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Proceedings Paper

Modeling hierarchical structure of images with stochastic grammars
Author(s): Wiley Wang; Tak-Shing Wong; Ilya Pollak; Charles A. Bouman; Mary P. Harper
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Paper Abstract

We construct a hierarchical image grammar model based on stochastic grammars and apply it to document images. An efficient maximum a posteriori probability estimation algorithm for this model produces accurate segmentations of document images and classifications of image parts.

Paper Details

Date Published: 2 February 2006
PDF: 5 pages
Proc. SPIE 6065, Computational Imaging IV, 606502 (2 February 2006); doi: 10.1117/12.655207
Show Author Affiliations
Wiley Wang, Purdue Univ. (United States)
Tak-Shing Wong, Purdue Univ. (United States)
Ilya Pollak, Purdue Univ. (United States)
Charles A. Bouman, Purdue Univ. (United States)
Mary P. Harper, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 6065:
Computational Imaging IV
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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