• DocumentCode
    352404
  • Title

    Object classification using mixed color feature

  • Author

    Gao, Y.Y. ; Zhang, Y.J.

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • Volume
    6
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    2003
  • Abstract
    This paper proposes a color feature called mixed color feature (MCF) to describe the image contents in terms of human visual perception. Construction and distance measurement of MCF is interpreted in detail. A nonlinear quantizer is proposed to improve the efficiency of MCF. To evaluate the effect and accuracy of MCF in practice, a practical implementation of MCF in object classification is carried out. First, the major histogram (MH) is extracted from MCF as the basic feature in the classification processing; second, weighted nearest matching (WNM) is presented and applied to accomplish the classification. A comparison experiment is carried out and the results show the advantage and efficiency of the proposed method
  • Keywords
    image classification; image colour analysis; image matching; visual databases; distance measurement; human visual perception; image contents; major histogram; mixed color feature; nonlinear quantizer; object classification; weighted nearest matching; Color; Displays; Feature extraction; Histograms; Humans; Image representation; Image retrieval; Indexing; Printing; Visual perception;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-6293-4
  • Type

    conf

  • DOI
    10.1109/ICASSP.2000.859225
  • Filename
    859225