Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2016-10-17T13:34:17Z No. of bitstreams: 2 Dissertação - Elias Borges Macena Junior - 2016.pdf: 9321304 bytes, checksum: ca477b8a1eeb56b690f41c443b0ca638 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2016-10-17T17:17:50Z (GMT) No. of bitstreams: 2 Dissertação - Elias Borges Macena Junior - 2016.pdf: 9321304 bytes, checksum: ca477b8a1eeb56b690f41c443b0ca638 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-10-17T17:17:50Z (GMT). No. of bitstreams: 2 Dissertação - Elias Borges Macena Junior - 2016.pdf: 9321304 bytes, checksum: ca477b8a1eeb56b690f41c443b0ca638 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-09-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / In order to improve the diagnostic process several research centers have focused on the development of information systems applying powerful techniques of computer-aided diagnosis (CAD). In this context, the creation of content-based image retrieval (CBIR) is an important step in developing an efficient CAD system. This work proposes the validation of recovery with a hybrid CBIR method based on 2D medical images. The results of the techniques applied, indicate a hit rate of 90.25% and indicate a gain of 35% in the performance of techniques, that is, the time search and retrieval of images, paving the way for the development of information systems more efficient to build support generic diagnostic systems. / Com o objetivo de melhorar o processo de diagnóstico vários centros de pesquisas têm focado no desenvolvimento de sistemas de informação aplicando poderosas técnicas de diagnóstico auxiliado por computador (Computer-Aided Diagnosis-CAD). Neste contexto, a criação de métodos de recuperação de imagens baseado em conteúdo (Content-based image retrieval - CBIR) é um passo importante para desenvolver um sistema CAD eficiente. Este trabalho propõe a validação de técnicas de recuperação com um método híbrido CBIR baseado em imagens médicas 2D. Os resultados das técnicas aplicadas, indicam uma taxa de acerto de 90,25% e ainda indicam um ganho de 35% no desempenho das técnicas, isto é, no tempo de busca e recuperação das imagens, abrindo caminho para o desenvolvimento de sistemas de informação mais eficientes para construção de sistemas de apoio ao diagnóstico genéricos.

O objetivo deste trabalho é avaliar a recuperação de imagem por conteúdo (CBIR - Content-based Image Retrieval) em uma rede de computadores, estabelecendo-se métricas de controle que otimizem a utilização da rede e ao mesmo tempo garanta melhor qualidade na resposta. Prevê-se a recuperação de imagens baseada em consulta por similaridade, combinando-se o extrator de características com a função de distância. O desenvolvimento é realizado em uma linguagem de programação independente da plataforma e de âmbito de internet, utilizado Java, desenvolvendo-se uma API (Application Programming Interface), visando, em especial, a reutilização de código, o que implica na diminuição do tempo de desenvolvimento. O trabalho demonstra a utilização de estruturas de indexação sequencial, comparada com a estrutura de indexação de árvore \"Slim-tree\". A principal contribuição deste trabalho é a análise e a utilização de métricas na rede de computadores em um projeto de CBIR. / The objective of this study is to evaluate the Content-based Image Retrieval (CBIR) in a computer network, establishing control metrics that optimize the use of network while ensuring better quality in the response. It is expected that images are going to be recovered based on queries that are similar, combining the features extractor with the distance function. The development environment is an independent language of the platform and of the Internet scope, using Java, that has developed an Application Programming Interfaces (API), aiming primarily the code reuse, which implies a decrease in the development time. This thesis demonstrates the use of sequential indexing structures compared to the tree index structure \"Slim-tree\". The main contribution of this thesis is the analysis and utilization of metrics in a computer network project in CBIR.

Les courbes remplissant l'espace sont connues pour la capacité d'ordonner les points multidimensionnels sur une ligne en tout conservant la localité, i.e. les points proches sont toujours proches sur la ligne. La conservation de la localité est beaucoup recherchée dans plusieurs applications. La courbe de Hilbert est la courbe remplissant l'espace qui conserve le mieux la localité. Cette courbe est originalement proposée en 2D, i.e. n'est qu'applicable aux points dans un espace 2D. Pour une perspective d'application dans le cas multidimensionnel, nous proposons dans cette thèse une généralisation de la courbe de Hilbert. La courbe généralisée est définie en s'appuyant sur la propriété essentielle de la courbe de Hilbert qui crée son niveau de conservation de la localité : l'adjacence. Ainsi, elle évite la dépendance du motif primitif RBG qui est le seul motif primitif de la courbe étendu par les recherches précédentes. Le résultat est donc une famille de courbe conservant bien la localité. L'optimisation de la conservation de la localité est aussi abordée pour permettre de retrouver la courbe qui conserve le mieux la localité. Pour cet objectif, nous proposons une mesure de la conservation de la localité. En s'appuyant sur les paramètres, cette mesure peut adapter aux différentes situations applicatives comme le changement de métrique ou de taille de localité. La construction est une partie importante de la thèse, elle est la base du calcul de l'index utilisé dans l'application. Pour un calcul de l'index rapide, la courbe de Hilbert autosimilaire est utilisée. La courbe de Hilbert satisfaisant les conditions de la courbe fait l'objet du chapitre 4. La courbe généralisée est enfin appliquée dans la recherche d'image. Il s'agit d'une recherche par le contenu où chaque image est caractérisée par un vecteur multidimensionnel. Les images sont ordonnées par la courbe sur une ligne ; ainsi, la recherche est simplifiée en une recherche sur une liste ordonnée. En donnant une image d'entrée, les images similaires sont celles correspondantes aux index voisins de l'index de l'image d'entrée. La conservation de la localité garantit que ces index correspondent aux images similaires. / The space-filling curves are known for the ability to order the multidimensional points on a line while preserving the locality, i.e. the close points are closely ordered on the line. The locality preserving is wished in many applications. Hilbert curve is the best locality preserving space-filling curve. This curve is originally proposed in 2D, i.e. it is only applied to points in a 2D space. For application in the multidimensional case, we propose in this thesis a generalization of Hilbert curve. Generalized curve is based on the essential property of Hilbert curve that creates its level of locality preserving: the adjacency. Thus, it avoids the dependence on the pattern RBG, which is the only pattern of the curve extended by previous researches. The result is a family of curves preserving well the locality. The optimization of the locality preserving is also addressed to find out the best locality preserving curve. For this purpose, we propose a measure of the locality preserving. Based on the parameters, this measure can adapt to different application situations such as the change of metric or locality size. The curve construction is an important part of the thesis. It is the basis of the index calculation used in application. For a rapid index calculation, the self-similar Hilbert curves is used. They are Hilbert curves satisfying the self-similar conditions specified in chapitre 4. The generalized curve is finally applied in image search. It is the question of the content-based image search (CBIR) where each image is characterized by a multidimensionalvector. Images are ordered by the curve of a line, and the search is simplified to the search on an ordered list. By giving an input image, similar images are those corresponding to neighbors of the index of the input. The locality preserving ensures that these indexes correspond to similar images.

A recuperação de imagens baseada em conteúdo, amplamente conhecida como CBIR (do inglês Content-Based Image Retrieval), é um ramo da área da computação que vem crescendo muito nos últimos anos e vem contribuindo com novos desafios. Sistemas que utilizam tais técnicas propiciam o armazenamento e manipulação de grandes volumes de dados e imagens e processam operações de consultas de imagens a partir de características visuais extraídas automaticamente por meio de métodos computacionais. Esses sistemas devem prover uma interface de usuário visando uma interação fácil, natural e atraente entre o usuário e o sistema, permitindo que o usuário possa realizar suas tarefas com segurança, de modo eficiente, eficaz e com satisfação. Desse modo, o design da interface firma-se como um elemento fundamental para o sucesso de sistemas CBIR. Contudo, dentro desse contexto, a interface do usuário ainda é um elemento constituído de pouca pesquisa e desenvolvimento. Um dos obstáculos para eficácia de design desses sistemas consiste da necessidade em prover aos usuários uma interface de alta qualidade para permitir que o usuário possa consultar imagens similares a uma dada imagem de referência e visualizar os resultados. Para atingir esse objetivo, este trabalho visa analisar a interação do usuário em sistemas de recuperação de imagens por conteúdo e avaliar sua funcionalidade e usabilidade, aplicando técnicas de interação humano-computador que apresentam bons resultados em relação à performance de sistemas com grande complexidade, baseado em um estudo de caso aplicado à medicina / The content-based image retrieval (CBIR) is a challenging area of the computer science that has been growing in a very fast pace in the last years. CBIR systems employ techniques for extracting features from the images, composing the features vectores, and store them together with the images in data bases management system, allowing indexing and querying. CBIR systems deal with large volumes of images. Therefore, the feature vectors are extracted by automatic methods. These systems allow to query the images by content, processing similarity queries, which inherently demands user interaction. Consequently, CBIR systems must pay attention to the user interface, aiming at providing friendly, intuitive and attractive interaction, leading the user to do the tasks efficiently, getting the desired results, feeling safe and fulfilled. From the points highlighted beforehand, we can state that the human-computer interaction (HCI) is a key element of a CBIR system. However, there is still little research on HCI for CBIR systems. One of the requirements of HCI for CBIR is to provide a high quality interface to allow the user to search for similar images to a given query image, and to display the results properly, allowing further interaction. The present dissertation aims at analyzing the user interaction in CBIR systems specially suited to medical applications, evaluating their usability by applying HCI techniques. To do so, a case study was employed, and the results presented

Un défi pour les systèmes de recherche basée sur le contenu réside dans la nécessité d’avoir une base annotée. Cette thèse propose un système d’annotation d’images interactif par le regard afin d’alléger la tâche d’annotation. Le but est de classer un petit ensemble d’images en fonction d’une catégorie cible (classification binaire) pour classer un grand ensemble d’images. Parmi les caractéristiques du regard pointées comme informatives sur l’intention des utilisateurs, nous avons élaboré un estimateur d’intention par le regard, calculable en temps réel, indépendant de l’utilisateur et de la catégorie cible. Cette annotation implicite est meilleure qu’une annotation aléatoire mais reste incertaine. Dans une deuxième partie, les images ainsi annotées sont utilisées pour classifier un plus grand ensemble d’images avec un algorithme prenant en compte l’incertitude des labels : P-SVM combinant classification et régression. Nous avons déterminé parmi différentes stratégies un critère de pertinence pour discriminer les labels les plus fiables, utilisés pour la classification, des labels les plus incertains, utilisés pour la régression. La précision du P-SVM est évaluée dans différents contextes et peut atteindre les performances d’un algorithme de classification standard entraîné avec les labels certains. Ces évaluations ont tout d’abord été menées sur un benchmark standard pour se comparer à l’état de l’art, et dans un second temps, sur une base d’images de nourriture. / One daunting challenge of Content Based Image Retrieval systems is the requirement of annotated databases. To limit the burden of annotation, this thesis proposes a system of image annotation based on gaze data. The purpose is to classify a small set of images according to a target category (binary classification) in order to classify a set of unseen images. First, we have designed a protocol based on visual preference paradigm in order to collect gaze data from different groups of participants during a category identification task. Among the gaze features known to be informative about the intentions of the participants, we have determined a Gaze-Based Intention Estimator (GBIE), computable in real-time; independent from both the participant and the target category. This implicit annotation is better than random annotation but is inherently uncertain. In a second part, the images annotated by the GBIE from the participants’ gaze data are used to classify a bigger set of images with an algorithm that handles label uncertainty: P-SM combining classification and regression SVM. We have determined among different strategies a criterion of relevance in order to discriminate the most reliable labels, involved in the classification part, from the most uncertain labels, involved in the regression part. The average accuracy of P-SVM is evaluated in different contexts and can compete with the performances of standard classification algorithm trained with true-class labels. These evaluations were first conducted on a standard benchmark for comparing with state-of-the-art results and later conducted on food image dataset.

Cette thèse a pour but de proposer de nouvelles méthodes d'indexation des bases de données vidéo de type archive culturelle à partir des actions humaines qu'elles contiennent. Les actions humaines, représentent un aspect important des contenus multimédia, à côté des sons, images ou de la parole. L'interrogation technique principale à laquelle nous répondons est ``Comment détecter et localiser précisément et rapidement dans une vidéo une action humaine, à partir de quelques exemples de cette même action?''. Le défi relevé par cette interrogation se trouve dans la satisfaction de ces deux critères: qualité de détection et rapidité.Nous avons traité, dans une première partie, l'adaptation des mesures de similarité aux contraintes de temps de calcul et mémoire nécessaires pour avoir un système rapide de détection d'actions. Nous avons montré qu'une approche de type "alignement de séquences" couplée avec une sélection de variables permet de répondre rapidement à des requêtes et obtient une bonne qualité des résultats. L'ajout d'un filtrage préliminaire permet d'améliorer encore les performances.Dans une seconde partie de la thèse nous avons crée une méthode d'accélération de l'étage de filtrage pour obtenir une complexité de recherche sous-linéaire dans la taille de la base. Nous nous sommes basés sur le hachage sensible à la similarité et sur une nouvelle approche à l'exploration dans l'espace de hachage, adaptée à la << requête-par-détecteur >>.Nous avons testé les méthodes proposées sur une nouvelle base annotée de vidéos de grande taille destinée à la détection et localisation d'actions humaines. Nous avons montré que nos approches donnent des résultats de bonne qualité et qu'elles peuvent passer à l'échelle. / This thesis proposes new methods for indexing video collections with varied content, such as cultural archives. We focus on human actions, which represent an important cultural aspect, together with sound, images and speech. Our main technical challenge is 'How to quickly detect and precisely localize human actions in a large video collection, when these actions are given as a query through example video clips?'. Thus, the difficulty of the task is due to criteria: quality of detection and search response time.

This thesis documents the research which has led to the design of a number of techniques aiming to improve the performance of content-based image retrieval (CBIR) systems in wavelets domain using texture analysis. Attention was drawn on CBIR in transform domain and in particular wavelets because of the excellent characteristics for compression and texture extraction applications and the wide adoption in both the research community and the industry. The issue of performance is addressed in terms of accuracy and speed. The rationale for this research builds upon the conclusion that CBIR has not yet reached a good performance balance of accuracy, efficiency and speed for wide adoption in practical applications. The issue of bridging the sensory gap, which is defined as "[the difference] between the object in the real world and the information in a (computational) description derived from a recording of that scene." has yet to be resolved. Furthermore, speed improvement remains an uncharted territory as is feature extraction directly from the bitstream of compressed images. To address the above requirements the first part of this work introduces three techniques designed to jointly address the issue of accuracy and processing cost of texture characterization in wavelets domain. The second part introduces a new model for mapping the wavelet coefficients of an orthogonal wavelet transformation to a circular locus. The model is applied in order to design a novel rotation-invariant texture descriptor. All of the aforementioned techniques are also designed to bridge the gap between texture-based image retrieval and image compression by using appropriate compatible design parameters. The final part introduces three techniques for improving the speed of a CBIR query through more efficient calculation of the Li-distance, when it is used as an image similarity metric. The contributions conclude with a novel technique which, in conjunction with a widely adopted wavelet-based compression algorithm, extracts texture information directly from the compressed bit-stream for speed and storage requirements savings. The experimental findings indicate that the proposed techniques form a solid groundwork which can be extended to practical applications.

No description available.

A Recuperação de Imagens Baseada em Conteúdo (Content-Based Image Retrieval - CBIR) visa recuperar, em uma base de imagens, as ocorrências mais similares a uma imagem fornecida como modelo, a partir de características extraídas desses objetos. O uso dos conceitos de CBIR, embora bem explorado para recuperação de imagens bidimensionais, ainda é pouco explorado no domínio de objetos tridimensionais. A partir da identificação de lacunas na literatura a respeito da abordagem eficiente para recuperação destes objetos, o objetivo deste estudo foi definir, implementar e validar técnicas de recuperação destes objetos médicos tridimensionais com base no seu conteúdo considerando buscas globais e regionalizadas da estrutura tridimensional. Para atingir tal objetivo foram realizadas as seguintes atividades: revisão bibliográfica, definição da base de dados, implementação de descritores e métodos de comparação por similaridade, construção de um protótipo de sistema de recuperação, realização de testes com objetos médicos tridimensionais e análise dos resultados. Os resultados obtidos com os métodos desenvolvidos foram positivos, alcançando 90% de média de precisão no retorno da busca. Verificou-se que os descritores baseados em Harmônicos Esféricos podem ser adaptados para serem utilizados como descritores locais. Adicionalmente, verificou-se que a abordagem utilizando grafos bipartidos em conjunto com o cálculo de similaridade por meio de uma rede de fluxo, produziu resultados melhores do que os métodos que utilizaram abordagens clássicas de comparação. Em relação ao estudo de caso analisado, as Cardiomiopatias, foi possível constatar que as informações de idade e gênero contribuem para melhorar a precisão da recuperação, uma vez que essas informações podem influenciar diretamente a estrutura do ventrículo esquerdo. Além disso, em uma avaliação com usuários finais da área de Cardiologia, constatou-se que efetivamente esta abordagem pode auxiliar na composição de diagnósticos. Estes resultados confirmaram o potencial que a recuperação por conteúdo possui no contexto médico, além de contribuir com a área de Computação no sentido de ter desenvolvido técnicas para recuperação por conteúdo no domínio de objetos tridimensionais. / Content-Based Image Retrieval - CBIR aims to retrieval, in an image database, the most similar occurrences to an image provided as a query, from extracted characteristics of these objects. The use of CBIR concept, although exploited for recovery of twodimensional images, is still under explored in the three-dimensional objects knowledge field. Based on the identification of the current literature gaps regarding efficient approaches to retrieval these objects, the objective of this study was to define, implement and validate retrieval techniques of three-dimensional medical objects based on their content considering global and regionalized searches of the three-dimensional structure. In order to achieve this objective, the following activities were carried out: literature review, database definition, implementation of descriptors and methods of comparison by similarity, construction of a retrieval system prototype, tests with three-dimensional medical objects and results analysis. The results obtained with the methods developed were positive, reaching 90% of mean precision in the return of the search. It has been found that the descriptors based on Spherical Harmonics can be adapted to be used as local descriptors. Additionally, it was identified that the approach using bipartite graphs in conjunction with the similarity computation through network flow, produced better results than the methods that used classic approaches of comparison. Regarding the case study analyzed, the Cardiomyopathies, it was possible to verify that the information of age and gender contribute to improve the accuracy of the retrieval, since this information can directly influence the structure of the left ventricle. In addition, in an evaluation with end users of Cardiology area, it was verified that this approach can effectively aid in the diagnoses. These results confirmed the potential that content-based retrieval has in the medical context, as well as contribute to the Computing area in the sense of developing techniques for content-based in three-dimensional retrieval.

Neste trabalho é apresentada a implantação de um servidor de imagens médicas com a implementação e integração de módulos para recuperação textual e baseada em conteúdo para o Serviço de Radiodiagnóstico do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto (HCFMRP) da Universidade de São Paulo (USP). O sistema permite a aquisição, gerenciamento, armazenamento e disponibilização das informações dos pacientes, seus exames, laudos e imagens através da internet. Os exames radiológicos e suas respectivas imagens podem ser recuperados por informações textuais ou por similaridade do conteúdo pictório das imagens. As imagens utilizadas são de ressonância magnética nuclear e tomografia computadorizada e são geradas no padrão DICOM 3.0. O sistema foi desenvolvido contemplando tecnologias para Web com interfaces amigáveis para recuperação das informações. Ele é composto por três módulos integrados, sendo o servidor de imagens, o módulo de consulta textual e o módulo de consulta por similaridade. Os resultados apresentados indicam que as imagens são gerenciadas e armazenadas corretamente, bem como o tempo de retorno das imagens é clinicamente satisfatório, tanto para a consulta textual como para a consulta por similaridade. As avaliações da recuperação por similaridade apresentam que o extrator escolhido pode ser considerado relevante para separar as imagens por região anatômica. / This work introduces an the development of a server of medical images with the implementation and integration of modules to query/retrieve text information and content-based to Radiology Service of Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto (HCFMRP) at Universidade de São Paulo (USP). The system allows the acquisition, management, archiving and availability of the patients information, theirs exams, results and images through of internet. The radiological exams and theirs respectives images can be retrieved by text information or similarity of pictorial content of images. Images are from magnetic resonance nuclear and computadorized tomography and are given using DICOM 3.0 protocol. The system has been developed considering web technologies with friendly interfaces to retrieval of information. It is composed by three integrated modules: the image server module, the query text module and query by similarity module. Results show that images are managed and archived exactly, retrieval time of images is clinically satisfactory, considering both the text query as well as the query by similarity. The evaluation of the retrieval by similarity shows the chosen extractor can be considerated relevant to separate the images by anatomic region.