勤益科大機構典藏:Item 987654321/5973
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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.lib.ncut.edu.tw/handle/987654321/5973


    题名: Fingertip Detection and Gesture Recognition Based on Contour Approximation,
    作者: Mei Wang, Jzau-Sheng Lin, Guo Qing Meng
    贡献者: 圖書館
    关键词: Color segmentation
    Hu's moments
    D–P algorithm
    contour approximation
    fingertip detection
    gesture recognition
    日期: 2015-11
    上传时间: 2016-10-20 15:58:27 (UTC+8)
    摘要: In this paper, a new recognition algorithm was developed based on the skin color model and the fingertip structure detection to improve the hand gesture recognition accuracy based on the traditional Hu's moment features. Firstly, the geometric features and the areas of skin were adopted to segment the skin region from the background. The Douglas–Peucker (D–P) algorithm was utilized to conduct the contour approximation to get a polygonal in the process of feature detection. Then the convexity point inspections were conducted in the polygonal. Secondly, we developed two rules for locating and numbering the fingertips. After that, we built a seven-dimensional feature vector. Finally, the hand gesture was recognized by using the distance matching criterion. The developed recognition algorithm improved the recognition accuracy by 2.7% compared with the traditional Hu's moment features. Additionally, it has good robustness in several manners such as shifting, plane rotation and scaling.
    關聯: International Journal of Pattern Recognition and Artificial Intelligence, 29(7)
    显示于类别:[資訊工程系(所)] 【資訊工程系所】期刊論文

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