Robust Pose Invariant Shape-based Hand Recognition

    Research output: Chapter in Book/Conference paperConference paper

    9 Citations (Scopus)

    Abstract

    This paper presents a novel technique for hand shape and appearance based personal identification and verification. It has two major building blocks. A segmentation block presents robust and fully automatic algorithms which are able to accurately segment the hand's palm and fingers irrespective of colour contrast between the fosreground and background. They achieve a consistent representation of the fingers and the palm regardless of their pose/orientation or the spaces between the fingers. In the feature extraction/matching block, the iterative closest point (ICP) algorithm is employed to align the images. Both shape and appearance based features are extracted and comparatively assessed. The modified Hausdorff distance and independent component analysis (ICA) algorithms are used for shape and appearance analysis. Identification and verification were performed using fusion strategies upon the similarity scores of the fingers and the palm. Experimental results show the proposed system exhibits an accuracy of over 98% in hand recognition and verification in a database consisting of 500 different subjects.
    Original languageEnglish
    Title of host publicationProceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA)
    Place of PublicationSingapore
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages281-286
    VolumeSingle
    ISBN (Print)9781424487554
    Publication statusPublished - 2011
    Event2011 6th IEEE Conference on Industrial Electronics and Applications - Beijing, China
    Duration: 21 Jun 201123 Jun 2011

    Conference

    Conference2011 6th IEEE Conference on Industrial Electronics and Applications
    CountryChina
    CityBeijing
    Period21/06/1123/06/11

    Fingerprint

    Palmprint recognition
    Independent component analysis
    Feature extraction
    Fusion reactions
    Color

    Cite this

    El-Sallam, A., Sohel, F., & Bennamoun, M. (2011). Robust Pose Invariant Shape-based Hand Recognition. In Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA) (Vol. Single, pp. 281-286). Singapore: IEEE, Institute of Electrical and Electronics Engineers.
    El-Sallam, Amar ; Sohel, Ferdous ; Bennamoun, Mohammed. / Robust Pose Invariant Shape-based Hand Recognition. Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA). Vol. Single Singapore : IEEE, Institute of Electrical and Electronics Engineers, 2011. pp. 281-286
    @inproceedings{84a4fae362e94250a4e5b4b9cab8647d,
    title = "Robust Pose Invariant Shape-based Hand Recognition",
    abstract = "This paper presents a novel technique for hand shape and appearance based personal identification and verification. It has two major building blocks. A segmentation block presents robust and fully automatic algorithms which are able to accurately segment the hand's palm and fingers irrespective of colour contrast between the fosreground and background. They achieve a consistent representation of the fingers and the palm regardless of their pose/orientation or the spaces between the fingers. In the feature extraction/matching block, the iterative closest point (ICP) algorithm is employed to align the images. Both shape and appearance based features are extracted and comparatively assessed. The modified Hausdorff distance and independent component analysis (ICA) algorithms are used for shape and appearance analysis. Identification and verification were performed using fusion strategies upon the similarity scores of the fingers and the palm. Experimental results show the proposed system exhibits an accuracy of over 98{\%} in hand recognition and verification in a database consisting of 500 different subjects.",
    author = "Amar El-Sallam and Ferdous Sohel and Mohammed Bennamoun",
    year = "2011",
    language = "English",
    isbn = "9781424487554",
    volume = "Single",
    pages = "281--286",
    booktitle = "Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA)",
    publisher = "IEEE, Institute of Electrical and Electronics Engineers",
    address = "United States",

    }

    El-Sallam, A, Sohel, F & Bennamoun, M 2011, Robust Pose Invariant Shape-based Hand Recognition. in Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA). vol. Single, IEEE, Institute of Electrical and Electronics Engineers, Singapore, pp. 281-286, 2011 6th IEEE Conference on Industrial Electronics and Applications, Beijing, China, 21/06/11.

    Robust Pose Invariant Shape-based Hand Recognition. / El-Sallam, Amar; Sohel, Ferdous; Bennamoun, Mohammed.

    Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA). Vol. Single Singapore : IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 281-286.

    Research output: Chapter in Book/Conference paperConference paper

    TY - GEN

    T1 - Robust Pose Invariant Shape-based Hand Recognition

    AU - El-Sallam, Amar

    AU - Sohel, Ferdous

    AU - Bennamoun, Mohammed

    PY - 2011

    Y1 - 2011

    N2 - This paper presents a novel technique for hand shape and appearance based personal identification and verification. It has two major building blocks. A segmentation block presents robust and fully automatic algorithms which are able to accurately segment the hand's palm and fingers irrespective of colour contrast between the fosreground and background. They achieve a consistent representation of the fingers and the palm regardless of their pose/orientation or the spaces between the fingers. In the feature extraction/matching block, the iterative closest point (ICP) algorithm is employed to align the images. Both shape and appearance based features are extracted and comparatively assessed. The modified Hausdorff distance and independent component analysis (ICA) algorithms are used for shape and appearance analysis. Identification and verification were performed using fusion strategies upon the similarity scores of the fingers and the palm. Experimental results show the proposed system exhibits an accuracy of over 98% in hand recognition and verification in a database consisting of 500 different subjects.

    AB - This paper presents a novel technique for hand shape and appearance based personal identification and verification. It has two major building blocks. A segmentation block presents robust and fully automatic algorithms which are able to accurately segment the hand's palm and fingers irrespective of colour contrast between the fosreground and background. They achieve a consistent representation of the fingers and the palm regardless of their pose/orientation or the spaces between the fingers. In the feature extraction/matching block, the iterative closest point (ICP) algorithm is employed to align the images. Both shape and appearance based features are extracted and comparatively assessed. The modified Hausdorff distance and independent component analysis (ICA) algorithms are used for shape and appearance analysis. Identification and verification were performed using fusion strategies upon the similarity scores of the fingers and the palm. Experimental results show the proposed system exhibits an accuracy of over 98% in hand recognition and verification in a database consisting of 500 different subjects.

    M3 - Conference paper

    SN - 9781424487554

    VL - Single

    SP - 281

    EP - 286

    BT - Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA)

    PB - IEEE, Institute of Electrical and Electronics Engineers

    CY - Singapore

    ER -

    El-Sallam A, Sohel F, Bennamoun M. Robust Pose Invariant Shape-based Hand Recognition. In Proceeding of the 2011 6TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA). Vol. Single. Singapore: IEEE, Institute of Electrical and Electronics Engineers. 2011. p. 281-286