marins autonomes et en particulier, leurs capteurs de perception. Le travail de cette thèse avait pour objectif d'apporter des solutions permettant d'améliorer la qualité des images sous-marines dans le but de promouvoir l'emploi des robots sous-marins autonomes. La rapidité de calcul est un point très essentiel, car les robots autonomes sont limités par les contraintes d'énergie, la capacité de calcul et de stockage. Dans ce contexte, une méthode rapide et efficace d'amélioration de la qualité d’images sous-marines a été proposée. D'une part, cette méthode utilise un système optique d'imagerie polarimétrique pour réduire les effets de diffusion lors de l'acquisition d'images. D'autre part, elle est basée sur une version optimisée de la méthode DCP (dark channel prior) qui est très répondue pour le débrumage d’images sous-marines.Dans cette thèse, nous nous intéressons également à la détection et à l'identification de marqueurs utilisés pour le docking automatique d'un véhicule sous-marin avec une station immergée. Le succès de cette tâche nécessite un bon contraste dans la zone où se situe le marqueur. Pour résoudre ce problème, une méthode de débrumage orientée-objet est proposée pour optimiser le contraste des marqueurs. La stratégie proposée exploite les caractéristiques de texture dérivées du filtrage multicanal de Gabor pour la segmentation d'images. Une fois que les différents objets de l’image sont séparés, une version optimisée du Dark Channel Prior (DCP) est appliquée pour optimiser le contraste de chaque objet. Les résultats obtenus, sur une large base de données d’images de marqueurs, montrent que la méthode proposée améliore sensiblement la détection et l'identification des marqueurs en environnement sous-marinStudy of the underwater environment requires significant technological advances, particularly, in the development of autonomous underwater vehicles, and their perception sensors. This thesis is dealing with the development of a real time solution for underwater image quality improvement in order to promote the use of autonomous underwater vehicles. Developing a fast image processing algorithms are required due the limitations of these kinds of vehicles in terms of energy, computing capacity and storage. In this context, a fast and effective method of underwater image quality improvement has been proposed. On the one hand, this method uses a polarimetric imaging optical system to reduce the diffusion effects on the image acquisition.On the other hand, it is based on an optimized version of the dark channel prior (DCP) method that has received a great deal for image dehazing.In this thesis, we are also interested in the detection and the identification of markers used for the automatic docking of an underwater vehicle with a submerged station. The success of this task requires a good contrast in the area where the marker is located. To solve this problem, an object-oriented dehazing method is proposed to optimize the contrast of markers. The proposed strategy exploits the texture features derived by Gabor multichannel filtering for image segmentation. Once different objects of the image are separated, an optimized Dark Channel Prior dehazing method is applied to optimize the contrast of each individual object. The system has been tested on a large image dataset and the obtained results show that the object-oriented dehazing improves the markers identification in underwater environment
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Nutakki, Gopi Chand. "Appearance Based Stage Recognition of Drosophila Embryos." TopSCHOLAR®, 2010. http://digitalcommons.wku.edu/theses/217.
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Stages in Drosophila development denote the time after fertilization at which certain specific events occur in the developmental cycle. Stage information of a host embryo, as well as spatial information of a gene expression region is indispensable input for the discovery of the pattern of gene-gene interaction. Manual labeling of stages is becoming a bottleneck under the circumstance of high throughput embryo images. Automatic recognition based on the appearances of embryos is becoming a more desirable scheme. This problem, however, is very challenging due to severe variations of illumination and gene expressions. In this research thesis, we propose an appearance based recognition method using orientation histograms and Gabor filter. Furthermore, we apply Principal Component Analysis to reduce the dimension of the low-level features, aiming to accelerate the speed of recognition. With the experiments on BDGP images, we show the promise of the proposed method.
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Fonseca, Everthon Silva. "Wavelets, predição linear e LS-SVM aplicados na análise e classificação de sinais de vozes patológicas." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-04072008-094655/.
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Neste trabalho, foram utilizadas as vantagens da ferramenta matemática de análise temporal e espectral, a transformada wavelet discreta (DWT), além dos coeficientes de predição linear (LPC) e do algoritmo de inteligência artificial, Least Squares Support Vector Machines (LS-SVM), para aplicações em análise de sinais de voz e classificação de vozes patológicas. Inúmeros trabalhos na literatura têm demonstrado o grande interesse existente por ferramentas auxiliares ao diagnóstico de patologias da laringe. Os componentes da DWT forneceram parâmetros de medida para a análise e classificação das vozes patológicas, principalmente aquelas provenientes de pacientes com edema de Reinke e nódulo nas pregas vocais. O banco de dados com as vozes patológicas foi obtido do Departamento de Otorrinolaringologia e Cirurgia de Cabeça e Pescoço do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto (FMRP-USP). Utilizando-se o algoritmo de reconhecimento de padrões, LS-SVM, mostrou-se que a combinação dos componentes da DWT de Daubechies com o filtro LP inverso levou a um classificador de bom desempenho alcançando mais de 90% de acerto na classificação das vozes patológicas.The main objective of this work was to use the advantages of the time-frequency analysis mathematical tool, discrete wavelet transform (DWT), besides the linear prediction coefficients (LPC) and the artificial intelligence algorithm, Least Squares Support Vector Machines (LS-SVM), for applications in voice signal analysis and classification of pathological voices. A large number of works in the literature has been shown that there is a great interest for auxiliary tools to the diagnosis of laryngeal pathologies. DWT components gave measure parameters for the analysis and classification of pathological voices, mainly that ones from patients with Reinke\'s edema and nodule in the vocal folds. It was used a data bank with pathological voices from the Otolaryngology and the Head and Neck Surgery sector of the Clinical Hospital of the Faculty of Medicine at Ribeirão Preto, University of Sao Paulo (FMRP-USP), Brazil. Using the automatic learning algorithm applied in pattern recognition problems, LS-SVM, results have showed that the combination of Daubechies\' DWT components and inverse LP filter leads to a classifier with good performance reaching more than 90% of accuracy in the classification of the pathological voices.
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Liang, Xusheng. "Comparative study of table layout analysis : Layout analysis solutions study for Swedish historical hand-written document." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17643.
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Background. Nowadays, information retrieval system become more and more popular, it helps people retrieve information more efficiently and accelerates daily task. Within this context, Image processing technology play an important role that help transcribing content in printed or handwritten documents into digital data in information retrieval system. This transcribing procedure is called document digitization. In this transcribing procedure, image processing technique such as layout analysis and word recognition are employed to segment the document content and transcribe the image content into words. At this point, a Swedish company (ArkivDigital® AB) has a demand to transcribe their document data into digital data. Objectives. In this study, the aim is to find out effective solution to extract document layout regard to the Swedish handwritten historical documents, which are featured by their tabular forms containing the handwritten content. In this case, outcome of application of OCRopus, OCRfeeder, traditional image processing techniques, machine learning techniques on Swedish historical hand-written document is compared and studied. Methods. Implementation and experiment are used to develop three comparative solutions in this study. One is Hessian filtering with mask operation; another one is Gabor filtering with morphological open operation; the last one is Gabor filtering with machine learning classification. In the last solution, different alternatives were explored to build up document layout extraction pipeline. Hessian filter and Gabor filter are evaluated; Secondly, filter images with the better filter evaluated at previous stage, then refine the filtered image with Hough line transform method. Third, extract transfer learning feature and custom feature. Fourth, feed classifier with previous extracted features and analyze the result. After implementing all the solutions, sample set of the Swedish historical handwritten document is applied with these solutions and compare their performance with survey. Results. Both open source OCR system OCRopus and OCRfeeder fail to deliver the outcome due to these systems are designed to handle general document layout instead of table layout. Traditional image processing solutions work in more than a half of the cases, but it does not work well. Combining traditional image process technique and machine leaning technique give the best result, but with great time cost. Conclusions. Results shows that existing OCR system cannot carry layout analysis task in our Swedish historical handwritten document. Traditional image processing techniques are capable to extract the general table layout in these documents. By introducing machine learning technique, better and more accurate table layout can be extracted, but comes with a bigger time cost.Scalable resource-efficient systems for big data analytics
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Bouwer, Pieter. "Modelling, design and implementation of a small-scale, position sensorless, variable speed wind energy conversion system incorporating DTC-SVM of a PMSG drive with RLC filter." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80242.
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Thesis (MScEng)--Stellenbosch University, 2013.Wind energy has proven to be a viable source of clean energy, and the worldwide demand is growing rapidly. Variable speed topologies, with synchronous generators and full-scale converters, are becoming more popular, and the e ective control of these systems is a current trend in wind energy research. The purpose of this study is the modelling, design, simulation and implementation of a small-scale, variable speed wind energy conversion system, incorporating the position sensorless direct torque control with space vector modulation, of a permanent magnet synchronous generator, including an RLC converter lter. Another aim is the development of a gain scheduling algorithm that facilitates the high level control of the system. Mathematical models of the combined lter-generator model, in the stationary and rotating reference frames, are presented and discussed, from which equivalent approximate transfer functions are derived for the design of the controller gains. The design of the controller gains, RLC lter components, gain scheduling concept and maximum power point tracking controller are presented. It is discovered that the RLC lter damping resistance has a signi cant e ect on the resonance frequency of the system. The system is simulated dynamically in both Simulink and the VHDL-AMS programming language. Additionally, the maximum power point tracking controller is simulated in the VHDL-AMS simulation, including a wind turbine simulator. The simulation results demonstrate good dynamic performance, as well as the variable speed operation of the system. The practical results of torque and speed controllers show satisfactory performance, and correlate well with simulated results. The detailed gain scheduling algorithm is presented and discussed. A nal test of the complete system yields satisfactory practical results, and con rms that the objectives of this thesis have been reached.
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Vaľko, Tomáš. "Biologicky inspirované metody rozpoznávání objektů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237033.
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Object recognition is one of many tasks in which the computer is still behind the human. Therefore, development in this area takes inspiration from nature and especially from the function of the human brain. This work focuses on object recognition based on extracting relevant information from images, features. Features are obtained in a similar way as the human brain processes visual stimuli. Subsequently, these features are used to train classifiers for object recognition (e.g. SVM, k-NN, ANN). This work examines the feature extraction stage. Its aim is to improve the feature extraction and thereby increase performance of object recognition by computer.
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Albanwan, Hessah AMYM. "Remote Sensing Image Enhancement through Spatiotemporal Filtering." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1492011122078055.
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Hymér, Pontus. "Extraction and Application of Secondary Crease Information in Fingerprint Recognition Systems." Thesis, Linköping University, Department of Science and Technology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2951.
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This thesis states that cracks and scars, referred to as Secondary Creases, in fingerprint images can be used as means for aiding and complementing fingerprint recognition, especially in cases where there is not enough clear data to use traditional methods such as minutiae based or correlation techniques. A Gabor filter bank is used to extract areas with linear patterns, where after the Hough Transform is used to identify secondary creases in a r, theta space. The methods proposed for Secondary Crease extraction works well, and provides information about what areas in an image contains usable linear pattern. Methods for comparison is however not as robust, and generates False Rejection Rate at 30% and False Acceptance Rate at 20% on the proposed dataset that consists of bad quality fingerprints. In short, our methods still makes it possible to make use of fingerprint images earlier considered unusable in fingerprint recognition systems.
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Zuo, Tianyu. "An Efficient Vision-Based Pedestrian Detection and Tracking System for ITS Applications." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31778.
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In this thesis, a novel Pedestrian Protection System (PPS), composed of the Pedestrian Detection System (PDS) and the Pedestrian Tracking System (PTS), was proposed. The PPS is a supplementary application for the Advanced Driver Assistance System, which is used to avoid collisions between vehicles and pedestrians.
The Pedestrian Detection System (PDS) is used to detect pedestrians from near to
far ranges with the feature-classi er-based detection method (HOG + SVM). To achieve pedestrian detection from near to far ranges, a novel structure was proposed. The structure of our PDS consists of two cameras (called CS and CL separately). The CS is equipped with a short focal length lens to detect pedestrians in near-to-mid range; and, the CL is equipped with a long focal length lens to detect pedestrians in mid-to-far range. To accelerate the processing speed of pedestrian detection, the parallel computing capacity of GPU was utilized in the PDS. The synchronization algorithm is also introduced to synchronize the detection results of CS and CL. Based on the novel pedestrian detection structure, the detection process can reach a distance which is more than 130 meters away without decreasing detection accuracy. The detection range can be extended more than
100 meters without decreasing the processing speed of pedestrian detection. Afterwards, an algorithm to eliminate duplicate detection results is proposed to improve the detection accuracy.
The Pedestrian Tracking System (PTS) is applied following the Pedestrian Detection
System. The PTS is used to track the movement trajectory of pedestrians and to predict the future motion and movement direction. A C + + class (called pedestrianTracking class, which is short for PTC) was generated to operate the tracking process for every detected pedestrian. The Kalman lter is the main algorithm inside the PTC. During the operation of PPS, the nal detection results of each frame from PDS will be transmitted to the PTS to enable the tracking process. The new detection results will be used to update the existing tracking results in the PTS. Moreover, if there is a newly detected pedestrian, a new process will be generated to track the pedestrian in the PTS. Based on the tracking results in PTS, the movement trajectory of pedestrians can be obtained and their future motion and movement direction can be predicted. Two kinds of alerts are generated based on the predictions: warning alert and dangerous alert. These two alerts represent di erent situations; and, they will alert drivers to the upcoming situations. Based on the predictions and alerts, the collisions can be prevented e ectively. The safety
of pedestrians can be guaranteed.
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Vladimir, Tadić. "Fazifikacija Gaborovog filtra i njena primena u detekciji registarskih tablica." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2018. https://www.cris.uns.ac.rs/record.jsf?recordId=107171&source=NDLTD&language=en.
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Disertacija prikazuje novi algoritam za detekciju i izdvajanje registarskih tablica iz slike vozila koristeći fazi 2D Gaborov filtar. Parametri filtra: orijentacija i talasna dužina su fazifikovani u cilju optimizacije odziva Gaborovog filtra i postizanja dodatne selektivnosti filtra. Prethodno navedeni parametri dominiraju u rezultatu filtriranja. Bellova i trougaona funkcija pripadnosti pokazale su se kao najbolji izbor pri fazifikaciji parametara filtra. Algoritam je evaluiran nad više baza slika i postignuti su zadovoljavajući rezultati. Komponente od interesa su efikasno izdvojene i postignuta značajna otpornost na šum i degradaciju na slici.The thesis presents a new algorithm for detection and extraction of license plates from a vehicle image using a fuzzy two-dimensional Gabor filter. The filter parameters, orientation and wavelengths are fuzzified to optimize the Gabor filter’s response and achieve a greater selectivity. It was concluded that Bell’s function and triangular membership function are the most efficient methods for fuzzification. Algorithm was evaluated on several databases and has provided satisfactory results. The components of interest were efficiently extracted, and the procedure was found to be very noise-resistant.
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Cunha, Camilla Lima. "Estudo da previsão de propriedades do biodiesel utilizando espectros de infravermelho e calibração multivariada." Universidade do Estado do Rio de Janeiro, 2014. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=7293.
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O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão por mínimos quadrados parciais (PLS), regressão de mínimos quadrados parciais por intervalos (iPLS), e regressão por máquinas de vetor de suporte (SVM) com seleção de variáveis por Algoritmo Genético (GA) foram utilizadas para modelar as propriedades mencionadas. As amostras de biodiesel foram sintetizadas a partir de diferentes fontes, tais como canola, girassol, milho e soja. Amostras adicionais de biodiesel foram adquiridas de um fornecedor da região sul do Brasil. Em primeiro lugar, o pré-processamento de correção de linha de base foi usado para normalizar os dados espectrais de NIR, seguidos de outros tipos de pré-processamentos que foram aplicados, tais como centralização dos dados na média, 1 derivada e variação de padrão normal. O melhor resultado para a previsão do ponto de entupimento de filtro a frio foi utilizando os espectros de Mid-IR e o método de regressão GA-SVM, com alto coeficiente de determinação da previsão, R2Pred=0,96 e baixo valor da Raiz Quadrada do Erro Médio Quadrático da previsão, RMSEP (C)= 0,6. Para o modelo de previsão da massa específica, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com R2Pred=0,98 e RMSEP (g/cm3)= 0,0002. Quanto ao modelo de previsão para o índice de refração, o melhor resultado foi obtido utilizando os espectros de Mid-IR e regressão por PLS, com excelente R2Pred=0,98 e RMSEP= 0,0001. Para esses conjuntos de dados, o PLS e o SVM demonstraram sua robustez, apresentando-se como ferramentas úteis para a previsão das propriedades do biodiesel estudadasBiodiesel has been widely used as a renewable energy source which contributes to the mineral diesel decrease demand. Therefore, there are several properties that must be monitored in order to produce and distribute biodiesel with the required quality. In this work, the biodiesel physical properties such as specific mass, refractive index and cold filter plugging point were measured and associated with near infrared spectroscopy (NIR) and mid-Infrared spectroscopy (mid-IR) spectra using chemometric tools. The Partial Least Squares Regression (PLS), Interval Partial Least Squares Regression (iPLS), and Support Vector Machines Regression (SVM) with variable selection by Genetic Algorithm (GA) methods were used to model the aforementioned properties. The biodiesel samples were synthesized from different sources such as canola, sunflower, corn, and soybean. Additional biodiesel samples were purchased from a Brazil South Region supplier. Firstly, the preprocessing baseline correction was used to normalize the NIR spectral data, following others preprocessing types were applied in such as the mean center, the first derivative and standard normal variate. The best result for predicting the cold filter plugging point was using Mid-IR spectra and GA-SVM regression method, with high coefficient determination of prediction, R2Pred = 0.94 and low value of the Root Mean Square Error of Prediction, RMSEP (C) = 0.7. For the specific mass prediction model, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP (g/cm3) = 0.0002. As for a prediction model for the refractive index, the best result was obtained using the Mid-IR spectrums and PLS regression, with the R2Pred = 0.98 and RMSEP = 0.0001. For these datasets, the PLS and SVM models demonstrated theirs robustness, presenting themselves as useful tools for the biodiesel properties prediction studied
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Vaňhara, Jaromír. "Vylepšení obrazu z ultrazvuku pro vizuální diagnostiku." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237002.
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Ultrasound imaging is widely used in medical examination. However, the interpretation of images is not trivial and requires much experience. In this thesis, various techniques for enhancement of visual quality of ultrasound images are presented. Several basic and advanced methods that may simplify the visual diagnosis are described. Finally, an interactive application is designed and implemented for simple usage of presented methods.
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Srinivasan, Ramprakash. "Computational Models of the Production and Perception of Facial Expressions." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531239299392184.
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Chrápek, David. "Učení a detekce objektů různých tříd v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236481.
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This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.
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Monteiro-Palagi, Patricia. "Décomposition fréquentielle des textures : caractérisation et segmentation." Grenoble INPG, 1995. http://www.theses.fr/1995INPG0182.
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Le theme de cette etude est l'analyse de la performance des attributs de textures extraits a partir d'une decomposition frequentielle similaire a celle realisee au niveau des premiers etages du cortex visuel. Par cette decomposition, des images sont segmentees en zones homogenes au sens de la texture. Pour analyser les distributions des caracteristiques produites, nous avons mis en place une methodologie d'analyse de donnees utilisant des techniques statistiques, neuronales et de traitement d'images. Les caracteristiques frequentielles sont issues d'une decomposition en multiresolution ou a chaque niveau sont implantes de filtres de type passe-bande orientee (filtres de gabor). Les techniques utilisees pour l'analyse de la complexite des distributions (caracteristiques dispersees, recouvrantes,. . . ) sont principalement les projections non lineaires par reseaux de neurones auto-organisants et la classification hierarchique ascendante. Ces techniques offrent une representation des similarites dans l'espace multidimensionnel des caracteristiques. Pour la segmentation, nous avons utilise un prototypage par simples agregations des donnees, dans le cadre d'une strategie non supervisee. Pour la discrimination, nous avons utilise un classement au plus proche voisin, dans le cadre d'une strategie supervisee. Les resultats obtenus sont presentes selon cette approche, analyses preliminaires de la distribution et tests suivant des protocoles non supervisee et supervisee. Les images analysees couvrent differents domaines, a savoir, des images utilisees en analyse psychophysique, ainsi que des images de textures naturelles a diverses granulosites utilisees en traitement d'images
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Kolman, Aleš. "Detekce obličejů ve videu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236583.
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The project is focused on face detection in video. Firstly, it contains a summary of basic color models. Secondly, you can find the description and comparison of the basic methods for detection of human skin with a practical example of implementation of parametric detector. Thirdly, a theoretical basis for face detection and face tracking in a video containing a list of basic concepts and methods of this issue follows. Greater emphasis is placed on the description of machine learning algorithm AdaBoost and description of the possible application of the Kalman filter for the purpose of face tracking. Design, implementation and testing of library accomplished within the master thesis are listed in the final part of this thesis.
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Maruniak, Lukáš. "Software pro biometrické rozpoznávání duhovky lidského oka." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-235000.
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In my thesis, I focus on the task of recognizing human iris from an image.In the beginning, the work deals with a question of biometrics, its importance and basic concepts, which are necessary for use in following text. Subsequently process of human Iris detection is described together with theory of evolution algorithms. In the implementation part, is described the design of implemented solution, which uses evolution algorithms, where is emphasis on correct pupil and iris boundary detection.
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Bodnarova, Adriana. "Texture analysis for automatic visual inspection and flaw detection in textiles." Thesis, Queensland University of Technology, 2000.
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Chiu, Po-Sheng, and 邱柏勝. "Face Recognition System Based on Circularly Symmetrical Gabor Filter and SVM." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/gfg46q.
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碩士國立中央大學
電機工程學系
103
In this thesis, the face recognition algorithm for the realization of Gabor filter and the support vector machine (SVM) classifier is proposed. In the proposed algorithm, the circularly symmetrical Gabor Filter (SCG Filter) is used to replace the traditional Gabor filter and the SVM classifier is integrated in the application of image recognition. While the face recognition algorithm based on the Gabor filter has good performance in improving robustness on face image variances, there are still some problems. The traditional Gabor filter has no rotation invariant and its calculation is too complicated. These problems will become an obstacle in application of image recognition. In this thesis, a CSG Filter is proposed to replace the traditional Gabor transform filter and the SVM is used to train images in face recognition. Also, we test the exclusivity of the system and the impact of filter parameters on identification efficiency to promote the effectiveness of the face recognition system.
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HARIKESH. "HAND POSTURE RECOGNITION USING SKIN, TEXTURE AND SALIENCY MAP." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14982.
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Hand Gesture Recognition (HGR) systems are paying more attention in the present scenario due to a wide range of application in real life. These systems are based on the processing of an incoming digital image. In this thesis, the first task is to separate the hand from rest of the image. This can be achieved in several ways and depends on whether the image includes only a hand against a background or the entire person. All the techniques proposed have some limitations. Their performance is affected by the illumination or lighting conditions and complex backgrounds of the hand images. To overcome the above mentioned limitations, a new technique is proposed for Hand Posture Recognition using Skin, Texture and Saliency map which involve classification of hand gesture. It efficiently makes the use of different color spaces, skin detection, saliency map and texture of an image. To recognize the hand gesture classes the features are extracted using the proposed methodology. These features are used for the classification purpose. Finally the application of multi-class SVM classifier is employed to recognize the hand gesture class. The experiments show that the proposed model has stable performance for a wide range of images.
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HSIANG, Hu HISH, and 胡士祥. "Fingerprint Recognition Using Gabor Filter." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/07177690489814313804.
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Bhoi, Khagswar, and Dipesh Kumar Solanki. "Texture Segmentation Using Optimal Gabor Filter." Thesis, 2011. http://ethesis.nitrkl.ac.in/2490/1/Gabor--.pdf.
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Texture segmentation is one of the most important feature utilized in practical diagnosis because it can reveal the changing tendency of the image. A texture segmentation method based on Gabor lter is proposed in the project. This method synthesis the information of location, color and texture features to be the wight, this can make satisfactory segmentation according to texture of image. The experiment shows that overall rate correctness for this method exceeds 81%.
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Chen, Chun-wei, and 陳俊瑋. "A SVM Face Recognition Method Based on Gabor Feature Extraction." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/ryw274.
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碩士國立臺灣科技大學
電機工程系
94
The study in biometrics field has vigorous development these years, especially in feature-based recognition field. Since the September 11 attacks, there are more and more specialists dig into biometrics field to develop a security system to guard against the horror attacks; therefore, the study in face recognition has become one popular method in biometrics researches. However, the face recognition is the not easy to reach high recognition rate even though it is the most intuitional method. It is a good way to extract features by using Gabor filter, especially in finger print recognition and face recognition. The statistical learning theory is a hot topic these decades. The neural network has been used in many applications and has performed very well. These years, the support vector machine has showed its good classification ability and there are many papers proved that it performs better than neural network in some applications such as biometrics recognition, document classification, and data mining. In this thesis, I built a MATLAB GUI based security platform. This platform combines Gabor feature extraction, SVM classification, and duo-threshold concepts to simulate the real-world security system. While using the SVM classifiers, I adopted one-against-rest method instead of one-against-one method because the former one has better exclusivity.
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Chun-FuChen and 陳均富. "Texture Segmentation Based on Gabor Filter Banks." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/23964624055717417358.
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碩士國立成功大學
電機工程學系碩博士班
98
Texture plays a critical role in images and videos and different representation of one texture to another texture is a critical issue. This thesis explored the capability of Gabor filter banks in analyzing texture via the parameters of the bases of the Gabor filter. The versatile properties of Gabor filter bank includes (a) the multi-scale property in being adaptive to objects having different scales, (b) invariant features, including scale, shifting, and rotational invariance, (c) the ability to characterize natural textures with multiple directions, and (d) the capability in providing locality information for different frequency components. This thesis discussed the utilization of these Gabor properties in the analysis of natural textures contained within the Brodatz album, a popular database in the texture analysis field. Other algorithms such as wavelet transform, Radon transform, and co-occurrence matrix are also applied to texture segmentation for comparison to the proposed Gabor transform. Experimental results show the superiority of the Gabor filters over the above mentioned algorithms in terms of feature extraction and texture segmentation. Furthermore, the thesis also explored the potentials of Gabor filter banks in the segmentation of natural images.
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Tu, Hsiu-Yun, and 涂秀雲. "An Enhanced Gabor Filter for face recognition." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/01300930535029503839.
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碩士國立高雄第一科技大學
資訊管理系企業電子化碩士班
102
In this paper, we proposed a new face recognition which is based on maximizing-phase gabor filter for face feature enhancement. Then we use two-dimensional principal component analysis to convert the gabor filtered face images into a covariance matrix for each person. Final we use Euclidean distance to calculate the recognition results. The experimental results compare the proposed method with the traditional face recognition algorithm and shows that our method is better than the related methods.
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Chang, Chia-Chen, and 張家甄. "Breast Tumor Identification with Gabor Filter on Sonogram." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/35342916756910840333.
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碩士國立宜蘭大學
資訊工程研究所碩士班
98
Evolution and use of ultrasonic technology are widely applied to the medical image. The ultrasound is the most popular way for making a diagnosis; however, a noisy ultrasound image will reduce its overall diagnostic efficiency. In order to real-time ultrasound scans for segmenting and identifying the tumors, the main purpose of my study is to develop an adaptive initial contouring method for segmenting tumors in ultrasound images, and using my proposed texture extraction method to provide a physician some tumor diagnosis information. In my research methodology, the image preprocessing is by the Gaussian low-pass filter to eliminate the speckle in ultrasound image. Such as method of image enhancement, my study used histogram equalization in the specific region of gray level distribution of the US images. Next, my paper used Level Set and Fast Marching Method with adaptive initial contouring to segment possible tumor blocks. Then according to twelve orientations and five kinds of frequency of Gabor filter, my research proposed a mean expectation method to extract feature of possible tumors. In addition, my proposed feature extraction was combined with Auto-correlation. Finally, input the statistical information to neural network to perform training. After obtaining knowledge bases, the tumors can be identified effectively. It is therefore clinically useful to improve the diagnostic efficiency and offer a second reading to assist physicians in medical diagnosis.
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Wang, Song-Ren, and 王頌仁. "Lane Detection Based On Gabor Filter and Color Cue." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/uptzw7.
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碩士國立臺灣大學
電機工程學研究所
106
In recent years, in order to avoid the accidents which are caused by the lack of recognition and miss judgement by drivers, the driving assistance system become a very popular issue. Lane detection plays an important role in the driving assistance system. The position of lane can provide information for system to give a warning when the vehicle occur departure or automatically correct the dangerous action in the future. This paper presents a texture-based method. Gabor filter is utilized to find the texture orientation on the image from monocular camera. Based on the three assumptions on the lane, combine with color cue and texture orientation distribution to select the possible lane region. At the end, use the line model to represent the lane region. The method is divided into three parts, the first is to find the texture by Gabor filter, and detect the vanishing point with known texture orientation, then remove the unrelated region with the color information of lanes and detected vanishing point. After that, find the representative lane texture orientation with the accumulation of texture intensity. At the end, mark the region in lane texture orientation, and optimize the representative line with orientation consistent number (OCN). In this thesis, the lane can be detected accurately in the difference scenes, including freeway, downtown, country, and campus. In most time, the lane can be detected accurately except the red lane is too dark or the lane is cover by objects. As a result, based on two conditional limitations, the experiment in freeway can reach 96.67% successful ratio, other scene such as downtown, country, campus can reach 60%, 80%, and 50% respectively.
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Liao, Fu-Hsin, and 廖福信. "Textural feature extraction and texture reconstruction based on Gabor filter bank." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/25916543445350938297.
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碩士逢甲大學
通訊工程所
93
The purpose of this thesis is to develop a scheme of texture analysis and reconstruction based on a Gabor filter bank. The peak frequency components of a given texture are extracted from the outputs of the Gabor filter bank in the spatial and spatio-frequency domain. The extraction process could be implemented by either a supervised or non-supervised manner. Grouping the extracted peak frequency components facilitates the texture segmentation procedure. Provided with the parameters of the peak frequency components for a given texture, the texture image is approximately reconstructed by applying the frame theory.
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Lee, Kun-Ta, and 李坤達. "Investigation on face identification using Gabor Filter and spiking neural networks." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/j3j463.
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Chang, Wen-Lin, and 臧文菱. "Gabor filter-aided Diagnosis System for 3D Ultrasonography with Variance Estimation." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/83039631671670164519.
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碩士國立宜蘭大學
資訊工程研究所碩士班
97
Rationale and Objectives: The evaluate the accuracy of three-dimensional (3D) ultrasound in differentiating benign and malignant breast tumors by using neural network. Materials and Methods: The 3D US imaging was performed using a Voluson 530 scanner. The 5-10 MHz linear-array transducer with a scan width of 40 mm and a sweep angle of 20-25 is used to perform a 3-D volume scan. 3D ultrasonography was obtained from 192 patients with 128 benign and 64 malignant breast tumors. To computer-aided detection (CAD) technology Import the system. Choose the middle section of ultrasonic file and next slice, two images at the same time by the Gaussian low-pass filter to eliminate the speckle noise in ultrasound imaging. Such as method of image enhancement, Watershed algorithm with morphology found the edge of tumor. Select the region of tumor, and then with eight kinds of different angles and frequency Gabor filter to calculate changes in the tumor and the extent of the edge. Input the statistical information to neural network to training. Results: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of segmentation for Otsu method were 96%, 95%,96%,93% and 97%. Texture extraction of 128 benign calculated by the average of variance is below 0.2. And 64 malignant calculated by the variance are 0.4 above the average. Conclusions: The texture variance of 3D ultrasound is in differentiating benign and malignant breast tumors by using neural network. Experimental investigations demonstrated that the texture variance of 3D ultrasound were effective and useful for differential diagnosis of breast tumors. Texture extraction with proposed method can found malignant more accurate than auto-correlation.
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Yang, Qing hong, and 楊慶鴻. "An Age Classification System Using Gabor Filter And Local Binary Pattern." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/41857639716028708545.
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碩士長庚大學
電機工程學系
99
Abstract In age-based classification studies, it is found that accuracy and feature extraction are the two most important areas that need further improvement in the facial identification technique. Pre-processing and the actual content of input image also significantly affect the accuracy of facial identification. In previous studies, many researchers had adopted the complete image domain approach in the image processing, such as Principal Component Analysis (PCA) and Linear Discriminate Analysis (LDA). Since the complete image domain analysis method often causes the degradation of facial identification quality as affected by the distortion of image acquisition, texture descriptor has in recent years gradually gained significance in pattern recognition. Based on this concept, the study proposes a new age-based classification system by combing the advantages of several methods. The framework of this study consists of three components: image pre-processing, feature extraction and classification of recognizable modules. This study mainly relies on Local Binary Graphics Pattern (LBP) and Gabor Filters (GF) to extract texture features from the face. Distinguishing from traditional methods, the study employs a new method for reducing the number of dimensions by using the Principal Component Analysis (PCA) for multi-dimensional reduction of the acquired data while maintaining the data features in the original high-dimensional feature space. This method can facilitate the classification of recognizable modules using the Support Vector Machine (SVM) classification, of which the results will be integrated through voting, and thereby establishing a voting mechanism for age-based classification. The study utilizes 800 images of facial data, including 400 adults and 400 children. From each group, 300 facial images were selected, totaling 600 for image training, and the remaining 200 were used for image testing. Our experimental results show that Local Binary Graphics Pattern, Gabor Filters, and Principal Component Analysis can be used to compliment each other (LBP + GF + PCA) in order to obtain the best recognition rate with 100% accuracy.
48
Yi-SiouChen and 陳怡秀. "The Analysis of Collagen Fibers in Medical Images Using Gabor Filter Banks." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/45727917948958212334.
Full textAbstract:
碩士國立成功大學
電機工程學系碩博士班
101
Human contains many hidden information and we can acquire, analyze hidden information and farther interpret hidden information to understand physiological phenomena or disease. In biomedical research, acquiring and analyzing biomedical images can efficaciously prevent and detect disease. In this thesis, we analyze and gain understanding the structure and features of collagen fibers in human skin by optical in vivo virtual biopsy images. For the application of biomedical images to investigate the relationship between features of collagen fibers and human medicine, a computer aided algorithm for quantifying features of collagen fiber is developed. The proposed algorithm has significant potential for biomedical image analysis and medical contributions. According to the results of this experiment we can come to the conclusion that our calculations are accurate.
49
Chen, Bin-Ge, and 陳秉哲. "A study of the intellectual IC Card with Gabor Filter for Fingerprint Authentication." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/96981157440572860219.
Full textAbstract:
碩士國立臺灣科技大學
電機工程系
92
Password is often the way for authentication conventionally, but may be the most dangerous one, because it could be easily stolen or counterfeited. However, the common authentication system that use password cannot be aware whether the password belong to this guest or not. In this aspect the fingerprint verification technology is just able to reform this drawback, because the fingerprint features are unique and cannot be stolen or counterfeited. For this reason, this technology is very suitable for authentication. The objective of this research is to build the authentication system that has the ability to verified fingerprint. In this research, we will focus on the problem of fingerprint core point detection and location that is weak in the common fingerprint verification system, and seek for the better resolution. Furthermore, in order to make the system have excellent performance of verification, a fingerprint verification system that is based on Gabor Filter combines Smart IC Card will be constructed to perform the authentication. The system comprises of two subsystems. The first subsystem performs the fingerprint core point detection and location in the image captured by a Image Capture Device, and segments the sub-image that is probably fingerprint image from the whole image; then the sub-image is sent to the second subsystem that performs the fingerprint verification after image processing and feature extraction. Eventually, the authentication result is made based on the recognition result.
50
Chen, Chun-Fu, and 陳俊富. "A Cabbage Image Classification Method Based on Gabor Filter and HSV Color Space." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/yhxgmq.
Full textAbstract:
碩士國立中興大學
資訊科學與工程學系
103
This is a preliminary project intends to use advanced information and communication technologies to establish crop production prediction models for cabbage. This paper is about the image processing of the project, and uses some available methods and algorithm to help users to judge cabbage or not. This paper includes many simply but pretty effective methods. For exterior features of cabbage, use Gabor Filters to calculate directions of cabbage and use Sobel Operator Filter to enhance the edges, and use FFT method to get last results. For colors of cabbage, through RGB color space to other color spaces, like YCbCr color space, and use some images of cabbage to do training and testing in SVM method, and the result is 84%. However, in this paper, there are some methods will be used to improve recognition rate of cabbage, here use HSV color space in colors of cabbage and add multi-direction in the images after Gabor Filter and Sobel Operator Filter to get more information through SVM method to judge it is a cabbage image or not, and feedback uses these data. The recognition rate of cabbage trough these improved methods is 96%.