Efficient Wavelet-Based Image Retrieval Using Coarse Segmentation and Fine Region Feature Extraction

Authors:
Yongqing Sun;Shinji Ozawa
Affiliations:
The authors are with the Department of Information and Computer Science, Keio University, Yokohama-shi, 223--8522 Japan. E-mail: syq@ozawa.ics.keio.ac.jp;The authors are with the Department of Information and Computer Science, Keio University, Yokohama-shi, 223--8522 Japan. E-mail: syq@ozawa.ics.keio.ac.jp
Venue:
IEICE - Transactions on Information and Systems
Year:
2005

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Abstract

Semantic image segmentation and appropriate region content description are crucial issues for region-based image retrieval (RBIR). In this paper, a novel region-based image retrieval method is proposed, which performs fast coarse image segmentation and fine region feature extraction using the decomposition property of image wavelet transform. First, coarse image segmentation is conducted efficiently in the Low-Low(LL) frequency subband of image wavelet transform. Second, the feature vector of each segmented region is hierarchically extracted from all different wavelet frequency subbands, which captures the distinctive feature (e.g., semantic texture) inside one region finely. Experiment results show the efficiency and the effectiveness of the proposed method for region-based image retrieval.