Content-based image retrieval of museum images

Content-based image retrieval (CBIR) is becoming more and more important with the advance of multimedia and imaging technology. Among many retrieval features associated with CBIR, texture retrieval is one of the most difficult. This is mainly because no satisfactory quantitative definition of texture exists at this time, and also because of the complex nature of the texture itself. Another difficult problem in CBIR is query by low-quality images, which means attempts to retrieve images using a poor quality image as a query. Not many content-based retrieval systems have addressed the problem of query by low-quality images. Wavelet analysis is a relatively new and promising tool for signal and image analysis. Its time-scale representation provides both spatial and frequency information, thus giving extra information compared to other image representation schemes. This research aims to address some of the problems of query by texture and query by low quality images by exploiting all the advantages that wavelet analysis has to offer, particularly in the context of museum image collections. A novel query by low-quality images algorithm is presented as a solution to the problem of poor retrieval performance using conventional methods. In the query by texture problem, this thesis provides a comprehensive evaluation on wavelet-based texture method as well as comparison with other techniques. A novel automatic texture segmentation algorithm and an improved block oriented decomposition is proposed for use in query by texture. Finally all the proposed techniques are integrated in a content-based image retrieval application for museum image collections

Um modelo para recuperação por conteudo de imagens de sensoriamento remoto

Orientador: Neucimar Jeronimo LeiteTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O problema da recuperação de imagens por conteúdo tem sido uma área de muito interesse nos últimos anos, com múltiplas aplicações em diferentes domínios de geração de imagens. Uma classe de imagem onde este problema não tem sido resolvido satisfatoriamente referese à classe de Sensoriamento Remoto. Imagens de Sensoriamento Remoto (ISR) são obtidas como combinação do sensoriamento da Terra em múltiplas bandas espectrais. Esta tese aborda o problema da recuperação por em conteúdo das ISR . Este tipo de recuperação parte da caracterização do conteúdo de uma imagem e uma das suas principais abordagens considera modelos matemáticos da área de Processamento de Imagens a ser abordada nesta tese. Neste trabalho, abordamos o processo de recuperação de ISR que utilizando três recursos principais: padrões de textura e cor como elemento básico da consulta, uso de múltiplos modelos matemáticos de representação e caracterização do conteúdo e um mecanismo de retroalimentação para o processo de consulta. As principais contribuições da tese são: (1) uma análise dos problemas da recuperação por conteúdo para ISR; (2) a proposta de um modelo para esta recuperação; (3) um modelo e métrica de similaridade baseado no modelo proposto; (4) proposta de implementação do processamento das consultas que mostra a viabilidade do modeloAbstract: Content-based retrieval of images is a topic of growing interest given us multiple applications. One kind of images that have not yet been dealt with satisfactorily are the so-called Remote Sensing Images. Remote Sensing Images (RSI) are a especial type of image, created by combination of sensoring on different spectral bands . This work deals with the problem of content-based retrieval of Remote Sensiong Images(RSI). It uses the image retrieval approach based on content representation models from image processing area. This work presents a content-based image retrieval model for RSI, based on three main features: patterns of color and texture as basic query concept, use of multiple content representation modelsanda feedback Televance machanism. The main contributions os these work are: (1) an analysis of content-based RSI pro,. blems; (2) a proposal of a model for RSI retrieval; (3) a proposal of model and metric for similarity measure; (4) a proposal of algorithm for processing of content-based queriesDoutoradoDoutor em Ciência da Computaçã