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Efficient Wavelet-Based Image Retrieval Using Coarse Segmentation and Fine Region Feature Extraction
Yongqing SUN Shinji OZAWA
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E88-D
No.5
pp.1021-1030 Publication Date: 2005/05/01 Online ISSN:
DOI: 10.1093/ietisy/e88-d.5.1021 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Image Processing and Video Processing Keyword: region-based image retrieval, region description, fine region feature vector, wavelet transform,
Full Text: PDF(1010.2KB)>>
Summary:
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.
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