Directional Discriminant Analysis Based on Nearest Feature Line

Lijun Yan, Shu-Chuan Chu, John Roddick, Jeng-Shyang Pan

    Research output: Contribution to conferencePaperpeer-review


    In this paper, two novel image feature extraction algorithms based on directional filter banks and nearest feature line are proposed, which are named Single Directional Feature Line Discriminant Analysis (SD-NFDA) and Multiple Directional Feature Discriminant Line Analysis (MD-NFDA). SD-NFDA and MD-NFDA extract not only the statistic feature of samples, but also the directionality feature. SD-NFDA and MD-NFDA can get higher average recognition rate with less running time than other nearest feature line based feature extraction algorithms. Experimental results confirm the advantages of SD-NFDA and MD-NFDA.

    Original languageEnglish
    Number of pages10
    Publication statusPublished - 27 Mar 2012
    Event4th Asian Conference -
    Duration: 19 Mar 2012 → …


    Conference4th Asian Conference
    Period19/03/12 → …


    • Directional Filter Bank
    • Feature Extraction
    • Nearest Feature Line


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