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Context-based filtering for document image compression

Identifieur interne : 001E40 ( Main/Exploration ); précédent : 001E39; suivant : 001E41

Context-based filtering for document image compression

Auteurs : E. Ageenko [Finlande] ; P. Fr Nti [Finlande]

Source :

RBID : Pascal:01-0027683

Descripteurs français

English descriptors

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.


Affiliations:


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Le document en format XML

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<term>Reconnaissance optique caractère</term>
<term>Compression</term>
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<div type="abstract" xml:lang="en">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.</div>
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