Text-Transformed Image Classification Based on Data Compression

  • Nuo Zhang
  • Toshinori Watanabe
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 156)


Image data analysis technology occupies an important position in processing multimedia information. Due to the wide usage of digital images, automatic classification technology with high capacity is necessary for processing enormous number of digital images. In this paper, we propose an automatic classification technique which representing text-transformed image based on data compression. Images are first transformed into texts, which are then divided into segments and replaced by characters. Then, instead of using texts themselves, the similarity between compressibility vectors of texts are 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.


Segment Length Data Compression Nature Image Text Data Complex Property 
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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Graduate School of Information SystemsThe University of Electro-CommunicationsTokyoJapan

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