Cette thèse explore l’utilisation de représentations hiérarchiques des images issues de la morphologie mathématique, les arbres des coupes, pour la recherche et la classification d’images. Différents types de structures arborescentes sont analysés et une nouvelle classification en deux superclasses est proposée, ainsi qu’une contribution à l’indexation et à la représentation de ces structures par des dendogrammes. Deux contributions à la recherche d’images sont proposées, l’une sur la détection de régions d’intérêt et l’autre sur la description de ces régions. Les régions MSER peuvent être détectées par un algorithme s’appuyant sur une représentation des images par arbres min et max. L’utilisation d’autres structures arborescentes sous-jacentes permet de détecter des régions présentant des propriétés de stabilité différentes. Un nouveau détecteur, basé sur les arbres des formes, est proposé et évalué en recherche d’images. Pour la description des régions, le concept de spectres de formes 2D permettant de décrire globalement une image est étendu afin de proposer un descripteur local, au pouvoir discriminant plus puissant. Ce nouveau descripteur présente de bonnes propriétés à la fois de compacité et d’invariance à la rotation et à la translation. Une attention particulière a été portée à la préservation de l’invariance à l’échelle. Le descripteur est évalué à la fois en classification d’images et en recherche d’images satellitaires. Enfin, une technique de simplification des arbres de coupes est présentée, qui permet à l’utilisateur de réévaluer les mesures du niveau d’agrégation des régions imposé par les arbres des coupes. / This thesis explores component trees, hierarchical structures from Mathematical Morphology, and their application to image retrieval and related tasks. The distinct component trees are analyzed and a novel classification into two superclasses is proposed, as well as a contribution to indexing and representation of the hierarchies using dendrograms. The first contribution to the field of image retrieval is in developing a novel feature detector, built upon the well-established MSER detection. The tree-based implementation of the MSER detector allows for changing the underlying tree in order to produce features of different stability properties. This resulted in the Tree of Shapes based Maximally Stable Region detector, leading to improvements over MSER in retrieval performance. Focusing on feature description, we extend the concept of 2D pattern spectra and adapt their global variant to more powerful, local schemes. Computed on the components of Min/Max-tree, they are histograms holding the information on distribution of image region attributes. The rotation and translation invariance is preserved from the global descriptor, while special attention is given to achieving scale invariance. We report comparable results to SIFT in image classification, as well as outperforming Morphology-based descriptors in satellite image retrieval, with a descriptor shorter than SIFT. Finally, a preprocessing or simplification technique for component trees is also presented, allowing the user to reevaluate the measures of region level of aggregation imposed on a component tree. The thesis is concluded by outlining the future perspectives based on the content of the thesis.

Orientador: Peter Sussner / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-07T23:05:00Z (GMT). No. of bitstreams: 1 Mesquita_MarcosEduardoRibeirodoValle_D.pdf: 1277085 bytes, checksum: 70e93671eb62f360b430f7b81b3c71e3 (MD5) Previous issue date: 2007 / Resumo: Uma Memória Associativa (AM, Associative Memory) é um modelo projetado para armazenar pares de entrada e saída. Sobretudo, uma AM deve ser capaz de recordar uma sida desejada ao mesmo após a apresentação de uma versão incompleta ou destorcida de um padrão de entrada. Essa tese de doutorado discute as Memórias Associativas Morfológicas Nebulosas (FMAMs, Fuzzi Morphological Associative Memories), uma classe de memórias associativas elaboradas para armazenar padrões nebulosas cujos neurÔnios realizam operações elementares da morfologia matemática, i.e., dilatação, erosão, anti-dilatação e anti-erosão. É verificado que os principais modelos de Memória Associativa Nebulosa (FAM, Fuzzy Associative Memory) pertencem à classe das FMAMs. Essa tese introduz as Memórias Associativas Nebulosas Implicativas (IFAMs, Implicative Fuzzy Associative Memories) e suas versões duas com respeito à negação e adjunção. Uma IFAM é uma FMAM onde os pares de entrada e saída são armazenados usando o armazenamento nebuloso implicativo. No armazenamento nebuloso implicativo, os pesos sinápticos. Resultados sobre a fase de armazenamento faz IFAMs e das IFAMs duas são apresentados. Em particular, são demonstrados teoremas sobre a convergência, capacidade de armazenamento, tolerância à ruído e pontos fixos das IFAMs e das IFAMs duais para o caso autoassoplos e resultados teóricos. Finalmente, são apresentadas duas aplicações das FMAMs em problemas de previsão de séries temporais. O primeiro problema trata da previsão da mão-de-obra requerida em industrias metalúrgicas enquanto que a segunda aplicação refere-se a previsão da vazão média mensal da usina hidrelétrica de Furnas / Abstract: Associative memories (AMs) are models that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. This thesis discusses fuzzy morphological associative memories (FMAMs), a general class of AMs designed to store fuzzy patterns and described by fuzzy neural networks. Each neuron of a FMAM model performs an elementary operation of mathematical morphology such as dilation, erosion, anti-dilation, and anti-erosion. We show that the most widely known models of fuzzy associative memories (FAMs) belong to the FMAM class. This thesis introduces the implicative fuzzy associative memories (IFAMs) and their dual versions with respect to negation and adjunction. An IFAM is a FMAM model where the patterns are stored by means of implicative fuzzy learning. Specifically, in implicative fuzzy learning, the synaptic weights are given by the minimum of the implication of pre- and postsynaptic activations. We present results concerning the recall and storing phase of IFAM and the dual IFAM models. In particular, we present theorems concerning the convergence, the storage capacity, the noise tolerance, and the fixed points of the IFAM and dual IFAM models in the auto-associative case. We compare the IFAMs with several others FAM models by means of theoretical results and examples. Finally, we present two applications of FMAM models in problems of time-series prediction. The first problem concerns the engineering manpower requirement in steel manufacturing industry while the second refers to the stream flow prediction of a large hydroelectric plant, namely Furnas / Doutorado / Doutor em Matemática Aplicada

Orientador: Peter Sussner / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-26T15:06:30Z (GMT). No. of bitstreams: 1 Bueno_FelipeRoberto_M.pdf: 1499339 bytes, checksum: 85b58d8b856fafa47974349e80c1729e (MD5) Previous issue date: 2015 / Resumo: Perceptrons morfológicos (MPs) pertencem à classe de redes neurais morfológicas (MNNs). Estas redes representam uma classe de redes neurais artificiais que executam operações de morfologia matemática (MM) em cada nó, possivelmente seguido pela aplicação de uma função de ativação. Vale ressaltar que a morfologia matemática foi concebida como uma teoria para processamento e análise de objetos (imagens ou sinais), por meio de outros objetos chamados elementos estruturantes. Embora inicialmente desenvolvida para o processamento de imagens binárias e posteriormente estendida para o processamento de imagens em tons de cinza, a morfologia matemática pode ser conduzida de modo mais geral em uma estrutura de reticulados completos. Originalmente, as redes neurais morfológicas empregavam somente determinadas operações da morfologia matemática em tons de cinza, denominadas de erosão e dilatação em tons de cinza, segundo a abordagem umbra. Estas operações podem ser expressas em termos de produtos máximo aditivo e mínimo aditivo, definidos por meio de operações entre vetores ou matrizes, da álgebra minimax. Recentemente, as operações da morfologia matemática fuzzy surgiram como funções de agregação das redes neurais morfológicas. Neste caso, falamos em redes neurais morfológicas fuzzy. Perceptrons híbridos lineares/morfológicos fuzzy foram inicialmente projetados como uma generalização dos perceptrons lineares/morfológicos existentes, ou seja, os perceptrons lineares/morfológicos fuzzy podem ser definidos por uma combinação convexa de uma parte morfológica fuzzy e uma parte linear. Nesta dissertação de mestrado, introduzimos uma rede neural artificial alimentada adiante, representando um perceptron híbrido linear/morfológico fuzzy chamado F-DELP (do inglês fuzzy dilation/erosion/linear perceptron), que ainda não foi considerado na literatura de redes neurais. Seguindo as ideias de Pessoa e Maragos, aplicamos uma suavização adequada para superar a não-diferenciabilidade dos operadores de dilatação e erosão fuzzy utilizados no modelo F-DELP. Em seguida, o treinamento é realizado por intermédio de um algoritmo de retropropagação de erro tradicional. Desta forma, aplicamos o modelo F-DELP em alguns problemas de classificação conhecidos e comparamos seus resultados com os produzidos por outros classificadores / Abstract: Morphological perceptrons (MPs) belong to the class of morphological neural networks (MNNs). These MNNs represent a class of artificial neural networks that perform operations of mathematical morphology (MM) at every node, possibly followed by the application of an activation function. Recall that mathematical morphology was conceived as a theory for processing and analyzing objects (images or signals), by means of other objects called structuring elements. Although initially developed for binary image processing and later extended to gray-scale image processing, mathematical morphology can be conducted very generally in a complete lattice setting. Originally, morphological neural networks only employed certain operations of gray-scale mathematical morphology, namely gray-scale erosion and dilation according to the umbra approach. These operations can be expressed in terms of (additive maximum and additive minimum) matrix-vector products in minimax algebra. It was not until recently that operations of fuzzy mathematical morphology emerged as aggregation functions of morphological neural networks. In this case, we speak of fuzzy morphological neural networks. Hybrid fuzzy morphological/linear perceptrons was initially designed by generalizing existing morphological/linear perceptrons, in other words, fuzzy morphological/linear perceptrons can be defined by a convex combination of a fuzzy morphological part and a linear part. In this master's thesis, we introduce a feedforward artificial neural network representing a hybrid fuzzy morphological/linear perceptron called fuzzy dilation/erosion/linear perceptron (F-DELP), which has not yet been considered in the literature. Following Pessoa's and Maragos' ideas, we apply an appropriate smoothing to overcome the non-differentiability of the fuzzy dilation and erosion operators employed in the proposed F-DELP models. Then, training is achieved using a traditional backpropagation algorithm. Finally, we apply the F-DELP model to some well-known classification problems and compare the results with the ones produced by other classifiers / Mestrado / Matematica Aplicada / Mestre em Matemática Aplicada

Orientador: Peter Sussner / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-26T17:27:37Z (GMT). No. of bitstreams: 1 Schuster_Tiago_M.pdf: 2910336 bytes, checksum: 1f5147831dd6410a0fdb0c0fa53d94c8 (MD5) Previous issue date: 2015 / Resumo: As últimas décadas têm testemunhado a emergência de uma variedade de abordagens à resolução de problemas com base na computação em reticulados como, por exemplo, as redes neurais morfológicas e os modelos neurocomputação e de raciocínio fuzzy em reticulados. Usamos aqui o termo "reticulado'' no sentido dado no trabalho seminal de Birkhoff. A teoria dos reticulados nasceu da álgebra booleana e tem um grande leque de aplicações como a análise de conceitos formais, a inteligência computacional, a teoria dos conjuntos fuzzy e a morfologia matemática (MM). A MM em reticulados completos representa a base teórica para uma série de modelos de inteligência computacional conhecidos como redes neurais morfológicas (MNNs), que incluem as memórias associativas morfológicas em tons de cinza e as memórias associativas morfológicas fuzzy (FMAMs). As últimas décadas têm testemunhado a emergência de uma variedade de abordagens à resolução de problemas com base na computação em reticulados como, por exemplo, as redes neurais morfológicas e os modelos neurocomputação e de raciocínio fuzzy em reticulados. Usamos aqui o termo "reticulado'' no sentido dado no trabalho seminal de Birkhoff. A teoria dos reticulados nasceu da álgebra booleana e tem um grande leque de aplicações como a análise de conceitos formais, a inteligência computacional, a teoria dos conjuntos fuzzy e a morfologia matemática (MM). A MM em reticulados completos representa a base teórica para uma série de modelos de inteligência computacional conhecidos como redes neurais morfológicas (MNNs), que incluem as memórias associativas morfológicas em tons de cinza e as memórias associativas morfológicas fuzzy (FMAMs). O advento de sistemas fuzzy tipo-2 sugere o desenvolvimento das FMAMs tipo-2 e em particular FMAMs tipo-2 intervalar, ou FMAMs intervalar (IV-FMAMs). Observemos aqui que a classe dos conjuntos fuzzy, assim como a dos conjuntos fuzzy tipo-2, fuzzy tipo-2 intervalar e fuzzy intervalar sobre um universo arbitrário em conjunção com diferentes escolhas de ordens parciais formam classes de conjuntos L-fuzzy, em que L denota um reticulado completo. Nessa dissertação de mestrado, introduzimos as memórias associativas L-fuzzy (L-FMAMs) com base na morfologia matemática L-fuzzy (L-FMM). Nosso foco está nas FMAMs fuzzy intervalar, uma vez que sistemas fuzzy intervalar têm sido aplicados com sucesso em problemas de engenharia, computação com palavras e raciocínio aproximado. Nós aplicamos os modelos de IV-FMAMs em conjunção com a técnica de clusterização fuzzy c-means intervalar a um problema de predição de série temporal, especificamente o prognóstico da vazão mensal de uma usina hidroelétrica localizada no sudeste brasileiro. Por fim, comparamos as predições produzidas pela abordagem das IV-FMAMs com aquelas produzidas por modelos competitivos da literatura / Abstract: The last decade has witnessed the emergence of a variety of lattice computing approaches towards computational intelligence such as morphological neural networks and fuzzy lattice reasoning / neuro-computing models. Here, the technical term "lattice" refers to a lattice in the mathematical sense of Birkhoff's seminal work. Lattice theory grew out of Boolean algebra and has found a wide range of applications such as mathematical morphology, formal concept analysis, computational intelligence, and fuzzy set theory. Mathematical morphology on complete lattices represents the theoretical basis for a range of computational intelligence models known as morphological neural networks (MNNs) including gray-scale and fuzzy morphological associative memories (FMAMs). The advent of type-2 fuzzy systems suggests the development of type-2 FMAMs and in particular interval type-2 FMAMs or interval-valued FMAMs. Recall that the class of fuzzy sets as well as the classes of type-2, interval type-2, and interval-valued fuzzy sets over an arbitrary universe together with different choices of partial orderings form classes of L-fuzzy sets, where L denotes a complete lattice. In this master's thesis, we introduce L-fuzzy morphological associative memories (L-FMAMs) on the basis of L-FMM. Our focus is on interval-valued FMAMs since interval type-2 fuzzy systems, have found various applications in engineering, computing with words, and approximate reasoning. We applied the aforementioned interval-valued FMAM models in conjunction with the interval-valued fuzzy c-means clustering technique to a time-series prediction problem in industry, namely the problem of forecasting the average monthly streamflow of a hydroelectric plant located in southeastern Brazil, and compared the predictions produced by the IV-FMAM approach with the ones produced by a number of competitive models from the literature / Mestrado / Matematica Aplicada / Mestre em Matemática Aplicada

Resolver um problema de processamento de imagens pode ser uma tarefa bastante complexa. Em geral, isto depende de diversos fatores, como o conhecimento, experiência e intuição de um especialista, e o conhecimento do domínio da aplicação em questão. Motivados por tal complexidade, alguns grupos de pesquisa têm trabalhado na criação de técnicas para projetar operadores de imagens automaticamente, a partir de uma coleção de exemplos de entrada e saída do operador desejado. A abordagem multirresolução tem sido empregada com sucesso no projeto estatístico de W-operadores de janelas grandes. Esta metodologia usa uma estrutura piramidal de janelas para auxiliar na estimação das distribuições de probabilidade condicional para padrões não observados no conjunto de treinamento. No entanto, a qualidade do operador projetado depende diretamente da pirâmide escolhida. Tal escolha é feita pelo projetista a partir de sua intuição e de seu conhecimento prévio sobre o problema. Neste trabalho, investigamos o uso da entropia condicional como um critério para determinar automaticamente uma boa pirâmide a ser usada no projeto do W-operador. Para isto, desenvolvemos uma técnica que utiliza o arcabouço piramidal multirresolução como um modelo na estimação da distribuição conjunta de probabilidades. Experimentos com o problema de reconhecimento de dígitos manuscritos foram realizados para avaliar o desempenho do método. Utilizamos duas bases de dados diferentes, com bons resultados. Além disso, outra contribuição deste trabalho foi a experimentação com mapeamentos de resolução da teoria de pirâmides de imagens no contexto do projeto de W-operadores multirresolução. / The task of finding a good solution for an image processing problem is often very complex. It usually depends on the knowledge, experience and intuition of an image processing specialist. This complexity has served as a motivation for some research groups to create techniques for automatically designing image operators based on a collection of input and output examples of a desired operator. The multiresolution approach has been successfully used to statistically design W-operators for large windows. However, the success of this method directly depends on the adequate choice of a pyramidal window structure, which is used to aid in the estimation of the conditional probability distributions for patterns that do not appear in the training set. The choice is made by the designer, based on his intuition and previous knowledge of the problem domain. In this work, we investigate the use of the conditional entropy criterion for automatically determining a good pyramid. In order to compute the entropy, we have developed a technique that uses the multiresolution pyramidal framework as a model in the estimation of the joint probability distribution. The performance of the method is evaluated on the problem of handwritten digits recognition. Two different databases are used, with good practical results. Another important contribution of this work is the experimentation with resolution mappings from image pyramids theory in the context of multiresolution W-operator design.

Os W-operadores são operadores invariantes por translação e localmente definidos dentro de uma janela W. Devido a sua grande utilidade em análise de imagens, estes operadores foram extensamente pesquisados, sendo que uma abordagem para o seu estudo é a partir da Morfologia Matemática. Uma propriedade interessante de W-operadores é que eles possuem uma sup-decomposição, ou seja, um W-operador pode ser decomposto em termos de uma família de operadores sup-geradores que, por sua vez, são parametrizados por elementos da base desse $W$-operador. No entanto, a sup-decomposição tem uma estrutura intrinsecamente paralela que não permite uma implementação eficiente em máquinas de processamento sequencial. Em um trabalho publicado em 2001, Hashimoto e Barrera formalizaram o problema de transformar a sup-decomposição em decomposições puramente sequenciais como um problema de encontrar soluções discretas de uma equação. Neste texto, estendemos o trabalho desenvolvido por eles. Estudamos e exploramos as propriedades matemáticas do problema, e desenvolvemos estratégias heurísticas para encontrar uma decomposição sequencial de um $W$-operador a partir de sua base que seja eficiente ao ser executado. / W-operators are defined as operators which are translation invariant and locally defined within a finite window W. Due to their great contribution to image processing, these operators have been widely researched and used, specially in Mathematical Morphology. An interesting property of W-operators is that they have a sup-decomposition in terms of a family of sup-generating operators, that are parameterized by their basis. However, the sup-decomposition has a parallel structure that is not efficient in sequential machines. In a paper published in 2001, Hashimoto and Barrera formalized the problem of transforming sup-decompositions into purely sequential decompositions as a problem of finding discrete solutions of an equation. In this work, we extend Hashimoto and Barrera\'s approach. We study and explore mathematical properties of this problem and we elaborate heuristic strategies to find a sequential decomposition of a $W$-operator from its basis that can be executed efficiently.

This thesis focuses on advanced methods of detecting contours of the cardiac cells and measuring their contraction. The theoretical section describes the types of confocal microscopes, which are used for capturing biological samples. The following chapter is devoted to the methods of cardiac cells segmentation, where we are introduced to the generally applied approaches. The most widely spread methods of segmentation are active contours and mathematical morphology, which are the crucial topics of this thesis. Thanks to the those methods we are able in the visual data to accurately detect required elements and measure their surface chnage in time. Acquired theoretical knowledge leads us to the practical realization of the methods in MATLAB.

Résumé : La détection des bâtiments dans les images à très haute résolution spatiale (THRS) a plusieurs applications pratiques et représente un domaine de recherche scientifique intensive ces dernières années. Elle fait face à la complexité du milieu urbain et aux spécificités des images provenant des différents capteurs. La performance des méthodes existantes pour l’extraction des bâtiments n’est pas encore suffisante pour qu’elles soient généralisées à grande échelle (différents types de tissus urbains et capteurs). Les opérateurs morphologiques se sont montrés efficaces pour la détection des bâtiments dans les images panchromatiques (images en niveaux de gris) à très haute résolution spectrale (THRS). L’information spectrale issue des images multispectrales est jugée nécessaire pour l’amélioration de leur performance. L’extension des opérateurs morphologiques pour les images multispectrales exige l’adoption d’une stratégie qui permet le traitement des pixels sous forme de vecteurs, dont les composantes sont les valeurs dans les différentes bandes spectrales. Ce travail de recherche vise l’application de la transformation morphologique dite Hit-or-Miss (HMT) à des images multispectrales à THRS, afin de détecter des bâtiments. Pour répondre à la problématique de l’extension des opérateurs morphologiques pour les images multispectrales, nous proposons deux solutions. Comme une première solution nous avons généré des images en niveaux de gris à partir les bandes multispectrales. Dans ces nouvelles images les bâtiments potentiels sont rehaussés par rapport à l’arrière-plan. La HMT en niveaux de gris est alors appliquée à ces images afin de détecter les bâtiments. Pour rehausser les bâtiments nous avons proposé un nouvel indice, que nous avons appelé Spectral Similarity Ratio (SSR). Pour éviter de définir des configurations, des ensembles d’éléments structurants (ES), nécessaires pour l’application de la HMT, au préalable, nous avons utilisé l’érosion et la dilatation floues et poursuivi la réponse des pixels aux différentes valeurs des ES. La méthode est testée sur des extraits d’images représentant des quartiers de type résidentiel. Le taux moyen de reconnaissance obtenu pour les deux capteurs Ikonos et GeoEye est de 85 % et de 80 %, respectivement. Le taux moyen de bonne identification, quant à lui, est de 85 % et 84 % pour les images Ikonos et GeoEye, respectivement. Après certaines améliorations, la méthode a été appliquée sur des larges scènes Ikonos et WorldView-2, couvrant différents tissus urbains. Le taux moyen des bâtiments reconnus est de 82 %. Pour sa part, le taux de bonne identification est de 81 %. Dans la deuxième solution, nous adoptons une stratégie vectorielle pour appliquer la HMT directement sur les images multispectrales. La taille des ES de cette transformation morphologique est définie en utilisant la transformation dite chapeau haut-de-forme par reconstruction. Une étape de post-traitement inclut le filtrage de la végétation par l’indice de la végétation NDVI et la validation de la localisation des bâtiments par l’information d’ombre. La méthode est appliquée sur un espace urbain de type résidentiel. Des extraits d’images provenant des capteurs satellitaires Ikonos, GeoEye et WorldView 2 ont été traités. Le taux des bâtiments reconnus est relativement élevé pour tous les extraits - entre 85 % et 97 %. Le taux de bonne identification démontre des résultats entre 74 % et 88 %. Les résultats obtenus nous permettent de conclure que les objectifs de ce travail de recherche, à savoir, la proposition d’une technique pour l’estimation de la similarité spectrale entre les pixels formant le toit d’un bâtiment, l’intégration de l’information multispectrale dans la HMT dans le but de détecter les bâtiments, et la proposition d’une technique qui permet la définition semi-automatique des configurations bâtiment/voisinage dans les images multispectrales, ont été atteints. // Abstract : Detection of buildings in very high spatial resolution images (THRS) has various practical applications and is recently a subject of intensive scientific research. It faces the complexity of the urban environment and the variety of image characteristics depending on the type of the sensor. The performance of existing building extraction methods is not yet sufficient to be generalized to a large scale (different urban patterns and sensors). Morphological operators have been proven effective for the detection of buildings in panchromatic (greyscale) very high spectral resolution (VHSR) images. The spectral information of multispectral images is jugged efficient to improve the results of the detection. The extension of morphological operators to multispectral images is not straightforward. As pixels of multispectral images are pixels vectors the components of which are the intensity values in the different bands, a strategy to order vectors must be adopted. This research thesis focuses on the application of the morphological transformation called Hit-or-Miss (HMT) on multispectral VHSR images in order to detect buildings. To address the issue of the extension of morphological operators to multispectral images we have proposed two solutions. The first one employs generation of greyscale images from multispectral bands, where potential buildings are enhanced. The grayscale HMT is then applied to these images in order to detect buildings. To enhance potential building locations we have proposed the use of Spectral Similarity Ratio (SSR). To avoid the need to set multiple configurations of structuring elements (SE) necessary for the implementation of the HMT, we have used fuzzy erosion and fuzzy dilation and examined the pixel response to different values of SE. The method has been tested on image subsets taken over residential areas. The average rate of recognition for the two sensors, Ikonos and GeoEye, is 85% and 80%, respectively. The average rate of correct identification is 85% and 84%, for Ikonos and GeoEye subsets, respectively. Having made some improvements, we then applied the method to large scenes from Ikonos and WorldView-2 images covering different urban patterns. The average rate of recognized buildings is 82%. The rate of correct identification is 81%. As a second solution, we have proposed a new vector based strategy which allows the multispectral information to be integrated into the percent occupancy HMT (POHMT). Thus, the POHMT has been directly applied on multispectral images. The parameters for the POHMT have been defined using the morphological transformation dubbed top hat by reconstruction. A post-processing step included filtering the vegetation and validating building locations by proximity to shadow. The method has been applied to urban residential areas. Image subsets from Ikonos, GeoEye and WorldView2 have been processed. The rate of recognized buildings is relatively high for all subsets - between 85% and 97%. The rate of correct identification is between 74 % and 88 %. The results allow us to conclude that the objectives of this research, namely, suggesting a technique for estimating the spectral similarity between the pixels forming the roof of a building, the integration of multispectral information in the HMT in order to detect buildings and the proposition of a semiautomatic technique for the definition of the configurations building/neighbourhood in multispectral images, have been achieved.

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5.4pt;mso-para-margin:0in;mso-para-margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:11.0pt;font-family:"Calibri","sans-serif";mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:"Times New Roman";mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}</style><![endif]--><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">The </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">t</span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">hesis investigates development, improvement and evaluation of methods for quantitative characterization of objects from their digital images and similarity measurements between digital images. Methods for quantitative characterization of objects from their digital images are increasingly used in applications in which error can </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">have crtical consequences, </span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">but the traditional methods for shape quantification are of low precision and accuracy. </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">In the thesis is shown </span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">that the </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">coverage of a pixel by a shape can</span><span style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:EN-US;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA"> be used to highly improve the accuracy and precision of using digital images to estimate the maximal distance between objects </span><span lang="sr-Latn-RS" style="font-size:9.0pt;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-font-kerning:.5pt;mso-ansi-language:#241A;mso-fareast-language:AR-SA;mso-bidi-language:AR-SA">furthest points measured in a given direction. It is highly desirable that a distance measure between digital images can be related to a certain shape property and morphological operations are used when defining a distance for this purpose. Still, the distances defined in this manner turns out to be insufficiently sensitive to relevant data representing shape properties in images. We show that the idea of adaptive mathematical morphology can be used successfully to overcome problems related to sensitivity of distances defined via morphological operations when comparing objects from their digital image representations.</span></p> / <p>У тези су размотрени развој, побољшање и евалуација метода за квантитативну карактеризацију објеката приказаних дигиталним сликама, као и мере растојања између дигиталних слика. Методе за квантитативну карактеризацију објеката представљених дигиталним сликама се&nbsp; све више користе у применама у којима грешка може имати критичне последице, а традиционалне методе за&nbsp; квантитативну карактеризацију су мале прецизности и тачности. У тези се показује да се коришћењем информације о покривеност пиксела обликом може значајно побољшати прецизност и тачност оцене растојања између две најудаљеније тачке облика мерено у датом правцу. Веома је пожељно да мера растојања између дигиталних слика може да се веже за одређену особину облика и морфолошке операције се користе приликом дефинисања растојања у ту сврху. Ипак, растојања дефинисана на овај начин показују се недовољно осетљива на релевантне податке дигиталних слика који представљају особине облика. У тези се показује да идеја адаптивне математичке морфологије може успешно да се користи да би се превазишао поменути&nbsp; проблем осетљивости растојања дефинисаних користећи морфолошке операције.</p> / <p>U tezi su razmotreni razvoj, poboljšanje i evaluacija metoda za kvantitativnu karakterizaciju objekata prikazanih digitalnim slikama, kao i mere rastojanja između digitalnih slika. Metode za kvantitativnu karakterizaciju objekata predstavljenih digitalnim slikama se&nbsp; sve više koriste u primenama u kojima greška može imati kritične posledice, a tradicionalne metode za&nbsp; kvantitativnu karakterizaciju su male preciznosti i tačnosti. U tezi se pokazuje da se korišćenjem informacije o pokrivenost piksela oblikom može značajno poboljšati preciznost i tačnost ocene rastojanja između dve najudaljenije tačke oblika mereno u datom pravcu. Veoma je poželjno da mera rastojanja između digitalnih slika može da se veže za određenu osobinu oblika i morfološke operacije se koriste prilikom definisanja rastojanja u tu svrhu. Ipak, rastojanja definisana na ovaj način pokazuju se nedovoljno osetljiva na relevantne podatke digitalnih slika koji predstavljaju osobine oblika. U tezi se pokazuje da ideja adaptivne matematičke morfologije može uspešno da se koristi da bi se prevazišao pomenuti&nbsp; problem osetljivosti rastojanja definisanih koristeći morfološke operacije.</p>

Les caméras infrarouges modernes permettent d’accéder à la mesure de champs thermiques et de leur évolution temporelle. Le traitement d’images obtenues permet d’analyser la signature thermique d’objets mobiles ou de fluides en écoulement. Dans ce contexte nous avons fait l’étude de trois expériences différentes. La première consiste à suivre des billes mobiles et à évaluer leurs coefficients d’échanges thermiques avec l’environnement par l’estimation de temps caractéristiques. Dans le deuxième cas, nous faisons une comparaison entre deux fluides qui s’écoulent dans un microcanal, afin de déterminer les variations relatives des propriétés thermiques. La dernière application consiste à réaliser une cartographie de diffusivité thermique avec une source de chaleur mobile. / The modern infrared cameras allow the measurement of thermal fields and their temporal evolution. Infrared images processing is suitable to analyze the thermal signature of moving objects or fluid flows. In this context, we made the study of three different experiments. The first one is relative to infrared tracking of randomly moving balls and then estimate their thermal exchanges with the environment by the estimation of some characteristic time. In the second case we made a comparison between two fluids which flow inside a microchannel in order to determine the relative changes of thermal properties. The last application was to estimate a thermal diffusivity field with a mobile heat source.