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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/73120

    Title: Face Detection Based on Skin Color Segmentation and Neural Network
    Authors: Lin, Hwei-jen;Wang, Shu-yi;Yen, Shwu-huey;Kao, Yang-ta
    Contributors: 淡江大學資訊工程學系
    Date: 2005-10
    Issue Date: 2011-10-24 11:31:34 (UTC+8)
    Publisher: IEEE中國類神經網路協會
    Abstract: This paper proposes a human face detection system based on skin color segmentation and neural networks. The system consists of several stages. First, the system searches for the regions where faces might exist by using skin color information and forms a so-called skin map. After performing noise removal and some morphological operations on the skin map, it utilizes the aspect ratio of a face to find out possible face blocks, and then eye detection is carried out within each possible face block. If an eye pair is detected in a possible face block, a region is cropped according to the location of the two eyes, which is called a face candidate; otherwise it is regarded as a non-face block. Finally, each of the face candidates is verified by a 3-layer back-propagation neural network. Experimental results show that the proposed system results in better performance than the other methods, in terms of correct detection rate and capacity of coping with the problems of lighting, scaling, rotation, and multiple faces.
    Relation: Neural Networks and Brain, 2005. ICNN&B '05. International Conference on, pp.1144-1149
    DOI: 10.1109/ICNNB.2005.1614818
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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