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Proceedings Paper

Binarization of camera-captured document using A MAP approach
Author(s): Xujun Peng; Srirangaraj Setlur; Venu Govindaraju; Ramachandrula Sitaram
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Paper Abstract

Document binarization is one of the initial and critical steps for many document analysis systems. Nowadays, with the success and popularity of hand-held devices, large efforts are motivated to convert documents into digital format by using hand-held cameras. In this paper, we propose a Bayesian based maximum a posteriori (MAP) estimation algorithm to binarize the camera-captured document images. A novel adaptive segmentation surface estimation and normalization method is proposed as the preprocessing step in our work and followed by a Markov Random Field based refine procedure to remove noises and smooth binarized result. Experimental results show that our method has better performance than other algorithms on bad or uneven illumination document images.

Paper Details

Date Published: 24 January 2011
PDF: 8 pages
Proc. SPIE 7874, Document Recognition and Retrieval XVIII, 78740R (24 January 2011); doi: 10.1117/12.874091
Show Author Affiliations
Xujun Peng, Univ. at Buffalo (United States)
Srirangaraj Setlur, Univ. at Buffalo (United States)
Venu Govindaraju, Univ. at Buffalo (United States)
Ramachandrula Sitaram, Hewlett-Packard Labs. India (India)

Published in SPIE Proceedings Vol. 7874:
Document Recognition and Retrieval XVIII
Gady Agam; Christian Viard-Gaudin, Editor(s)

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