Texture Image Retrieval Using Novel Non-separable Filter Banks Based on Centrally Symmetric Matrices

Zhenyu He, Xinge You, Yuan Yan Tang, Patrick Wang, Yun Xue

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

8 Citations (Scopus)


Though millions of images are stored in a large digital image library today, the user can not access or make full use of these image information unless the digital image library is well organized in order to allow efficient browsing, searching and retrieval. Thus, research in image retrieval has been an active discipline since 70’s last century. Image retrieval is a typical problem of pattern recognition, consisting of two parts: extracting features (EF) and similarity measurement (SM). In this paper, we develop new non-separable filter banks based on the centrally symmetric matrixes, and apply them to extract the features of texture images. Compared to tensor product wavelets, our new filter banks can capture more directional texture information, which is helpful for texture image retrieval. Experiments show that our novel non-separable filter banks are satisfiable and achieve a better retrieval effectiveness than Daubechies wavelets.
Original languageEnglish
Title of host publication18th International Conference on Pattern Recognition (ICPR'06)
EditorsY.Y. Tang, S.P. Wang, G. Lorette, D.S. Yeung, H. Yan
Number of pages4
ISBN (Print)0769525210
Publication statusPublished - 20 Aug 2006
Event18th International Conference on Pattern Recognition (ICPR'06) - Hong Kong, China
Duration: 20 Aug 200624 Aug 2006

Publication series

NameInternational Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference18th International Conference on Pattern Recognition (ICPR'06)

User-Defined Keywords

  • Image retrieval
  • Filter bank
  • Symmetric matrices
  • Digital images
  • Software libraries
  • Information retrieval
  • Data mining
  • Feature extraction
  • Pattern recognition
  • Samarium


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