Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition

Lijun Yan, Jeng-Shyang Pan, Shu-Chuan Chu, Muhammad Khan

    Research output: Contribution to journalArticlepeer-review

    16 Citations (Scopus)

    Abstract

    A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results confirm that the recognition rate of the proposed system is higher than the other popular algorithms.

    Original languageEnglish
    Pages (from-to)232-235
    Number of pages4
    JournalFuture Generation Computer Systems
    Volume28
    Issue number1
    DOIs
    Publication statusPublished - Jan 2012

    Keywords

    • Directional filter banks
    • Face recognition
    • Two-dimensional linear discriminant analysis

    Fingerprint

    Dive into the research topics of 'Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition'. Together they form a unique fingerprint.

    Cite this