Compression of text images by soft pattern matching

Image analysis – Image compression or coding – Predictive coding

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341107, 382232, G06K 936, G06K 946, H03M 700

Patent

active

057518599

ABSTRACT:
Bilevel textual images are compressed by segmenting the image into marks (401) and then coding each mark using a soft pattern matching method. Each mark is compared (403) with the marks in a library of marks and if an acceptable match is found (404), the index of the matching mark is coded (412). Each pixel in a current mark is then coded using a statistical coder that codes each pixel based on the value of the pixel and a set of probabilities of all sample values based on a context that consists of pixels in the current mark and pixels in the matching mark (414, 415, 416, 417). In order to reduce the overall bit count of the image, pixels which color-reversed (706, 709) prior to coding, if so doing will not perceptibly alter a reconstructed image (708). If a matching mark is not found among the marks in the library, each pixel in the mark is coded using a statistical coder using a context of pixels in the non-matching mark (406, 407, 408, 409, 410). Again, pixels which are poorly predicted (721) are color-reversed (722, 725) prior to coding if the reversed pixels will not perceptibly alter the image (724).

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I. H. Witten et al., Managing Gigabytes: Compressing and Indexing Documents and Images, Chapter 7, Van Nostrand Reinhold, New York, 1994.
E. Mohiuddin et al., "Lossless Binary Image Compression Based on Pattern Matching", Proc. Intl. Conf. on Computers, Systems & Signal Processing, Bangalore, India. 1984, pp. 447-451.
R. N. Ascher et al., "A Means for Achieving a High Degree of Compaction on Scan-Digitized Printed Text", IEEE Trans. Comput. C-23, Nov. 1974, pp. 1174-1179.

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