• DocumentCode
    657895
  • Title

    Feature Description Based on LBP and Order Pooling

  • Author

    Lingda Wu ; Wei Huang ; Yingmei Wei

  • Author_Institution
    Key Lab., Acad. of Equip., Beijing, China
  • fYear
    2013
  • fDate
    14-15 Sept. 2013
  • Firstpage
    213
  • Lastpage
    216
  • Abstract
    A novel local image descriptor named OCLBP(Order based Complete Local Binary Patterns) is proposed in this paper. It firstly extracts CLBP(Complete Local Binary Patterns) features pixel-by-pixel in the local image patch, and then pooled the CLBP features based on order relations of the pixel brightness in the patch. Specifically, the CLBP feature is based on CSLBP and adds the information of center pixel. The pattern number of the pixels is reduced compared to CSLBP. Furthermore, in order to better meet the scale invariance, the descriptors is extracted in multi-scales and the final descriptor is constructed by concatenating the histograms in multi-scales. The performance of the proposed descriptor is similar to the state-of-the-art descriptors SIFT and CSLBP in the condition of perspective transformation and light changes. In the condition of scaling, rotation, blurring, and JPEG compression, our descriptor has a better performance against the above descriptors using standard benchmarks.
  • Keywords
    feature extraction; statistical analysis; CLBP feature; JPEG compression condition; OCLBP image descriptor; blurring condition; center pixel information; complete local binary patterns; feature description; histogram concatenation; light changes; order based complete local binary patterns; order pooling; perspective transformation; pixel brightness; pixel-by-pixel feature extraction; rotation condition; scale invariance; scaling condition; Computer vision; Feature extraction; Histograms; Image sequences; Pattern recognition; Robustness; Vectors; Feature description; Feature extraction; Feature matching; LBP;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Virtual Reality and Visualization (ICVRV), 2013 International Conference on
  • Conference_Location
    Xi´an
  • Type

    conf

  • DOI
    10.1109/ICVRV.2013.40
  • Filename
    6689419