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A Codebook Generation Algorithm for Document Image Compression

Qin Zhang·John Danskin·Neal Young
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Abstract

Pattern-matching-based document-compression systems (e.g. for faxing) rely on finding a small set of patterns that can be used to represent all of the ink in the document. Finding an optimal set of patterns is NP-hard; previous compression schemes have resorted to heuristics. This paper describes an extension of the cross-entropy approach, used previously for measuring pattern similarity, to this problem. This approach reduces the problem to a k-medians problem, for which the paper gives a new algorithm with a provably good performance guarantee. In comparison to previous heuristics (First Fit, with and without generalized Lloyd's/k-means postprocessing steps), the new algorithm generates a better codebook, resulting in an overall improvement in compression performance of almost 17%.

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Qin Zhang, John Danskin, Neal Young. 2002-05-17. A Codebook Generation Algorithm for Document Image Compression. https://doi.org/10.1109/dcc.1997.582053

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