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Doctoral Thesis
DOI
https://doi.org/10.11606/T.76.2000.tde-14012009-101451
Document
Author
Full name
Luís Augusto Consularo
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2000
Supervisor
Committee
Costa, Luciano da Fontoura (President)
Bellon, Olga Regina Pereira
Cesar Junior, Roberto Marcondes
Mascarenhas, Nelson Delfino D'Ávila
Slaets, Jan Frans Willem
Title in Portuguese
Técnicas de mineração de dados para análise de imagens
Keywords in Portuguese
Análise de formas
Análise de imagens
Descoberta de conhecimento em imagens
Mineração de dados
Visão computacional
Abstract in Portuguese
Imagens codificadas por matrizes de intensidade são tipicamente representadas por grande quantidade de dados. Embora existam inúmeras abordagens para análise de imagens, o conhecimento sobre problemas específicos é raramente considerado. Este trabalho trata sobre problemas de análises de imagens cujas soluções dependem do conhecimento sobre os dados envolvidos na aplicação específica. Para isso, utiliza técnicas de mineração de dados para modelar as respostas humanas obtidas de experimentos psicofísicos. Dois problemas de análise de imagens são apresentados: (1) a análise de formas e (2) a análise pictórica. No primeiro problema (1), formas de neurônios da retina (neurônios ganglionares de gato) são segmentadas e seus contornos submetidos a uma calibração dos parâmetros de curvatura considerando a segmentação manual de um especialista. Outros descritores, tais como esqueletos multi-escalas são explorados para eventual uso e avaliação da abordagem. No segundo problema (2), a análise pictórica de imagens de home-pages serve para avaliar critérios estéticos a partir de medidas de complexidade, contraste e textura. O sistema generaliza as respostas por um experimento psicofísico realizados com humanos. Os resultados objetivos com as duas abordagens revelaram-se promissores, surpreendentes e com ampla aplicabilidade.
Title in English
Data mining techniques for image analysis
Keywords in English
Computer vision
Data mining
Image analysis
Image understanding
Shape analysis
Abstract in English
Images coded by intensity matrices typically involve large amount of data. Although image analysis approaches are diverse, knowledge about specific problems is rarely considered. This work is about image analysis problems whose solutions depend on the knowledge about the involved data. In order to do so data mining techniques are applied to model human response to psychophysical experiments. Two image analysis problems are addressed: (1) shape analysis; and (2) pictorial analysis. In the former, neuronal images (ganglion retinal cells of cat) are segmented and curvature parameters are calibrated to identify extremities and branches on the shape considering human segmentation as a reference. Descriptors such as multiscale skeletons are also explored for potential application or evaluations. In the second problem, a pictorial analysis of home-pages images feed an artificial aesthetics criteria evaluator based on complexity, contrast and texture features. The system models and generalizes the obtained human responses to psychophysical experiment. The results for these two approaches are promising, surprising and widely applicable.
 
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Publishing Date
2009-01-19
 
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