Topological multi-contour decomposition for image analysis and image retrieval

Authors:
Odemir Martinez Bruno;Luis Gustavo Nonato;Mario Augusto Pazoti;Joao Batista Neto
Affiliations:
Instituto de Ciências Matemáticas e de Computação, Unversidade de São Paulo, Brazil;Instituto de Ciências Matemáticas e de Computação, Unversidade de São Paulo, Brazil;Instituto de Ciências Matemáticas e de Computação, Unversidade de São Paulo, Brazil;Instituto de Ciências Matemáticas e de Computação, Unversidade de São Paulo, Brazil
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power.