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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44229

Title: Similarity Retrieval in Image Database by Boosted Common Shape Features among Query Images
Authors: Jiann-Jone Chen
Cheng-Yi Liu
YeaShuan Huang
Jun-Wei Hsieh
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Date: 2001
Issue Date: 2017-11-16T02:44:06Z
Publisher: IEEE Pacific-Rim Conf. on Multimedia
Abstract: Abstract:We present an on-line query mechanism for shape-based similarity retrieval of image databases. It successively boosts salient common features among query samples, in which weak classifiers are tuned and selected to contribute to a final strong classifier. The similarity between two shape samples was measured in statistic space of features, through which relative instead of absolute similarity was targeted for visual information retrieval. Experiments of query by the boosted features on thirty thousand trademark images showed that the retrieved results meet visual similarity of shape very well. Only 5 – 7 boosted features out of 100 or more were enough to represent subjective recognition on shape similarity.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44229
Appears in Collections:[資訊工程學系] 演講及研討會

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