Derivative Variation Pattern for Illumination-Invariant Image Representation

M. Tavakolian, F. Hajati, Ajmal Mian, Y. Gao, S. Gheisari

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    This paper presents a novel image descriptor called Derivative Variation Pattern (DVP) and its application to face and palmprint recognition. DVP captures image variations in both the frequency and the spatial domains. The effects of uncontrolled illumination are compensated in the frequency domain by discarding the illumination affected frequencies. Image pixels are encoded as binary patterns based on the higher-order spatial derivatives computed in the spatial domain. The proposed descriptor was evaluated on the Extended Yale-B and FERET face databases, and the PolyU palmprint database. Experimental results demonstrate the effectiveness of the DVP descriptor in both the face and the palmprint recognition tasks under uncontrolled illuminations.
    Original languageEnglish
    Title of host publicationProceedings of 20th IEEE International Conference on Image Processing (ICIP), 2013
    Place of PublicationAustralia
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    ISBN (Print)9781479923410
    Publication statusPublished - Sept 2013
    Event2013 IEEE International Conference on Image Processing - Melbourne, Australia, Melbourne, Australia
    Duration: 15 Sept 201318 Sept 2013
    Conference number: 20th


    Conference2013 IEEE International Conference on Image Processing
    Abbreviated titleICIP 2013


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