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Proceedings Paper

Word image retrieval using binary features
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Paper Abstract

Existing word image retrieval algorithms suffer from either low retrieval precision or high computation complexity. We present an effective and efficient approach for word image matching by using gradient-based binary features. Experiments over a large database of handwritten word images show that the proposed approach consistently outperforms the existing best handwritten word image retrieval algorithm. Dynamic Time Warping (DTW) with profile-based shape features. Not only does the proposed approach have much higher retrieval accuracy, but also it is 893 times faster than DTW.

Paper Details

Date Published: 15 December 2003
PDF: 9 pages
Proc. SPIE 5296, Document Recognition and Retrieval XI, (15 December 2003); doi: 10.1117/12.523968
Show Author Affiliations
Bin Zhang, Univ. of California/Los Angeles (United States)
Sargur N. Srihari, Univ. at Buffalo (United States)
Chen Huang, Univ. at Buffalo (United States)

Published in SPIE Proceedings Vol. 5296:
Document Recognition and Retrieval XI
Elisa H. Barney Smith; Jianying Hu; James Allan, Editor(s)

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