A Codebook Generation Algorithm for Document Image Compression
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%.
Cite
@article{arxiv.cs/0205029,
title = {A Codebook Generation Algorithm for Document Image Compression},
author = {Qin Zhang and John Danskin and Neal Young},
journal= {arXiv preprint arXiv:cs/0205029},
year = {2016}
}