Facial feature extraction using genetic algorithm

G. Yen, Nethrie Nithianandan
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引用次数: 58

Abstract

An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and a genetic algorithm is applied to search for the best ellipse region match. In the feature extraction stage, the genetic algorithm is applied to extract the facial features, such as the eyes, nose and mouth, in the predefined sub regions. The simulation results validates that the proposed method is capable of automatically extracting features from various video images effectively under natural lighting environments and in the presence of certain amount of artificial noise and of multi-face oriented with angles.
基于遗传算法的人脸特征提取
提出了一种自动提取人脸特征的方法。该方法基于图像的边缘密度分布。在预处理阶段,将人脸近似为椭圆,利用遗传算法寻找最佳的椭圆区域匹配。在特征提取阶段,利用遗传算法提取预定义子区域内的眼、鼻、口等面部特征。仿真结果表明,该方法能够在自然光照环境下,在存在一定的人工噪声和多角度定向的情况下,有效地从各种视频图像中自动提取特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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