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Image representation and classification based on data compression

Published: 22 March 2010 Publication History

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.

References

[1]
Toshinori Watanabe, K. Sugawara. and H. Sugihara, "A new pattern representation scheme using data compression," IEEE Transactions on Pattern Analysis and Machhine Intelligence, 24(5):579--590, May 2002.
[2]
Weiming Hu, Ou Wu, Zhouyao Chen, Zhouyu Fu and S. Maybank, "Recognition of pornographic web pages by classifying texts and images," IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(6):1019--1034, Jun 2007.

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    cover image ACM Conferences
    SAC '10: Proceedings of the 2010 ACM Symposium on Applied Computing
    March 2010
    2712 pages
    ISBN:9781605586397
    DOI:10.1145/1774088
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    Publication History

    Published: 22 March 2010

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    Author Tags

    1. data compression
    2. data mining
    3. evaluation
    4. image classification
    5. image representation

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    SAC'10: The 2010 ACM Symposium on Applied Computing
    March 22 - 26, 2010
    Sierre, Switzerland

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    SAC '10 Paper Acceptance Rate 364 of 1,353 submissions, 27%;
    Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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