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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/64326

    Title: 利用模糊最近特徵線轉換做人臉辨識;Face Recognition Using Fuzzy Nearest
    Authors: 涂麗玉;Tu,Li-Yu
    Contributors: 資訊工程學系在職專班
    Keywords: 最近特徵線;模糊理論;NFLE;Fuzzy
    Date: 2014-03-19
    Issue Date: 2014-06-19 14:06:55 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 最近特徵線轉換 (Nearest Feature Line Embedding, NFLE),是以
    究中,NFLE 已在實驗中顯示出它在人臉辨識上有不錯的效果,然而
    分。因此在本研究中,我們提出了 Fuzzy NFLE,利用加權式歐式距
    驗,實驗結果顯示 Fuzzy NFLE 辨識率可優於 NFLE。; Nearest Feature Line Embedding (NFLE) is a feature space transformation algorithm whose covariance matrix is obtained based on Nearest Feature Line. In previous studies, NFLE has successfully demonstrated its capability in face recognition However, the contribution of each training sample cannot be precisely extracted because NFLE is obtained based on Euclidean distance. To remedy this problem, fuzzy NFLE is introduced in this thesis. In our work, Fuzzy NFLE uses distance to evaluate each sample by assigning greater weight to closer sample in order to fully utilize the discriminative information of each sample with an eye to increasing feature space transfer capability. Experimental results demonstrate that the face recognition rate of Fuzzy NFLE performs better than NFLE.
    Appears in Collections:[資訊工程學系碩士在職專班 ] 博碩士論文

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