Paper
21 December 2000 Modeling the sample distribution for clustering OCR
Author Affiliations +
Proceedings Volume 4307, Document Recognition and Retrieval VIII; (2000) https://doi.org/10.1117/12.410858
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas M. Breuel "Modeling the sample distribution for clustering OCR", Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); https://doi.org/10.1117/12.410858
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Cited by 10 scholarly publications.
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KEYWORDS
Optical character recognition

Statistical modeling

Statistical analysis

Expectation maximization algorithms

Error analysis

Feature extraction

Image compression

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