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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/77665

    Title: A Real Time Hand Gesture Recognition System Based on DFT and SVM
    Authors: Hsieh, Ching-tang;Yeh, Cheng-hsiang;Hung, Kuo-ming;Chen, Ting-wen;Ke, Chin-yen
    Contributors: 淡江大學電機工程學系
    Keywords: Camshift;BEA;SVM;Hand Gesture Recognition
    Date: 2012-06
    Issue Date: 2012-06-30 22:33:00 (UTC+8)
    Publisher: Advanced Institute of Convergence Information Technology
    Abstract: Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture
    recognition algorithm comprises four main steps. First use Camshift algorithm to track skin color after closing process. Second,in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.
    Relation: Information Science and Digital Content Technology (ICIDT), 2012 8th International Conference on, pp.490-494
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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