Dominant color correlogram descriptor for content-based image retrieval

Atoany Fierro-Radilla; Karina Perez-Daniel; Mariko Nakano-Miyatake; Jenny Benois

doi:10.1117/12.2179020

4 March 2015 Dominant color correlogram descriptor for content-based image retrieval

Atoany Fierro-Radilla, Karina Perez-Daniel, Mariko Nakano-Miyatake, Jenny Benois

Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94431I (2015) https://doi.org/10.1117/12.2179020
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China

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.

Citation Download Citation

Atoany Fierro-Radilla, Karina Perez-Daniel, Mariko Nakano-Miyatake, and Jenny Benois "Dominant color correlogram descriptor for content-based image retrieval", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431I (4 March 2015); https://doi.org/10.1117/12.2179020

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available