A New and Effective Image Retrieval Method Based on Combined Features

Authors:
Pengyu Liu;Kebin Jia;Zhuozheng Wang;Zhuoyi Lv
Affiliations:
Beijing University of Technology, China;Beijing University of Technology, China;Beijing University of Technology, China;Beijing University of Technology, China
Venue:
ICIG '07 Proceedings of the Fourth International Conference on Image and Graphics
Year:
2007

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Abstract

In CBIR (Content-based Image Retrieval), image has various inherent features which reflect its content such as color, texture, shape, spatial relationship features etc. How to organize and utilize these features effectively and improve the retrieval performance is a valuable research topic. One of the key issues in image retrieval based on combined features is how to assign weight to different features. An image retrieval method combined color and texture features is proposed in this paper. According to image texture characteristic, a kind of image feature statistic is defined. By using feature weight assignment operators designed here, the method can assign weight to color and texture features according to image content adaptively and realize image retrieval based on combined image features. The experiment results show that this method is more efficiently than those traditional CBIR methods based on single visual feature or simple linear combined low-level visual features of fixed weight.