Image retrieval based on multi-texton histogram

Guang Hai Liu, Lei Zhang, Ying Kun Hou, Zuo Yong Li, Jing Yu Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

253 Citations (Scopus)

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 15 000 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. Crown
Original languageEnglish
Pages (from-to)2380-2389
Number of pages10
JournalPattern Recognition
Volume43
Issue number7
DOIs
Publication statusPublished - 1 Jul 2010

Keywords

  • Image retrieval
  • Multi-texton histogram
  • Texton detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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