Wavelet-based personal identification

S. Takano, K. Niijima, K. Kuzume

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    This work presents a personal identification system based on the learning of the lifting dyadic wavelet filters. Our system consists of face learning, detection, and identification processes. In the learning process, free parameters in the lifting filters are determined so as to capture a facial part. Our face detection method is performed by applying the learned filters to each of the video frames. A person whose face is detected in a maximum number of frames is identified as a target person. In simulation, it is shown that our personal identification algorithm is fast and accurate.

    Original languageEnglish
    Title of host publicationProceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages215-218
    Number of pages4
    ISBN (Electronic)0780382927, 9780780382923
    DOIs
    Publication statusPublished - 2003
    Event3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003 - Darmstadt, Germany
    Duration: Dec 14 2003Dec 17 2003

    Publication series

    NameProceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003

    Other

    Other3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
    Country/TerritoryGermany
    CityDarmstadt
    Period12/14/0312/17/03

    All Science Journal Classification (ASJC) codes

    • Signal Processing

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