Дисертації з теми "IMAGE SEGMENTATION TECHNIQUES"
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Duramaz, Alper. "Image Segmentation Based On Variational Techniques." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607721/index.pdf.
Повний текст джерелаbut for the hierarchical four-phase segmentation, it is observed that this method sometimes gives unsatisfactory results. In this work, a fast hierarchical four-phase segmentation method is proposed where the Chan-Vese active contour method is applied following the gradient flows method. After the segmentation process, the segmented regions are denoised using diffusion filters. Additionally, for the low signal-to-noise ratio applications, the prefiltering scheme using nonlinear diffusion filters is included in the proposed method. Simulations have shown that the proposed method provides an effective solution to the image segmentation and denoising problem.
Altinoklu, Metin Burak. "Image Segmentation Based On Variational Techniques." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610415/index.pdf.
Повний текст джерела#8211
Shah variational approach have been studied. By obtaining an optimum point of the Mumford-Shah functional which is a piecewise smooth approximate image and a set of edge curves, an image can be decomposed into regions. This piecewise smooth approximate image is smooth inside of regions, but it is allowed to be discontinuous region wise. Unfortunately, because of the irregularity of the Mumford Shah functional, it cannot be directly used for image segmentation. On the other hand, there are several approaches to approximate the Mumford-Shah functional. In the first approach, suggested by Ambrosio-Tortorelli, it is regularized in a special way. The regularized functional (Ambrosio-Tortorelli functional) is supposed to be gamma-convergent to the Mumford-Shah functional. In the second approach, the Mumford-Shah functional is minimized in two steps. In the first minimization step, the edge set is held constant and the resultant functional is minimized. The second minimization step is about updating the edge set by using level set methods. The second approximation to the Mumford-Shah functional is known as the Chan-Vese method. In both approaches, resultant PDE equations (Euler-Lagrange equations of associated functionals) are solved by finite difference methods. In this study, both approaches are implemented in a MATLAB environment. The overall performance of the algorithms has been investigated based on computer simulations over a series of images from simple to complicated.
Storve, Sigurd. "Kalman Smoothing Techniques in Medical Image Segmentation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for elektronikk og telekommunikasjon, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18823.
Повний текст джерелаSeemann, Torsten 1973. "Digital image processing using local segmentation." Monash University, School of Computer Science and Software Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8055.
Повний текст джерелаMatalas, Ioannis. "Segmentation techniques suitable for medical images." Thesis, Imperial College London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339149.
Повний текст джерелаYeo, Si Yong. "Implicit deformable models for biomedical image segmentation." Thesis, Swansea University, 2011. https://cronfa.swan.ac.uk/Record/cronfa42416.
Повний текст джерелаAlazawi, Eman. "Holoscopic 3D image depth estimation and segmentation techniques." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/10517.
Повний текст джерелаShaffrey, Cian William. "Multiscale techniques for image segmentation, classification and retrieval." Thesis, University of Cambridge, 2003. https://www.repository.cam.ac.uk/handle/1810/272033.
Повний текст джерелаSekkal, Rafiq. "Techniques visuelles pour la détection et le suivi d’objets 2D." Thesis, Rennes, INSA, 2014. http://www.theses.fr/2014ISAR0032/document.
Повний текст джерелаNowadays, image processing remains a very important step in different fields of applications. In an indoor environment, for a navigation system related to a mobile robot (electrical wheelchair), visual information detection and tracking is crucial to perform robotic tasks (localization, planning…). In particular, when considering passing door task, it is essential to be able to detect and track automatically all the doors that belong to the environment. Door detection is not an obvious task: the variations related to the door status (open or closed), their appearance (e.g. same color as the walls) and their relative position to the camera have influence on the results. On the other hand, tasks such as the detection of navigable areas or obstacle avoidance may involve a dedicated semantic representation to interpret the content of the scene. Segmentation techniques are then used to extract pseudosemantic regions based on several criteria (color, gradient, texture...). When adding the temporal dimension, the regions are tracked then using spatiotemporal segmentation algorithms. In this thesis, we first present joint door detection and tracking technique in a corridor environment: based on dedicated geometrical features, the proposed solution offers interesting results. Then, we present an original joint hierarchical and multiresolution segmentation framework able to extract a pseudo-semantic region representation. Finally, this technique is extended to video sequences to allow the tracking of regions along image sequences. Based on contour motion extraction, this solution has shown relevant results that can be successfully applied to corridor videos
Celik, Mehmet Kemal. "Digital image segmentation using periodic codings." Thesis, Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/80099.
Повний текст джерелаMaster of Science
López, Mir Fernando. "Advanced techniques in medical image segmentation of the liver." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/59428.
Повний текст джерела[ES] La segmentación de imágenes es, junto al registro multimodal y monomodal, la operación con mayor aplicabilidad en tratamiento digital de imagen médica. Son multitud las operaciones y filtros, así como las aplicaciones y casuística, que derivan de una segmentación de un tejido orgánico. El caso de segmentación del hígado en imágenes radiológicas es, después del cerebro, la que mayor número de publicaciones científicas podemos encontrar. Esto es debido por un lado a la necesidad de seguir innovando en los algoritmos ya existentes y por otro a la gran aplicabilidad que tiene en muchas situaciones relacionadas con el diagnóstico, tratamiento y seguimiento de patologías hepáticas pero también para la planificación clínica de las mismas. En el caso de imágenes de resonancia magnética, sólo en los últimos años han aparecido soluciones que consiguen buenos resultados en cuanto a precisión y robustez en la segmentación del hígado. Sin embargo dichos algoritmos, por lo general son poco utilizables en el ambiente clínico. En el caso de imágenes de tomografía computarizada encontramos mucha más variedad de metodologías y soluciones propuestas pero es difícil encontrar un equilibrio entre precisión y uso práctico clínico. Es por ello que para mejorar el estado del arte en ambos casos (imágenes de resonancia magnética y tomografía computarizada) en esta tesis se ha planteado una metodología común a la hora de diseñar y desarrollar sendos algoritmos de segmentación del hígado en las citadas modalidades de imágenes anatómicas. El segundo paso ha sido la validación de ambos algoritmos. En el caso de imágenes de tomografía computarizada existen bases de datos públicas con imágenes segmentadas manualmente por expertos y que la comunidad científica suele utilizar como nexo común a la hora de validar y posteriormente comparar sus algoritmos. La validación se hace mediante la obtención de determinados coeficientes de similitud entre la imagen segmentada manualmente por los expertos y las que nos proporciona el algoritmo. Esta forma de validar la precisión del algoritmo ha sido la seguida en esta tesis, con la salvedad que en el caso de imágenes de resonancia magnética no existen bases de datos de acceso público. Por ello, y para este caso, lo que se ha hecho es la creación previa de una base de datos propia donde diferentes expertos radiólogos han segmentado manualmente diferentes estudios de pacientes con el fin de que puedan servir como referencia y se pueda seguir la misma metodología que en el caso anterior. Dicha base de datos ha hecho posible que la validación se haga en 17 estudios (con más de 1.500 imágenes), lo que convierte la validación de este método de segmentación del hígado en imágenes de resonancia magnética en una de las más extensas publicadas hasta la fecha. La validación y posterior comparación han dejado patente una precisión superior al 90% reflejado en el coeficiente de Jaccard y Dice, muy en consonancia con valores publicados por la inmensa mayoría de autores que se han podido comparar. Sin embargo, y en general, los algoritmos planteados en esta tesis han obtenido unos criterios de uso mucho mayores, ya que en general presentan menores costes de computación, una interacción clínica casi nula y una iniciación nula en el caso del algoritmo de resonancia magnética y casi nula en el caso de algoritmos de tomografía computarizada. En esta tesis, también se ha abordado un tercer punto que hace uso de los resultados obtenidos en la segmentación del hígado en imágenes de resonancia magnética. Para ello, y haciendo uso de algoritmos de realidad aumentada, se ha diseñado y validado un estudio real inocuo y no invasivo para el clínico y para el paciente donde se ha demostrado que la utilización de esta tecnología reporta mayores beneficios en cuanto a mayor precisión y menor variabilidad frente a su no uso en un caso concreto de ciru
[CAT] La segmentació d'imatges és, al costat del registre multimodal i monomodal, l'operació amb major aplicabilitat en tractament digital d'imatge mèdica. Són multitud les operacions i filtres, així com les aplicacions i casuística, que comencen en la segmentació d'un teixit orgànic. El cas de segmentació del fetge en imatges radiològiques és, després del cervell, la que major nombre de publicacions científiques podem trobar. Això és degut per una banda a la necessitat de seguir innovant en els algoritmes ja existents i per un altre a la gran aplicabilitat que té en moltes situacions relacionades amb el diagnòstic, tractament i seguiment de patologies hepàtiques però també per a la planificació clínica de les mateixes. En el cas d'imatges de ressonància magnètica, només en els últims anys han aparegut solucions que aconsegueixen bons resultats quant a precisió i robustesa en la segmentació del fetge. No obstant això aquests algoritmes, en general són poc utilitzables en l'ambient clínic. En el cas d'imatges de tomografia computeritzada trobem molta més varietat de metodologies i solucions proposades però és difícil trobar un equilibri entre precisió i ús pràctic clínic. És per això que per millorar l'estat de l'art en els dos casos (imatges de ressonància magnètica i tomografia computeritzada) en aquesta tesi s'ha plantejat una metodologia comuna a l'hora de dissenyar i desenvolupar dos algoritmes de segmentació del fetge en les esmentades modalitats d'imatges anatòmiques. El segon pas ha estat la validació de tots dos algoritmes. En el cas d'imatges de tomografia computeritzada hi ha bases de dades públiques amb imatges segmentades manualment per experts i que la comunitat científica sol utilitzar com a nexe comú a l'hora de validar i posteriorment comparar els seus algoritmes. La validació es fa mitjançant l'obtenció de determinats coeficients de similitud entre la imatge segmentada manualment pels experts i les que ens proporciona l'algoritme. Aquesta forma de validar la precisió de l'algoritme ha estat la seguida en aquesta tesi, amb l'excepció que en el cas d'imatges de ressonància magnètica no hi ha bases de dades d'accés públic. Per això, i per a aquest cas, el que s'ha fet és la creació prèvia d'una base de dades pròpia on diferents experts radiòlegs han segmentat manualment diferents estudis de pacients amb la finalitat que puguen servir com a referència i es puga seguir la mateixa metodologia que en el cas anterior. Aquesta base de dades ha fet possible que la validació es faja en 17 estudis (amb més de 1.500 imatges), cosa que converteix la validació d'aquest mètode de segmentació del fetge en imatges de ressonància magnètica en una de les més extenses publicades fins a la data. La validació i posterior comparació han deixat patent una precisió superior al 90 \% reflectit en el coeficient de \ textit {Jaccard} i \ textit {Dice}, molt d'acord amb valors publicats per la immensa majoria d'autors en que s'ha pogut comparar. No obstant això, i en general, els algoritmes plantejats en aquesta tesi han obtingut uns criteris d'ús molt més grans, ja que en general presenten menors costos de computació, una interacció clínica quasi nul·la i una iniciació nul·la en el cas de l'algoritme de ressonància magnètica i quasi nul·la en el cas d'algoritmes de tomografia computeritzada. En aquesta tesi, també s'ha abordat un tercer punt que fa ús dels resultats obtinguts en la segmentació del fetge en imatges de ressonància magnètica. Per a això, i fent ús d'algoritmes de realitat augmentada, s'ha dissenyat i validat un estudi real innocu i no invasiu per al clínic i per al pacient on s'ha demostrat que la utilització d'aquesta tecnologia reporta més beneficis pel que fa a major precisió i menor variabilitat enfront del seu no ús en un cas concret de cirurgia amb laparoscòpia.
López Mir, F. (2015). Advanced techniques in medical image segmentation of the liver [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59428
TESIS
Premiado
Kerwin, Matthew. "Comparison of Traditional Image Segmentation Techniques and Geostatistical Threshold." Thesis, James Cook University, 2006. https://eprints.qut.edu.au/99764/1/kerwin-honours-thesis.pdf.
Повний текст джерелаKarmakar, Gour Chandra 1970. "An integrated fuzzy rule-based image segmentation framework." Monash University, Gippsland School of Computing and Information Technology, 2002. http://arrow.monash.edu.au/hdl/1959.1/8752.
Повний текст джерелаDokladal, Petr. "Grey-scale image segmentation : a topological approach." Marne-la-Vallée, 2000. http://www.theses.fr/2000MARN0065.
Повний текст джерелаLi, Xiaobing. "Automatic image segmentation based on level set approach: application to brain tumor segmentation in MR images." Reims, 2009. http://theses.univ-reims.fr/exl-doc/GED00001120.pdf.
Повний текст джерелаThe aim of this dissertation is to develop an automatic segmentation of brain tumors from MRI volume based on the technique of "level sets". The term "automatic" uses the fact that the normal brain is symmetrical and the localization of asymmetrical regions permits to estimate the initial contour of the tumor. The first step is preprocessing, which is to correct the intensity inhomogeneity of volume MRI and spatially realign the MRI volumes of the same patient at different moments. The plan hemispherical brain is then calculated by maximizing the degree of similarity between the half of the volume and his reflexion. The initial contour of the tumor can be extracted from the asymmetry between the two hemispheres. This initial contour is evolved and refined by the technique "level set" in order to find the real contour of the tumor. The criteria for stopping the evolution have been proposed and based on the properties of the tumor. Finally, the contour of the tumor is projected onto the adjacent images to form the new initial contours. This process is iterated on all slices to obtain the segmentation of the tumor in 3D. The proposed system is used to follow up patients throughout the medical treatment period, with examinations every four months, allowing the physician to monitor the state of development of the tumor and evaluate the effectiveness of the therapy. The method was quantitatively evaluated by comparison with manual tracings experts. Good results are obtained on real MRI images
Abdulhadi, Abdulwanis Abdalla. "Evaluation of spot welding electrodes using digital image processing and image segmentation techniques." Thesis, Liverpool John Moores University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.589998.
Повний текст джерелаPan, Jianjia. "Image segmentation based on the statistical and contour information." HKBU Institutional Repository, 2008. http://repository.hkbu.edu.hk/etd_ra/1004.
Повний текст джерелаGomes, Vicente S. A. "Global optimisation techniques for image segmentation with higher order models." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1334450/.
Повний текст джерелаSu, Qi, and 蘇琦. "Segmentation and reconstruction of medical images." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41897067.
Повний текст джерелаMasek, Martin. "Hierarchical segmentation of mammograms based on pixel intensity." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2003.0033.
Повний текст джерелаRousson, Mikaël. "Cue integration and front evolution in image segmentation." Nice, 2004. http://www.theses.fr/2004NICE4100.
Повний текст джерелаAutomatic detection and selection of regions of interest is a key step in image understanding. In the literature, most segmentation approaches are restricted to a particular class of images. This limitation is due to the large variety of cues available to characterize a region of interest. Targeting particular applications, algorithms are centered on the from most relevant cue. The limiting factor to obtain a general algorithm is the large variety of cues available to characterize a region of interest. It can be gray-level, color, texture, shape, etc. . . In this thesis, we propose a general formulation able to deal with each one of these characteristics. Image intensity, color, texture, motion and prior shape knowledge are considered. For this purpose, a probabilistic inference is obtained from a Bayesian formulation of the segmentation problem. Then, reformulated as an energy minimization, the most probable image partition is obtained using front evolution techniques. Level-set functions are naturally introduced to represent the evolving fronts while region statistics are optimized in parallel. This framework can naturally handle scalar and vector-valued smooth images but more complex cues are also integrated. Texture and motion features, as well as prior shape knowledge are successively introduced. Complex medical images are considered in the last part with the case of diffusion magnetic resonance images which gives 3D probability density fields
Liu, Sam J. "Low bit-rate image and video compression using adaptive segmentation and quantization." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/14850.
Повний текст джерелаHuang, Guo Heng. "On-line video object segmentation using superpixel approach." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691897.
Повний текст джерелаChen, Zhuo, and 陳卓. "A split-and-merge approach for quadrilateral-based image segmentation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B38749440.
Повний текст джерелаTan, Zhigang, and 譚志剛. "A region merging methodology for color and texture image segmentation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43224143.
Повний текст джерелаStein, Andrew Neil. "Adaptive image segmentation and tracking : a Bayesian approach." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/13397.
Повний текст джерелаVergés, Llahí Jaume. "Color Constancy and Image Segmentation Techniques for Applications to Mobile Robotics." Doctoral thesis, Universitat Politècnica de Catalunya, 2005. http://hdl.handle.net/10803/6189.
Повний текст джерелаPer dur a terme aquests objectius, primerament s'estableix matemàticament la transformació entre colors degut a variacions d'il·luminació. Així es proposa un model continu per la generació del senyal de color com a generalització natural d'altres propostes anteriors. D'aquesta manera es pot estudiar matemàticament i amb generalitat les condicions per l'existència, unicitat i bon comportament de les solucions, i expressar qualsevol tipus d'aplicació entre colors, independentment del tipus de discretització. Així, queda palès la relació íntima entre el problema de la invariància de color i el de la recuperació espectral, que també es planteja a la pràctica. El model desenvolupat es contrasta numèricament amb els de regressió lineal, en termes d'errors de predicció.
Un cop establert el model general, s'opta per un model lineal simplificat a l'hora de realitzar els càlculs pràctics i permet alleugerir el nombre dels mateixos. En particular, el mètode proposat es basa en trobar la transformació més probable entre dues imatges a partir del càlcul d'un conjunt de transformacions possibles i de l'estimació de la freqüència i grau d'efectivitat de cadascuna d'elles. Posteriorment, es selecciona el millor candidat d'acord amb la seva versemblança. L'aplicació resultant serveix per transformar els colors de la imatge tal i com es veuria sota les condicions d'il·luminació canòniques.
Una vegada el color de les imatges d'una mateixa escena es manté constant, cal procedir a la seva segmentació per extreure'n la informació corresponent a les regions amb color homogeni. En aquesta Tesi es suggereix un algorisme basat en la partició de l'arbre d'expansió mínima d'una imatge mitjançant una mesura local de la probabilitat de les unions entre components. La idea és arribar a una segmentació coherent amb les regions reals, compromís entre particions amb moltes components (sobresegmentades) i amb molt poques (subsegmentades).
Un altre objectiu és que l'algorisme sigui prou ràpid com per ser útil en aplicacions de robòtica mòbil. Aquesta característica s'assoleix amb un plantejament local del creixement de regions, tot i que el resultat presenti caràcters globals (color). La possible sobresegmentació es suavitza gràcies al factor probabilístic introduït.
L'algorisme de segmentació també hauria de generar segmentacions estables en el temps. Així, l'algorisme referit s'ha ampliat incloent-hi un pas intermedi entre segmentacions que permet de relacionar regions semblants en imatges diferents i propagar cap endavant els reagrupaments de regions fets en anteriors imatges, així si en una imatge unes regions s'agrupen formant-ne una de sola, les regions corresponents en la imatge següent també s'han d'agrupar juntes. D'aquesta manera, dues segmentacions correlatives s'assemblen i es pot mantenir estable la segmentació d'una seqüència.
Finalment, es planteja el problema de comparar imatges a partir del seu contingut. Aquesta Tesi es concentra només en la informació de color i, a més de investigar la millor distància entre segmentacions, es busca també mostrar com la invariància de color afecta les segmentacions.
Els resultats obtinguts per cada objectiu proposat en aquesta Tesi avalen els punts de vista defensats, i mostren la utilitat dels algorismes, així com el model de color tant per la recuperació espectral com pel càlcul explícit de les transformacions entre colors.
This Thesis endeavors providing a set of techniques for facing the problem of color variation in images taken from a mobile platform and caused by the change in the conditions of lighting among several views of a certain scene taken at different instants and positions. It also treats the problem of segmenting color images in order to use them in tasks associated with the capacities of a mobile robot, such as object identification or image retrieval from a large database.
In order to carry out these goals, first transformation among colors due to light variations is mathematically established. Thus, a continuous model for the generation of color is proposed as a natural generalization of other former models. In this way, conditions for the existence, uniqueness, and good behavior of the solutions can be mathematically studied with a great generality, and any type of applications among colors can be expressed independently of the discretization scheme applied. Thus, the intimate relation among the problem of color invariance and that of spectral recovery is made evident and studied in practice too. The developed model is numerically contrasted with those of a least squares linear regression in terms of prediction errors.
Once the general model is established, a simplified linear version is chosen instead for carrying out the practical calculations while lightening the number of them. In particular, the proposed method is based on finding the likeliest transformation between two images from the calculation of a set of feasible transformations and the estimation of the frequency and the effectiveness degree of each of them. Later, the best candidate is selected in accordance with its likelihood. The resulting application is then able to transform the image colors as they would be seen under the canonical light.
After keeping the image colors from a scene constant, it is necessary to proceed to their segmentation to extract information corresponding to regions with homogeneous colors. In this Thesis, an algorithm based on the partition of the minimum spanning tree of an image through a local measure of the likelihood of the unions among components is suggested. The idea is to arrive at a segmentation coherent with the real regions, a trade-off between partitions with many component (oversegmented) and those with fewer components (subsegmented).
Another goal is that of obtaining an algorithm fast enough to be useful in applications of mobile robotics. This characteristic is attained by a local approach to region growing, even though the result still shows global feature (color). The possible oversegmentation is softened thanks to a probabilistic factor.
The segmentation algorithm should also generate stable segmentations through time. Thus, the aforementioned algorithm has been widened by including an intermediate step that allows to relate similar regions in different images and to propagate forwards the regrouping of regions made in previous images. This way, if in some image some regions are grouped forming only one bigger region, the corresponding regions in the following image will also be grouped together. In this way, two correlatives segmentations resemble each other, keeping the whole segmented sequence stabler.
Finally, the problem of comparing images via their content is also studied in this Thesis, focusing on the color information and, besides investigating which is for our aims the best distance between segmentation, also showing how color constancy affects segmentations. The results obtained in each of the goals proposed in this Thesis guarantee the exposed points of view, and show the utility of the algorithms suggested, as well as the color model for the spectral recovery and the explicit calculation of the transformations among colors.
Awadallah, Mahmoud Sobhy Tawfeek. "Image Analysis Techniques for LiDAR Point Cloud Segmentation and Surface Estimation." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/73055.
Повний текст джерелаPh. D.
Lin, Xiangbo. "Knowledge-based image segmentation using deformable registration: application to brain MRI images." Reims, 2009. http://theses.univ-reims.fr/exl-doc/GED00001121.pdf.
Повний текст джерелаThe research goal of this thesis is a contribution to the intra-modality inter-subject non-rigid medical image registration and the segmentation of 3D brain MRI images in normal case. The well-known Demons non-rigid algorithm is studied, where the image intensities are used as matching features. A new force computation equation is proposed to solve the mismatch problem in some regions. The efficiency is shown through numerous evaluations on simulated and real data. For intensity based inter-subject registration, normalizing the image intensities is important for satisfying the intensity correspondence requirements. A non-rigid registration method combining both intensity and spatial normalizations is proposed. Topology constraints are introduced in the deformable model to preserve an expected property in homeomorphic targets registration. The solution comes from the correction of displacement points with negative Jacobian determinants. Based on the registration, a segmentation method of the internal brain structures is studied. The basic principle is represented by ontology of prior shape knowledge of target internal structure. The shapes are represented by a unified distance map computed from the atlas and the deformed atlas, and then integrated into the similarity metric of the cost function. A balance parameter is used to adjust the contributions of the intensity and shape measures. The influence of different parameters of the method and comparisons with other registration methods were performed. Very good results are obtained on the segmentation of different internal structures of the brain such as central nuclei and hippocampus
Gundersen, Henrik Mogens, and Bjørn Fossan Rasmussen. "An Application of Image Processing Techniques for Enhancement and Segmentation of Bruises in Hyperspectral Images." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9594.
Повний текст джерелаHyperspectral images contain vast amounts of data which can provide crucial information to applications within a variety of scientific fields. Increasingly powerful computer hardware has made it possible to efficiently treat and process hyperspectral images. This thesis is interdisciplinary and focuses on applying known image processing algorithms to a new problem domain, involving bruises on human skin in hyperspectral images. Currently, no research regarding image detection of bruises on human skin have been uncovered. However, several articles have been written on hyperspectral bruise detection on fruits and vegetables. Ratio, difference and principal component analysis (PCA) were commonly applied enhancement algorithms within this field. The three algorithms, in addition to K-means clustering and the watershed segmentation algorithm, have been implemented and tested through a batch application developed in C# and MATLAB. The thesis seeks to determine if the enhancement algorithms can be applied to improve bruise visibility in hyperspectral images for visual inspection. In addition, it also seeks to answer if the enhancements provide a better segmentation basis. Known spectral characteristics form the experimentation basis in addition to identification through visual inspection. To this end, a series of experiments were conducted. The tested algorithms provided a better description of the bruises, the extent of the bruising, and the severity of damage. However, the algorithms tested are not considered robust for consistency of results. It is therefore recommended that the image acquisition setup is standardised for all future hyperspectral images. A larger, more varied data set would increase the statistical power of the results, and improve test conclusion validity. Results indicate that the ratio, difference, and principal component analysis (PCA) algorithms can enhance bruise visibility for visual analysis. However, images that contained weakly visible bruises did not show significant improvements in bruise visibility. Non-visible bruises were not made visible using the enhancement algorithms. Results from the enhancement algorithms were segmented and compared to segmentations of the original reflectance images. The enhancement algorithms provided results that gave more accurate bruise regions using K-means clustering and the watershed segmentation. Both segmentation algorithms gave the overall best results using principal components as input. Watershed provided less accurate segmentations of the input from the difference and ratio algorithms.
Gopalan, Sowmya. "Estimating Columnar Grain Size in Steel-Weld Images using Image Processing Techniques." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250621610.
Повний текст джерелаMartin, Vincent. "Cognitive vision : supervised learning for image and video segmentation." Nice, 2007. http://www.theses.fr/2007NICE4067.
Повний текст джерелаIn this thesis, we address the problem of image and video segmentation with a cognitive vision approach. More precisely, we study two major issues of the segmentation task in vision systems: the selection of an algorithm and the tuning of its free parameters according to the image contents and the application needs. We propose a learning-based methodology to easily set up the algorithms and continuously adapt the segmentation task. Our first contribution is a generic optimization procedure to automatically extract optimal algorithm parameters. The evaluation of the segmentation quality is done w. R. T. Reference segmentation. In this way, the user task is reduced to provide reference data of training images, as manual segmentations. A second contribution is a twofold strategy for the algorithm selection issue. This strategy relies on a training image set representative of the problem. The first part uses the results of the optimization stage to perform a global ranking of algorithm performance values. The second part consists in identifying different situations from the training image set and then to associate a tuned segmentation algorithm with each situation. A third contribution is a semantic approach to image segmentation. In this approach, we combine the result from the previously (bootom-up) optimized segmentations to a region labelling process. Regions labels are given by region classifiers which are trained from annotated samples. A fourth contribution is the implementation of the approach and the development of a graphical tool currently able to carry out the learning of segmentation knowledge (context modelling and learning, automatic parameter optimization, region annotations, region classifier training, and algorithm selection) and to use this knowledge to perform adaptive segmentation. We have tested our approach on two real-world applications: a biological application (pests counting on rose leaves), and video surveillance applications. For the first one, the proposed adaptive segmentation approach over performs a non-adaptive segmentation in terms of segmentation quality and thus allows the vision system to count the pests with a better precision. For the video application, the main contribution of the proposed approach takes place at the context modelling level. By achieving dynamic background model selection based on spatio-temporal context analysis, our approach allows to enlarge the scope of surveillance applications to high variable environments (e. G. , outdoor sequences of several hours)
Gover, Tobin. "Low bit rate imaging coding based on segmentation and vector techniques." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309221.
Повний текст джерелаBatista, Neto Joao Do Espirito Santo. "Techniques for computer-based anatomical segmentation of the brain using MRI." Thesis, Imperial College London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244197.
Повний текст джерелаKang, Jung Won. "Effective temporal video segmentation and content-based audio-visual video clustering." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/13731.
Повний текст джерелаTran, Minh Tue. "Pixel and patch based texture synthesis using image segmentation." University of Western Australia. School of Computer Science and Software Engineering, 2010. http://theses.library.uwa.edu.au/adt-WU2010.0030.
Повний текст джерелаJayasuriya, Surani Anuradha. "Application of Symmetry Information in Magnetic Resonance Brain Image Segmentation." Thesis, Griffith University, 2013. http://hdl.handle.net/10072/366576.
Повний текст джерелаThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information and Communication Technology
Science, Environment, Engineering and Technology
Full Text
Surma, David Ray 1963. "Design and performance evaluation of parallel architectures for image segmentation processing." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277042.
Повний текст джерелаSandhu, Romeil Singh. "Statistical methods for 2D image segmentation and 3D pose estimation." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37245.
Повний текст джерелаKouzana, Amira. "Conception d'un cadre d'optimisation de fonctions d'énergies : application au traitement d'images." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1121/document.
Повний текст джерелаWe propose a new formulation of the energy minimisation paradigm for image segmentation. The segmentation problem is modeled as a non-cooperative strategic game, and the optimization process is interpreted as the search of a Nash equilibrium. The problem is expressed as a combinatorial problem, for which an efficient Branch and Bound algorithm is proposed to solve the problem exactly. To illustrate the performance of the proposed framework, it is applied on convex regularization model, as well as a non-convex regularized segmentation models
Gao, Yi. "Geometric statistically based methods for the segmentation and registration of medical imagery." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/39644.
Повний текст джерелаJamrozik, Michele Lynn. "Spatio-temporal segmentation in the compressed domain." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/15681.
Повний текст джерелаDeveau, Matthieu. "Utilisation conjointe de données image et laser pour la segmentation et la modélisation 3D." Paris 5, 2006. http://www.theses.fr/2006PA05S001.
Повний текст джерелаThis thesis deals with combining a digital image with laser data for complex scenes 3D modeling automation. Image and laser data are acquired from the same point of view, with a greater image resolution than the laser one. This work is structured around three main topics pose estimation, segmentation and modeling. Pose estimation is based both on feature points matching, between the digital image and the laser intensity image, and on linear feature extraction. Data segmentation into geometric features is done through a hierarchical segmentation scheme, where image and laser data are combined. 3D modeling automation is studied through this hierarchical scheme. A tool for semi-automated modeling is also derived from the hierarchical segmentation architecture. In the modeling step, we have focused on automatic modeling of cylinders with free-form profiles. The description is then very general, with planes, freeform profile cylinders, revolution objects, and meshes on complex parts
Noyel, Guillaume. "Filtrage, réduction de dimension, classification et segmentation morphologique hyperspectrale." Phd thesis, École Nationale Supérieure des Mines de Paris, 2008. http://pastel.archives-ouvertes.fr/pastel-00004473.
Повний текст джерелаWang, Xiaofang. "Graph based approaches for image segmentation and object tracking." Thesis, Ecully, Ecole centrale de Lyon, 2015. http://www.theses.fr/2015ECDL0007/document.
Повний текст джерелаImage segmentation is a fundamental problem in computer vision. In particular, unsupervised image segmentation is an important component in many high-level algorithms and practical vision systems. In this dissertation, we propose three methods that approach image segmentation from different angles of graph based methods and are proved powerful to address these problems. Our first method develops an original graph construction method. We also analyze different types of graph construction method as well as the influence of various feature descriptors. The proposed graph, called a local/global graph, encodes adaptively the local and global image structure information. In addition, we realize global grouping using a sparse representation of superpixels’ features over the dictionary of all features by solving a l0-minimization problem. Extensive experiments are conducted on the Berkeley Segmentation Database, and the proposed method is compared with classical benchmark algorithms. The results demonstrate that our method can generate visually meaningful partitions, but also that very competitive quantitative results are achieved compared with state-of-the-art algorithms. Our second method derives a discriminative affinity graph that plays an essential role in graph-based image segmentation. A new feature descriptor, called weighted color patch, is developed to compute the weight of edges in an affinity graph. This new feature is able to incorporate both color and neighborhood information by representing pixels with color patches. Furthermore, we assign both local and global weights adaptively for each pixel in a patch in order to alleviate the over-smooth effect of using patches. The extensive experiments show that our method is competitive compared to the other standard methods with multiple evaluation metrics. The third approach combines superpixels, sparse representation, and a new midlevel feature to describe superpixels. The new mid-level feature not only carries the same information as the initial low-level features, but also carries additional contextual cue. We validate the proposed mid-level feature framework on the MSRC dataset, and the segmented results show improvements from both qualitative and quantitative viewpoints compared with other state-of-the-art methods. Multi-target tracking is an intensively studied area of research and is valuable for a large amount of applications, e.g. video surveillance of pedestrians or vehicles motions for sake of security, or identification of the motion pattern of animals or biological/synthetic particles to infer information about the underlying mechanisms. We propose a detect-then-track framework to track massive colloids’ motion paths in active suspension system. First, a region based level set method is adopted to segment all colloids from long-term videos subject to intensity inhomogeneity. Moreover, the circular Hough transform further refines the segmentation to obtain colloid individually. Second, we propose to recover all colloids’ trajectories simultaneously, which is a global optimal problem that can be solved efficiently with optimal algorithms based on min-cost/max flow. We evaluate the proposed framework on a real benchmark with annotations on 9 different videos. Extensive experiments show that the proposed framework outperforms standard methods with large margin
Besbes, Ahmed. "Image segmentation using MRFs and statistical shape modeling." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00594246.
Повний текст джерелаKolesov, Ivan A. "Statistical methods for coupling expert knowledge and automatic image segmentation and registration." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/47739.
Повний текст джерелаYang, Yan. "Image Segmentation and Shape Analysis of Blood Vessels with Applications to Coronary Atherosclerosis." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14577.
Повний текст джерелаPiovano, Jérôme. "Image segmentation and level set method : application to anatomical head model creation." Nice, 2009. http://www.theses.fr/2009NICE4062.
Повний текст джерелаMagnetic Resonance Images (MRI) have been introduced at the end of the XXth century and have revolutionized the world of modern medicine, allowing to view with precision the inside of anatomical structures in a non-invasive way. This imaging technique has greatly contributed to the study and comprehension of the human brain, allowing to discern with precision the different anatomical structures composing the head, especially the cerebral cortex. Discernment between these anatomical structures is called segmentation, and consist in “extracting” structures of interest from MRIs. Several models exists to perform image segmentation, and this thesis focus on those based on hypersurface evolutions: an hypersurface (surface in 3D) is incrementally adjusted to finally fit the border of the region of interest. A head model corresponds to the partitioning of the head into several segmented anatomical structures. A classic head model generally includes 5 anatomical structures (skin, skull, cerebrospinal fluid, grey matter, white matter), nested inside each other in the manner of “Russian nested dolls”. Nevertheless because of the complexity of their shapes, manual segmentation of these structures is tedious and extremely difficult. This thesis is dedicated to the creation of new segmentation models robust to MRI alterations, and to the application of these models in the purpose of automatic creation of anatomical head models. After briefly reviewing some classical models in image segmentation, two contributions to segmentation based on hypersurface evolution are proposed. The first one corresponds to a new representation and a new numerical scheme for the level-sets method, based on quadrilateral finite elements. This representation aims at improving the accuracy and robustness of the model. The second contribution corresponds to a new segmentation model based on local statistics, and robust to standard MRI alterations. This model aims at unifying several 'state-of-the-art' models in image segmentation. Finally, a framework for automatic creation of anatomical head models is proposed, mainly using the previous local-statistic based segmentation model
Liu, Siwei. "Apport d'un algorithme de segmentation ultra-rapide et non supervisé pour la conception de techniques de segmentation d'images bruitées." Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM4371.
Повний текст джерелаImage segmentation is an important step in many image processing systems and many problems remain unsolved. It has recently been shown that when the image is composed of two homogeneous regions, polygonal active contour techniques based on the minimization of a criterion derived from information theory allow achieving an ultra-fast algorithm which requires neither parameter to tune in the optimized criterion, nor a priori knowledge on the gray level fluctuations. This algorithm can then be used as a fast and unsupervised processing module. The objective of this thesis is therefore to show how this ultra-fast and unsupervised algorithm can be used as a module in the conception of more complex segmentation techniques, allowing to overcome several limits and particularly:- to be robust to the presence of strong inhomogeneity in the image which is often inherent in the acquisition process, such as non-uniform illumination, attenuation, etc.;- to be able to segment disconnected objects by polygonal active contour without complicating the optimization strategy;- to segment multi-region images while estimating in an unsupervised way the number of homogeneous regions in the image.For each of these three problems, unsupervised segmentation techniques based on the optimization of Minimum Description Length criteria have been obtained, which do not require the tuning of parameter by user or a priori information on the kind of noise in the image. Moreover, it has been shown that fast segmentation techniques can be achieved using this segmentation module, while keeping reduced implementation complexity