• DocumentCode
    1861221
  • Title

    Ear recognition using a new local matching approach

  • Author

    Guo, Yimo ; Xu, Zhengguang

  • Author_Institution
    Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    289
  • Lastpage
    292
  • Abstract
    A new ear recognition approach, including a feature extraction method and the recognition framework, is presented in this paper. The proposed feature extraction method, called the local similarity binary pattern (LSBP), considers both the connectivity and similarity information in representation. In ear recognition, LSBP is combined with the local binary pattern (LBP) to represent the ear image. The concatenated histogram sequences encode more relationships among neighborhoods that are shown to be discriminative. To enhance efficient representation, cellular neural network is adopted to preprocess images, the function of which is to eliminate irrelevant information. From the experimental results conducted on the USTB ear database, the proposed approach outperforms some other well-known methods in terms of the recognition rate.
  • Keywords
    cellular neural nets; feature extraction; image matching; cellular neural network; concatenated histogram sequences; ear recognition; feature extraction; local matching approach; local similarity binary pattern; Cellular neural networks; Ear; Feature extraction; Histograms; Image recognition; Linear discriminant analysis; Pattern recognition; Principal component analysis; Shape; Statistical learning; Pattern recognition; feature extraction; image representations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1765-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2008.4711748
  • Filename
    4711748