Context-based filtering for document image compression

Eugene Jevgeni Ageenko; Pasi Franti

doi:10.1117/12.373513

22 December 1999 Context-based filtering for document image compression

Eugene Jevgeni Ageenko, Pasi Franti

Proceedings Volume 3967, Document Recognition and Retrieval VII; (1999) https://doi.org/10.1117/12.373513
Event: Electronic Imaging, 2000, San Jose, CA, United States

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.

Citation Download Citation

Eugene Jevgeni Ageenko and Pasi Franti "Context-based filtering for document image compression", Proc. SPIE 3967, Document Recognition and Retrieval VII, (22 December 1999); https://doi.org/10.1117/12.373513

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