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Information Technology Journal
  Year: 2012 | Volume: 11 | Issue: 5 | Page No.: 626-631
DOI: 10.3923/itj.2012.626.631
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Image Retrieval Based on Topological Features of Gray-level Co-occurrence Networks

Zheng-Liang Huang, Shi-Ze Guo and Zhe-Ming Lu

This study presents to construct special networks from images and then apply their topological properties to image retrieval. Each input color image is divided into three separate gray-level images in the RGB space. For each gray-level image, we view the 256 gray-levels as nodes and construct the Horizontal Gray-level Co-occurrence Network (HGCN) and Vertical Gray-level Co-occurrence Network (VGCN) by counting the number of horizontal and vertical occurrences for each possible gray-level pair. Based on the obtained six directed weighted networks HGCN_R/G/B and VGCN_R/G/B, we extract their topological features including in-degrees, out-degrees, in-strengths and out-strengths for image retrieval. Simulation results demonstrate the superiority of our features to some existing features in terms of P-R curve.
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How to cite this article:

Zheng-Liang Huang, Shi-Ze Guo and Zhe-Ming Lu, 2012. Image Retrieval Based on Topological Features of Gray-level Co-occurrence Networks. Information Technology Journal, 11: 626-631.

DOI: 10.3923/itj.2012.626.631






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