A ROI image retrieval method based on CVAAO

Authors:
Yung-Kuan Chan;Yu-An Ho;Yi-Tung Liu;Rung-Ching Chen
Affiliations:
Department of Management Information Systems, National Chung Hsing University, No. 250, Kuokuang Road, Taichung 402, Taiwan, ROC;Department of Computer Science, National Chung Hsing University, No. 250, Kuokuang Road, Taichung 402, Taiwan, ROC;Department of Information Management, Chaoyang University of Technology, No. 168, Gifeng E. Road, Wufeng, Taichung County, Taiwan, ROC;Department of Information Management, Chaoyang University of Technology, No. 168, Gifeng E. Road, Wufeng, Taichung County, Taiwan, ROC
Venue:
Image and Vision Computing
Year:
2008

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Abstract

A novel image feature called color variances among adjacent objects (CVAAO) is proposed in this study. Characterizing the color variances between contiguous objects in an image, CVAAO can effectively describe the principal colors and texture distribution of the image and is insensitive to distortion and scale variations of images. Based on CVAAO, a CVAAO-based image retrieval method is constructed. When given a full image, the CVAAO-based image retrieval method delivers the database images most similar to the full image to the user. This paper also presents a CVAAO-based ROI image retrieval method. When given a clip, the CVAAO-based ROI image retrieval method submits to the user a database image containing a target region most similar to the clip. The experimental results show that the CVAAO-based ROI image retrieval method can offer impressive results in finding out the database images that meet user requirements.