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    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/45289

    題名: Classification of Age Groups Based on Facial Features
    作者: 洪文斌;Horng, Wen-bing;李正平;Lee, Cheng-ping;陳俊文;Chen, Chun-wen
    貢獻者: 淡江大學資訊工程學系
    關鍵詞: Age Classification;Facial Feature Extraction;Neural Network
    日期: 2001-09-01
    上傳時間: 2010-03-26 18:55:55 (UTC+8)
    出版者: 淡江大學
    摘要: An age group classification system for gray-scale facial images is proposed in this paper. Four age groups, including babies, young adults, middle-aged adults, and old adults, are used in the classification system. The process of the system is divided into three phases: location, feature extraction, and age classification. Based on the symmetry of human faces and the variation of gray levels, the positions of eyes, noses, and mouths could be located by applying the Sobel edge operator and region labeling. Two geometric features and three wrinkle features from a facial image are then obtained. Finally, two back-propagation neural networks are constructed for classification. The first one employs the geometric features to distinguish whether the facial image is a baby. If it is not, then the second network uses the wrinkle features to classify the image into one of three adult groups. The proposed system is experimented with 230 facial images on a Pentium II 350 processor with 128 MB RAM.
    One half of the images are used for training and the other half for test. It takes 0.235 second to classify an image on an average. The identification rate achieves 90.52% for the training images and 81.58% for the test images, which is roughly close to human’s subjective justification.
    關聯: 淡江理工學刊=Tamkang journal of science and engineering 4(3), pp.183-192
    DOI: 10.6180/jase.2001.4.3.05
    顯示於類別:[資訊工程學系暨研究所] 期刊論文


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