• DocumentCode
    2255710
  • Title

    Harris feature vector descriptor

  • Author

    Wang, Xu-guang ; Su, Jie ; Cheng, Hai-yan

  • Author_Institution
    Dept. of Autom., North China Electr. Power Univ., Baoding, China
  • Volume
    1
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    512
  • Lastpage
    517
  • Abstract
    This paper defines a new image feature called Harris feature vector, which is able to describe the image gradient distribution in an effective way. By computing the mean and the standard deviation of the Harris feature vector in a local image region, novel descriptors are constructed for feature matching which are invariable to image rigid transformation and linear intensity change. Experimental evidence suggests that the novel descriptor for point matching has a good adaptability to slight view point changing, JPEG compression and nonlinear changing of intensity, besides, the descriptor for line matching performs well too.
  • Keywords
    data compression; feature extraction; gradient methods; image coding; image matching; Harris feature vector descriptor; JPEG compression; feature matching; image gradient distribution; image rigid transformation; linear intensity change; local image region; Cybernetics; Detectors; Feature extraction; Image coding; Machine learning; Transform coding; Vectors; Feature descriptor; Feature matching; HFV; Orthogonal transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5581008
  • Filename
    5581008