Image representation and classification based on data compression

Authors:
Nuo Zhang;Toshinori Watanabe
Affiliations:
The University of Electro-Communications, Chofu-shi, Tokyo, Japan;The University of Electro-Communications, Chofu-shi, Tokyo, Japan
Venue:
Proceedings of the 2010 ACM Symposium on Applied Computing
Year:
2010

Citing 2
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Abstract

With the development of the information technology, the number of different electronic information has been increased rapidly. In which, for enormous number of digital images the demand of automatic classification technology exceeded human processing capacity. As an automatic classification technique, representing and classifying text-transformed image based on data compression is proposed in this paper. In the step of transforming image into text, image is divided into segments which are replaced as characters. Then, the similarity between compressibility vectors is used in the classification step. In which, we focus on the compressibility of the text string. Finally, the effectivity of the proposed method is verified in our experiments.