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Proceedings Paper

Dominant color correlogram descriptor for content-based image retrieval
Author(s): Atoany Fierro-Radilla; Karina Perez-Daniel; Mariko Nakano-Miyatake; Jenny Benois
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Paper Abstract

Content-based image retrieval (CBIR) has become an interesting and urgent research topic due to the increase of necessity of indexing and classification of multimedia content in large databases. The low level visual descriptors, such as color-based, texture-based and shape-based descriptors, have been used for the CBIR task. In this paper we propose a color-based descriptor which describes well image contents, integrating both global feature provided by dominant color and local features provided by color correlogram. The performance of the proposed descriptor, called Dominant Color Correlogram descriptor (DCCD), is evaluated comparing with some MPEG-7 visual descriptors and other color-based descriptors reported in the literature, using two image datasets with different size and contents. The performance of the proposed descriptor is assessed using three different metrics commonly used in image retrieval task, which are ARP (Average Retrieval Precision), ARR (Average Retrieval Rate) and ANMRR (Average Normalized Modified Retrieval Rank). Also precision-recall curves are provided to show a better performance of the proposed descriptor compared with other color-based descriptors.

Paper Details

Date Published: 4 March 2015
PDF: 7 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431I (4 March 2015); doi: 10.1117/12.2179020
Show Author Affiliations
Atoany Fierro-Radilla, Instituto Politécnico Nacional (Mexico)
Karina Perez-Daniel, Instituto Politécnico Nacional (Mexico)
Mariko Nakano-Miyatake, Instituto Politécnico Nacional (Mexico)
Jenny Benois, LaBRI, Univ. Bordeaux I (France)

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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