• DocumentCode
    3270584
  • Title

    Subregion based local descriptor

  • Author

    Xiaojie Dong ; Erqi Liu ; Jie Yang

  • Author_Institution
    Inst. of Image Process. & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China
  • fYear
    2013
  • fDate
    15-18 Sept. 2013
  • Firstpage
    250
  • Lastpage
    254
  • Abstract
    A novel distinctive descriptor named MSOGH is proposed, which is able to well represent the interest region and is robust to photometric transformations and geometric transformations. According to intensity order, subregions are firstly constructed. Then feature descriptor of the subregion is computed by point permutation of the sample points in each subregion. Finally, feature descriptor of the region is formed by concatenating all subregion feature descriptors. The discriminative power of the proposed descriptor is compared with 5 major existing region descriptors (MROGH, SIFT, GLOH, PCA-SIFT and spin images). Extensive experimental results show that the proposed descriptor achieves better performance than state-of-the-art descriptors.
  • Keywords
    feature extraction; image representation; GLOH; MROGH; MSOGH; PCA-SIFT; geometric transformations; intensity order; interest region representation; photometric transformations; point permutation; spin images; subregion based local descriptor; subregion feature descriptor; Color; Detectors; Feature extraction; Histograms; Robustness; Standards; Vectors; Image Matching; Local Descriptor; Performance Evaluation; Subregion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2013 20th IEEE International Conference on
  • Conference_Location
    Melbourne, VIC
  • Type

    conf

  • DOI
    10.1109/ICIP.2013.6738052
  • Filename
    6738052