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Region-based Image Retrieval Algorithm Using Image Segmentation and Multi-Feature  

Noh, Jin-Soo (Chosun University, Electronics & Information Engineering College, Dept. of Electronics Eng.)
Rhee, Kang-Hyeon (Chosun University, Electronics & Information Engineering College, Dept. of Electronics Eng.)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.46, no.3, 2009 , pp. 57-63 More about this Journal
Abstract
The rapid growth of computer-based image database, necessity of a system that can manage an image information is increasing. This paper presents a region-based image retrieval method using the combination of color(autocorrelogram), texture(CWT moments) and shape(Hu invariant moments) features. As a color feature, a color autocorrelogram is chosen by extracting from the hue and saturation components of a color image(HSV). As a texture, shape and position feature are extracted from the value component. For efficient similarity confutation, the extracted features(color autocorrelogram, Hu invariant moments, and CWT moments) are combined and then precision and recall are measured. Experiment results for Corel and VisTex DBs show that the proposed image retrieval algorithm has 94.8% Precision, 90.7% recall and can successfully apply to image retrieval system.
Keywords
Image Retrieval; Color Autocorrelogram; Hu Invariant Moments; Active Contour; CWT; BDIP;
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