Chinese Textual Image Compression Based on Multi-feature Extraction

Abstract

Abstract: Based on the characteristics of Chinese textual images, an improved compression algorithm MC-JBIG2 is developed. First, multilevel feature data of Chinese characters are extracted; then the data are used in a cascaded clustering algorithm to replace the pattern matching procedure of JBIG2. Experiment results show MC-JBIG2 is highly efficient and can improve compression ratio in the criterion of not involving substitution errors. Despite designed for Chinese textual images, MC-JBIG2 can also improve compression ratio of English textual images.

Key words: text( textual) image compression, pattern matching, clustering, JBIG2

摘要： 针对中文文本图像的特点, 提出了一种改进的压缩算法MC-JBIG2 。该算法首先对中文字符进行多级特征提取, 然后将提取到的特征数据用于一个级联聚类算法中以替代传统 JBIG2 中的模式匹配过程。实验表明, MC-JBIG2 改进了传统 JBIG2 算法对中文文本图像压缩的不足, 能够保证在内容无损的情况下提高对中文文本图像的压缩率, 同时该算法对英文本图像的压缩也有一定的改进。

关键词: 文本图像压缩, 模式匹配, 聚类, JBIG2

CLC Number:

TP391

HU Kui,TANG Zhi,GAO Liangcai. Chinese Textual Image Compression Based on Multi-feature Extraction[J]. Acta Scientiarum Naturalium Universitatis Pekinensis.

胡奎,汤帜,高良才. 基于多级特征提取的中文文本图像压缩算法[J]. 北京大学学报（自然科学版）.

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URL: https://xbna.pku.edu.cn/EN/

https://xbna.pku.edu.cn/EN/Y2010/V46/I6/914

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Chinese Textual Image Compression Based on Multi-feature Extraction

基于多级特征提取的中文文本图像压缩算法

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