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Proceedings Paper

Modeling the sample distribution for clustering OCR
Author(s): Thomas M. Breuel
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Paper Abstract

The paper re-examines a well-known technique in OCR, recognition by clustering followed by cryptanalysis, from a Bayesian perspective. The advantage of such techniques is that they are font-independent, but they appear not to have offered competitive performance with other pattern recognition techniques in the past. The analysis presented in this paper suggests an approach to OCR that is based on modeling the sample distribution as a mixture of Gaussians. Results suggest that such an approach may combine the advantages of cluster- based OCR with the performance of traditional classification algorithms.

Paper Details

Date Published: 21 December 2000
PDF: 8 pages
Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); doi: 10.1117/12.410858
Show Author Affiliations
Thomas M. Breuel, Xerox Palo Alto Research Ctr. (United States)


Published in SPIE Proceedings Vol. 4307:
Document Recognition and Retrieval VIII
Paul B. Kantor; Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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