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Proceedings Paper

Context-based filtering for document image compression
Author(s): Eugene Jevgeni Ageenko; Pasi Franti
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Paper Abstract

Two statistical context-based filters are proposed for the enhancement of the binary document images for compression and recognition. The Simple Context Filter unconditionally changes the uncommon pixels in low information contexts, whereas the Gain-Loss Filter changes the pixels conditionally depending whether the gain in compression outweighs the loss of information. The evaluation methods and results with some traditional filtering methods are presented. The filtering methods alleviate the loss in compression performance caused by digitization noise while preserving the image quality measured as the OCR accuracy. The Gain-Loss Filter reaches approximately the compression limit estimated by the compression of the noiseless digital original.

Paper Details

Date Published: 22 December 1999
PDF: 10 pages
Proc. SPIE 3967, Document Recognition and Retrieval VII, (22 December 1999); doi: 10.1117/12.373513
Show Author Affiliations
Eugene Jevgeni Ageenko, Univ. of Joensuu (Finland)
Pasi Franti, Univ. of Joensuu (Finland)

Published in SPIE Proceedings Vol. 3967:
Document Recognition and Retrieval VII
Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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