Image retrieval based on multi-texton histogram

  • Authors:

  • Guang-Hai Liu;Lei Zhang;Ying-Kun Hou;Zuo-Yong Li;Jing-Yu Yang

  • Affiliations:

  • College of Computer Science and Information Technology, Guangxi Normal University, Guilin 541004, China;Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China;School of Information Science and Technology, Taishan University, Taian 271021, China;Department of Computer Science, Nanjing University of Science and Technology, Nanjing 210094, China;Department of Computer Science, Nanjing University of Science and Technology, Nanjing 210094, China

  • Venue:
  • Pattern Recognition
  • Year:
  • 2010

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Abstract

This paper presents a novel image feature representation method, called multi-texton histogram (MTH), for image retrieval. MTH integrates the advantages of co-occurrence matrix and histogram by representing the attribute of co-occurrence matrix using histogram. It can be considered as a generalized visual attribute descriptor but without any image segmentation or model training. The proposed MTH method is based on Julesz's textons theory, and it works directly on natural images as a shape descriptor. Meanwhile, it can be used as a color texture descriptor and leads to good performance. The proposed MTH method is extensively tested on the Corel dataset with 15000 natural images. The results demonstrate that it is much more efficient than representative image feature descriptors, such as the edge orientation auto-correlogram and the texton co-occurrence matrix. It has good discrimination power of color, texture and shape features.