Dissertations / Theses on the topic 'GRAY SCALE IMAGE'
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Fetter, Paul. "Heuristics for selecting gray scale morphological structuring elements /." Online version of thesis, 1994. http://hdl.handle.net/1850/11728.
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Ström, Bartunek Josef. "FINGERPRINT IMAGE ENHANCEMENT, SEGMENTATION AND MINUTIAE DETECTION." Doctoral thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-11149.
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Prior to 1960's, the fingerprint analysis was carried out manually by human experts and for forensic purposes only. Automated fingerprint identification systems (AFIS) have been developed during the last 50 years. The success of AFIS resulted in that its use expanded beyond forensic applications and became common also in civilian applications. Mobile phones and computers equipped with fingerprint sensing devices for fingerprint-based user identification are common today. Despite the intense development efforts, a major problem in automatic fingerprint identification is to acquire reliable matching features from fingerprint images with poor quality. Images where the fingerprint pattern is heavily degraded usually inhibit the performance of an AFIS system. The performance of AFIS systems is also reduced when matching fingerprints of individuals with large age variations. This doctoral thesis presents contributions within the field of fingerprint image enhancement, segmentation and minutiae detection. The reliability of the extracted fingerprint features is highly dependent on the quality of the obtained fingerprints. Unfortunately, it is not always possible to have access to high quality fingerprints. Therefore, prior to the feature extraction, an enhancement of the quality of fingerprints and a segmentation are performed. The segmentation separates the fingerprint pattern from the background and thus limits possible sources of error due to, for instance, feature outliers. Most enhancement and segmentation techniques are data-driven and therefore based on certain features extracted from the low quality fingerprints at hand. Hence, different types of processing, such as directional filtering, are employed for the enhancement. This thesis contributes by proposing new research both for improving fingerprint matching and for the required pre-processing that improves the extraction of features to be used in fingerprint matching systems. In particular, the majority of enhancement and segmentation methods proposed herein are adaptive to the characteristics of each fingerprint image. Thus, the methods are insensitive towards sensor and fingerprint variability. Furthermore, introduction of the higher order statistics (kurtosis) for fingerprint segmentation is presented. Segmentation of the fingerprint image reduces the computational load by excluding background regions of the fingerprint image from being further processed. Also using a neural network to obtain a more robust minutiae detector with a patch rejection mechanism for speeding up the minutiae detection is presented in this thesis.
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Becer, Huseyin Caner. "A Robust Traffic Sign Recognition System." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612912/index.pdf.
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The traffic sign detection and recognition system is an essential part of the driver warning and assistance systems. In this thesis, traffic sign recognition system is studied. We considered circular, triangular and square Turkish traffic signs. For detection stage, we have two different approaches. In first approach, we assume that the detected signs are available. In the second approach, the region of interest of the traffic sign image is given. Traffic sign is extracted from ROI by using a detection algorithm.
In recognition stage, the ring-partitioned method is implemented. In this method, the traffic sign is divided into rings and the normalized fuzzy histogram is used as an image descriptor. The histograms of these rings are compared with the reference histograms. Ring-partitions provide robustness to rotation because the rotation does not change the histogram of the ring. This is very critical for circle signs because rotation is hard to detect in circle signs. To overcome illumination problem, specified gray scale image is used.
To apply this method to triangle and square signs, the circumscribed circle of these shapes is extracted.
Ring partitioned method is tested for the case where the detected signs are available and the region of interests of the traffic sign is given. The data sets contain about 500 static and video captured images and the images in the data set are taken in daytime.
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Muhammad, Imran. "Colorizing Grey Scale Images." Thesis, Högskolan Dalarna, Datateknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:du-6181.
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The purpose of this thesis is to develop a working methodology to color a grey scale image. This thesis is based on approach of using a colored reference image. Coloring grey scale images has no exact solution till date and all available methods are based on approximation. This technique of using a color reference image for approximating color information in grey scale image is among most modern techniques.Method developed here in this paper is better than existing methods of approximation of color information addition in grey scale images in brightness, sharpness, color shade gradients and distribution of colors over objects.Color and grey scale images are analyzed for statistical and textural features. This analysis is done only on basis of luminance value in images. These features are then segmented and segments of color and grey scale images are mapped on basis of distances of segments from origin. Then chromatic values are transferred between these matched segments from color image to grey scale image.Technique proposed in this paper uses better mechanism of mapping clusters and mapping colors between segments, resulting in notable improvement in existing techniques in this category.
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Kowalewski, Damian. "Edge-based encoding of gray-scale images." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=80305.
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This thesis explores image compression based on visual information contained within the edges. This work is based on an observation that not all the information contained within an image is used by the human brain. Previous works demonstrate methods for reconstructing images adequately using edge information. We exploit the fact that some components of the image can be removed while having little effect on human perception: this is the key basis for the compression developed in this thesis. We first construct compression preserving all the edge information extracted from the image. We then consider the impact of removing some of the edge information to further improve the compression ratio. We direct our attention to two types of information associated with edges: (1) its location and shape, (2) intensity and blur values on each side of the edge. First we propose a method to encode edge location and shape in a most efficient manner. We propose a measure of redundancy to remove edges carrying information already encoded in neighboring edges. Then we consider the compression of intensities and blur associated with each edge. Since the intensity information is quite noisy we show that we can remove the noise and reduce intensity functions to linear functions without significant impact on the quality of a reconstructed image. Finally we introduce a method to encode pattern information not included in edge information to improve the overall quality of the reconstructed image.
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Dokladal, Petr. "Grey-scale image segmentation : a topological approach." Marne-la-Vallée, 2000. http://www.theses.fr/2000MARN0065.
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Le domaine aborde par cette these concerne la segmentation des images en niveaux de gris. Deux approches principales et independantes ont ete exploitees : l'application des graphes a l'operateur h-minima pour une segmentation des images multi-classes et la segmentation basee sur la topologie appliquee a l'angiographie du foie par tomographie. Une presentation des modeles mathematiques existants, utilises pour modeliser la topologie est faite dans un premier temps. Les modeles presentes sont discutes du point de vue de leurs applications a la segmentation d'images. La methode des h-minima est une methode de morphologie mathematique. Etant concue pour segmenter des images bi-classes, les images multi-classes peuvent etre segmentees par application des h-minima a l'image de gradient. L'extraction du gradient entraine toutefois une perte inevitable d'information dans l'image. Une modification des h-minima fondee sur des graphes ponderes d'adjacence de regions est etudiee. L'extraction du gradient devenant superflue, cette approche permet l'application des h-minima aux images multi-classes. La segmentation d'angiographie 3-d de foie, proposee dans la derniere partie de ce manuscrit, est fondee sur la topologie du systeme vasculaire du foie. La veine porte ayant une structure sans cycles, il est possible de concevoir des techniques de segmentation orientees topologie garantissant un resultat topologiquement correct. Deux methodes duales de segmentation et une methode de squelettisation ont ete proposees. Une methode de filtrage de squelette, fondee sur la meme approche, a ete etudiee afin d'ameliorer le resultat
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Dale-Jones, Ralph. "Contrast enhancement using grey scale transformation techniques." Thesis, University of Warwick, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387342.
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Ganapathiraman, Subburengan. "QUANTIFICATION OF SURFACE DEFECTS USING PRIMARY HIGHLIGHT IN DIFFUSE ANGLE GRAY SCALE IMAGES." UKnowledge, 2005. http://uknowledge.uky.edu/gradschool_theses/348.
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The thesis presented is an effort to gather all possible information of one particular type of common paint defect the seed defect, from gray scale images of highly specular painted surface. The proposed approach in the thesis utilizes a white light source to illuminate the surface and utilizes a camera to capture its gray scale image at different diffused angles. While attempting to explain the physics of highlight formation in terms of location on the surface of a seed defect, the thesis also extends to utilize this information from gray scale images to accurately predict the parameters of seed defects including the height, size and position in real time. Since the primary highlight in a gray scale image is more defined, contrary to the past researches on diffuse angle images that use both primary / seed highlight and mirror highlight to estimate height of the seed, this thesis formulates a theory of highlight translation and estimates the height of seed based on primary / seed highlight. The other common type of surface defect - crater defect, is also addressed in the thesis.
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Al-Gindy, Ahmed M. N. "Design and analysis of Discrete Cosine Transform-based watermarking algorithms for digital images. Development and evaluation of blind Discrete Cosine Transform-based watermarking algorithms for copyright protection of digital images using handwritten signatures and mobile phone numbers." Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5450.
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This thesis deals with the development and evaluation of blind discrete cosine transform-based watermarking algorithms for copyright protection of digital still images using handwritten signatures and mobile phone numbers. The new algorithms take into account the perceptual capacity of each low frequency coefficients inside the Discrete Cosine Transform (DCT) blocks before embedding the watermark information. They are suitable for grey-scale and colour images. Handwritten signatures are used instead of pseudo random numbers. The watermark is inserted in the green channel of the RGB colour images and the luminance channel of the YCrCb images. Mobile phone numbers are used as watermarks for images captured by mobile phone cameras. The information is embedded multiple-times and a shuffling scheme is applied to ensure that no spatial correlation exists between the original host image and the multiple watermark copies. Multiple embedding will increase the robustness of the watermark against attacks since each watermark will be individually reconstructed and verified before applying an averaging process. The averaging process has managed to reduce the amount of errors of the extracted information. The developed watermarking methods are shown to be robust against JPEG compression, removal attack, additive noise, cropping, scaling, small degrees of rotation, affine, contrast enhancements, low-pass, median filtering and Stirmark attacks. The algorithms have been examined using a library of approximately 40 colour images of size 512 512 with 24 bits per pixel and their grey-scale versions. Several evaluation techniques were used in the experiment with different watermarking strengths and different signature sizes. These include the peak signal to noise ratio, normalized correlation and structural similarity index measurements. The performance of the proposed algorithms has been compared to other algorithms and better invisibility qualities with stronger robustness have been achieved.
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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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Önügören, Onur [Verfasser]. "Assessment of long axis ventricular function in the fetal heart based on 2D grey scale image processing with a tissue tracking algorithm / Onur Önügören." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2011. http://d-nb.info/1025353986/34.
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Prados, Gutiérrez Ricard. "Image blending techniques and their application in underwater mosaicing." Doctoral thesis, Universitat de Girona, 2013. http://hdl.handle.net/10803/111333.
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The fusion of several images of the same scene into a single and larger composite is known as photo-mosaic. Unfortunately, the seams along image boundaries are often noticeable, due to photometrical and geometrical registration inaccuracies. Image blending is the merging step in which those artefacts are minimized. Processing bottlenecks and the lack of medium-specific processing tools have restricted underwater photo-mosaics to small areas despite the hundreds of thousands of square meters that modern surveys can cover. Producing these mosaics is difficult due to the challenging nature of the underwater environment and the image acquisition conditions. This thesis proposes strategies and solutions to tackle the problems of very large underwater optical surveys (Giga-mosaics), presenting contributions in the image preprocessing, enhancing and blending steps, resulting in an improved visual quality in the final photo-mosaicLa unió de diverses imatges d’una mateixa escena en una d’única i més gran és coneguda com a foto-mosaic. Malauradament, els límits de les imatges són habitualment perceptibles, degut a imprecisions en els registres fotomètric i geomètric. La fusió d'imatges és l'etapa del procés d'unió a la qual aquests artefactes són minimitzats. Els colls d'ampolla en el processament i la manca d'eines específiques pel tractament del medi han restringint els foto-mosaics submarins a àrees reduïdes, malgrat que els estudis actuals poden cobrir centenars de milers de m2. . La producció d'aquests mosaics és complexa donada la naturalesa del medi subaquàtic i les condicions d'adquisició de les imatges. Aquesta tesi proposa estratègies i solucions per afrontar el problema de la generació de foto-mosaics submarins de grans dimensions (Giga-mosaics), i presenta contribucions en les etapes de preprocessament, realçat i fusió d’imatges, donant lloc a una qualitat visual millorada del foto-mosaic final
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Albà, Xènia. "Automated cardiac MR image analysis for population imaging." Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/403063.
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La pràctica clínica i la investigació generen grans quantitats de registres mèdics, incloent-hi imatges. No obstant això, molta informació que podria millorar l'assistència sanitària continua sent inaccessible. Es necessiten noves eines per processar dades a gran escala que tinguin en compte la variabilitat en l'anatomia i la fisiopatologia. En aquesta tesi, es presenten nous procediments per al tractament automàtic i eficient de dades mèdiques a gran escala, concretament en la segmentació d'imatges cardíaques de ressonància magnètica (RM). Les principals aportacions d'aquesta tesi permeten la segmentació automàtica (i) de múltiples seqüències de RM sense necessitat d'ajustar cap paràmetre, (ii) de casos altament variables sense un coneixement previ de la patologia involucrada, i (iii) incorporant la detecció automàtica i un control de qualitat sense necessitat de cap intervenció per part de l'usuari. Totes aquestes tècniques s’han avaluat utilitzant múltiples cohorts a gran escala de diferents centres clínics i bases de dades públiques.Clinical practice and research are routinely generating large amounts of medical records, including medical images. However, valuable knowledge that could impact healthcare delivery remains currently frozen in these population cohorts. New tools are therefore necessary to process and exploit such large-scale data, taking into account in particular the unprecedented variability in anatomy and pathophysiology. In this thesis, we present new approaches for the automatic and robust processing of large-scale medical image data, focusing on the challenging segmentation of cardiac magnetic resonance images (MRI) studies. The main contributions of this thesis allow automatic segmentation (i) across multiple MRI sequences without the need for sequence-specific parameter tuning, (ii) across highly variable cases without a priori knowledge of the involved pathology, and (iii) incorporating automatic detection and quality control without the need for any user interaction. All of these techniques are demonstrated over multiple large-scale cohorts from different clinical centers and public databases.
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Pen, Chih-Hsiu, and 賁致修. "The Study of Color to Gray-Scale Image Transform." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/3wpgw5.
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碩士國立中興大學
電機工程學系所
101
Most methods that convert color images to grayscale images use the intensity value directly for the converted grayscale value. When two pixels have different colors but the same intensity values, the conversion causes the original contrast to disappear. In addition, human visual system has a tendency of regarding regions with similar colors or structures as a whole. To solve the aforementioned problem and incorporating the characteristics of the human visual system into the color conversion, this thesis proposes a color-to-grayscale conversion method that considers the influence between image blocks. The method divides an image into several different blocks to calculate an overall grayscale value for each block. Then, it uses the color of a pixel and the probability that a pixel belongs to each block to better differentiate each pixel after grayscale conversion. The first step is to divide an image into two blocks. The grayscale value of each block is calculated by minimizing the energy of the difference between the grayscale value after conversion and the color distance before conversion. The second step further divides each block into two subblocks. Each pixel in a subblock is paired with a representative pixel in another subblock. Two weights for the chrominance values are calculated by minimizing the energy of color distances before and after conversion. In the third step, the grayscale value for each block is calculated by combining the grayscale value calculated in the first step, the weighted chrominance values calculated in the second step, and the difference between the intensity values before and after conversion. Finally, the grayscale value for each block is multiplied by the probability that a pixel belongs to each block to form the final grayscale value. In the experiments, we find that adjusting a parameter in the first step increases the contrasts among different blocks. On the other hand, the probability that a pixel belongs to each block cannot be too small or too large because it makes the influence among block either too weak or too strong. The experimental results show that the method can be adjusted to fit different conversion needs.
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Chan, Cheng Che, and 詹政哲. "Feature Extraction Strategy for Face Detection in Gray Scale Image." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/67649605385861151342.
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碩士國立臺灣科技大學
機械工程系
91
In recent years, the computer technology is fast developing and advancing. The speed of the computer enables the machine vision can be applied in many areas such as face detection and object tracing. There have been many researches in these fields, but most of them are based on color information. In this study, the technology of image processing aims to detect and trace human face with a web cam in grey scale images. Most of the previous face detection researches proposed detection methods using skin-color information to find out possible face-like regions. Then recognize face using shape information. In this paper we will propose feature extraction strategy and define the face-features for face detection in grey scale images. Finally, using the simple and fast face survey to filter out surplus regions. Compared to color image, the information in a grey scale image is less and easilier influenced by the condition of illumination. In order to adapt influence by varied illumination condition, we adjust parameter gains. In this way, the feasibility and the accuracy will not be reduced by poor illumination. The face detection process proposed in this study can detect faces in complex scenes with a fast speed. Our experiments confirm the strength and the reliability of the proposed algorithm. At the end, we discuss the results, and suggestions to future work.
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黃智任. "On the study of gray-scale image segmentation via fuzzy disks." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/78919317925877406755.
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吳育奇. "Gray-scale and color morphological image processing via binary decision diagrams." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/58067306959480891974.
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Jiang, Yao Min, and 江耀民. "A study of face detection in color and gray scale image." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/75944699952213921230.
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碩士清雲科技大學
電機工程系所
96
The problem of human face detection has been studied for many years. Although considerable successes have been achieved, much work remains to be done to devise improved algorithms. The objectives of this research are proposing a novel scheme for quasi-skin region face detection in color image and exploring the face detection reliability of neural network in gray scale image. In color image, a robust algorithm for face detection based on skin color segmentation is proposed. A quasi-skin region that connects the human face, neck, and body is formed while wearing skin color liked clothes. Although we can use additional eye information, but it will be failed when someone wears a sunglass or close eyes. The algorithm analyses the distribution curve of the quasi-skin region to overcome the failure of eye detection. After taking skin color segmentation and morphological operations of dilation and erosion, statistics curve of binary quasi-skin region is constructed and the local minimum is found by voting procedures. Experimental results show the correctness of our algorithm. In gray scale image, some features of face and eyes are used in training neural network to perform the face detection. Eye candidates are decided after edge detection and region growing processes. The face detection results of neural network are discussed and compared with other algorithms.
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Liu, Che-Wei, and 劉哲瑋. "Automatic Fingerprint Identification System Based on Direct Gray-Scale Image Processing." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/71788007314982342476.
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博士淡江大學
電機工程學系博士班
98
Abstract: Fingerprint is the most popular biometric feature that is widely accepted by the public. Fingerprint is also adopted by the court to be the forensic evidence. Even now, a lot of family and company use a fingerprint recognition system as the access control system. Fingerprints possess two characteristics: Uniqueness and Invariance. The age and the damage on the finger didn’t change the pattern of fingerprint. Therefore, fingerprint can be the identity of individual. Fingerprint had been researched for several hundred years. The first systematical classifying method of fingerprint was proposed by Henry in 1888. After Henry’s approach, many researchers dedicated on the systematic processing of fingerprint recognition, every kind of theorems and algorithms were developed to solve several fingerprint issues: fingerprint classification, fingerprint orientation fields, fingerprint feature and minutiae, and fingerprint matching. In this dissertation, we propose a complete automatic fingerprint identification system from the pre-processing: segmentation, normalization, orientation and frequency estimation and singular points extraction. We also propose a new fingerprint classification method, and direct grey scale minutiae detection in fingerprint and the fingerprint matching. We are not only referring some researches in the literature, we also improve the original procedure and propose some new algorithm in the fingerprint processing`. In the fingerprint pre-processing, we bring up the “Less is More” concept to the fingerprint. The significance of this concept is that pattern possess small portion in the fingerprint block would decide the characteristic of fingerprint texture. As an instance, if a finger pressed too hard on the fingerprint acquiring sensor, we will acquire a smudged fingerprint. The width of ridge lines will become too wide even can connect to other ridges. In this situation, the pixels belong to the ridge line take large portion in the fingerprint pattern. If we trace the ridge lines in the fingerprint, we will extract a lot of false minutiae. Hence, we enhance the information that takes less part of fingerprint which is the valley line in this case, and then we can extract the fingerprint features more correct. In the fingerprint classification, we illustrate the concept form data-mining to propose a new fingerprint classifying and indexing method. Our method can co-operate with Henry’s classification or work individually. By the statistical data of fingerprints, over 95 percents of fingerprint contain an upper core. We calculate the frequency around the upper core and classify fingerprints to 37 classes. We design a hierarchical structure for fingerprint indexing form the class that has the largest probability of matching to those classes that have smaller probability. Our method improves the traditional classification that we have to search the entire database while the input fingerprint is incorrectly classified. We arrange those classes in the different indexing level from high probability to low. In our fingerprint indexing verification, we can acquire more than 90% of matching rate in the first three levels. In the fingerprint minutiae extraction, we didn’t use traditional binarizing method to detect the minutiae, but direct extract minutiae on the grey scale image. Because the grey level image contains more information about fingerprint texture and significant amount of information may be lost during the binarization process. The binarization and thinning are time consuming; the thinning process may generate a large number of spurious minutiae. In the absence of an a priori enhancement step, most of the binarization techniques do not provide satisfactory results when applied to low-quality images. We propose two level minutiae extracting process, in the first level; we mark the peak and trough on the fingerprint histogram to indicate the position of ridge lines and valley lines. And we employ the “Less is more” concept that those textures will be enhanced by the pattern that takes fewer portions. In the second level, we link those points to extend the ridge lines and valley lines and then we can extract minutiae form the trace of ridge lines. In the fingerprint matching process, we proposed the polar coordinate system to represent the minutiae of fingerprint and match those minutiae with a pre-alignment process. This matching algorithm is very fast that we can match more than 10000 fingerprint templates within one second. In the same time, we still can keep good accuracy of fingerprint matching. In the last chapter, we discuss some issues about the processing of blurred or fragmental fingerprint and the future works. We also share some experience and the strategy that we design this system.
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Liou, Guan-Yu, and 柳冠宇. "A Study of Color Image Protection Using Reversible Data Hiding Schemes for Gray-Scale Images." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/53145956113001450105.
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碩士國立高雄第一科技大學
資訊管理所
97
Digital data have been widely transmitted and used on the practical lives as the great progress of computer and network technology in recent years. The problem of digital data protection becomes very important and is concerned. Many relevant studies to achieve the solution of this problem have been proposed. In this work, we propose a protection mechanism for color images using reversible data hiding schemes. Two kinds of images are generated for a test color image, one is a high quality color image and the other is a grayscale image. The grayscale image is for free access and the other is limited access, only authorized users can rebuild the color image from the grayscale image. In this study, two kinds of color images, palette and bitmap images are used as the object images for protection, respectively. Therefore, we adapted two different reversible data hiding schemes to achieve the purpose of image protection. In the first scheme of palette image steganography, color palette information is embedded into its corresponding grayscale image. In the second one of true color image steganography, the color information is transformed from RGB into YCbCr space and the Y element is converted into a gray-scale image as a cover image. The Cb and Cr elements are compressed using a JPEG2000 scheme and the compressed results are used as the secret information for embedding into the cover image. Experimental results show that the proposed image protection mechanisms can achieve high quality on both the grayscale cover images and the rebuilt color images with the use of high capacity reversible data hiding schemes. The performance of the proposed method is demonstrated by showing the good qualities of both the cover and the rebuilt images. In addition, the proposed method also outperforms than some existed color image protection methods.
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Kuo, Chun-Hsiang, and 郭俊祥. "Cellular Neural Networks Application to Gray-Scale Image Noise Cancellation Based on Particle Swarm Optimization." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/13401418881628776559.
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碩士國立高雄應用科技大學
電子與資訊工程研究所碩士班
96
Cellular Neural Networks (CNN) are characterized by the parallel computing of simple processing cells locally interconnected. Due to their local connectivity, CNN can be viewed as image processing and can allow operating at a very high speed in real time. Therefore, CNN can be applied to other areas, including signal processing, solving optimization problem, image compression, and VLSI implementation, etc. In this thesis, the technique of image noise cancellation is presented by employing the hybrid CNN and Particle Swarm Optimization (PSO). The main objective is to train the templates of CNN by a corrupted gray-scale image and a corresponding desired image. Then the CNN with given templates is employed to reconstruct the corrupted image. The simulation results will be illustrated that the proposed method is effectiveness for practical applications.
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HUANG, HONG-BEN, and 黃宏本. "A study on representations of gray scale images." Thesis, 1989. http://ndltd.ncl.edu.tw/handle/11441015822184322194.
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Hui, Yu Rong, and 于榮輝. "Adaptive Discrete Cosine Transform Coding of Gray-Scale Images." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/15830412519295635772.
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碩士國立中央大學
資訊及電子工程研究所
82
An adaptive cosine transform coding scheme for gray-scale images based on HVS is proposed in this thesis. Ngan, Leong, and Singh's approach is adopted in this paper. In our block adaptive scheme, a new range scale factor function is proposed to improve the subjective quality of those blocks which contain edges. Besides, we will propose a new adaptive block-effect redunction method to reduce the block effect resulting from block transform coding schemes. This scheme is combined with perceptual distortion minimization and two-dimensional block distortion equalization algorithms. Experimental results show that the subjective quality of the reconstructed images at a bit rate of 0.4 bit/pixel is very appealing.
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ZHAO, WEI-GANG, and 趙維岡. "Mesh Editing Via Vertex Insertion and Displacement Based on Gray Scale Images." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/crgtju.
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碩士大同大學
資訊工程學系(所)
107
There are many ways to change the appearance of a model in many modeling software. Each method requires different conditions or difficulty. In the case of making a triangular mesh into a desired pattern on the surface of the model, it is usually only in a slow way. In this paper, the triangular mesh of the model surface is changed to form a graph, and the process is simple and rapid. The paper discusses the establishment of material coordinates, the search for graphic regions, and the reconstruction of triangular meshes.
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陳欣蓮. "Recognition Techniques for 3D Objects of Specific Geometric Shapes from Gray Scale Images." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/22237368179187930468.
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Wei, Yi-Sin, and 魏逸昕. "Use Nakagami m value to caompare Fundamental Gray-Scale and Second Harmonic Ultrasound Liver Images." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/84505997962045874919.
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Yu, Rui-Wen, and 游瑞文. "A Study of Share Size Invariant Secret Sharing Techniques for Gray-scale and Color Images." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/3g7jnp.
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碩士臺中技術學院
資訊科技與應用研究所
97
Visual secret sharing (VSS) is an efficient way to share a secret image among many participants. In this scheme, the secret image is encrypted into many images which are also called shares. The secret image is revealed by overlapping share images without any complex computation. In recent years, this scheme has been employed to deal with gray-scale and color images for enhancing applications of the sharing way. However, most schemes result in the generated shares with large size expansion to cause the burden of bandwidth and storage space. In order to improve this drawback, this thesis focuses the study on visual secret sharing with share size invariant. First, a scheme based on gray-scale image to provide a high quality VSS scheme with share size invariant is presented in Chapter 3. In this scheme, the pattern histogram and MLB matrices are employed to enhance the quality of the reconstructed secret image. The encrypting way “block by block” is employed to maintain the share size invariant. Experimental results show that the proposed scheme can provide a better quality for the reconstructed secret image by improving the problem of information lost and providing more than two color levels for shares. In Chapter 4, a (k, n)-threshold color visual cryptography (CVC) with meaningful shares is proposed. In this scheme, halftone technique and optimizing color is employed to reduce the color information of a secret color image. Then, the secret is encrypted by the concept of probabilistic VSS for maintaining the share size invariant. In the meantime, the shares are embedded in nature images for reducing the attention of hackers. Experimental results show that the proposed scheme improves the shortcoming of previous color visual cryptography studies in pixel expansion. The secret image is revealed by overlapping sufficient meaningful shares. Moreover, this proposed scheme can be applied to additive and subtractive color models. Finally, a CVC scheme with authentication information is proposed in Chapter 5. In this scheme, the secret color image is processed by pre-processing for reducing the information size. Then, the secret image is encrypted by a probability CVC scheme. At the same time, the authentication information is embedded in each share. Experimental results show that each participant can identify each share owned by other participants. Moreover, the secret color image can be clearly revealed without any computation, and the size of each share is invariable.
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"Investigations on encryption techniques for colored and gray scale images in fourier- and fractional fourier domains." Thesis, 2009. http://localhost:8080/xmlui/handle/12345678/4551.
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