基于知识的人脸检测和人脸特征提取方法与形态学图像处理相融合

S. Devadethan, Geevarghese Titus, S. Purushothaman
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引用次数: 16

摘要

从图像中检测人脸是一个非常困难的过程。影响检测过程的原因有很多,如光照条件、阴影、面部表情等。因此,人脸特征提取本身就成为一项艰巨的任务。为了提出一种有效的人脸特征提取方法,我们利用了鼻孔、眼睛、嘴唇等特征特征。在我们的方法中,我们假设正面图像是现成的。首先通过检测眼睛区域来检测面部区域。在对人脸区域进行检测后,提取鼻孔、眼角、嘴角等其他特征点。首先,通过寻找和验证可能的眼睛区域来获得眼睛对。在检测到眼睛区域后,使用眼睛之间的距离来寻找可能的人脸候选人。接下来,将人脸划分为不同的区域,并从相应的区域提取人脸特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face detection and facial feature extraction based on a fusion of knowledge based method and morphological image processing
Detection of human face from an image is a very difficult process. There are many reasons that affect the detection process such as lighting condition, shadows, facial expression etc. Thus facial feature extraction itself becomes a difficult task. In order to propose an efficient method for facial feature extraction, we used the characteristic features of nostrils, eyes lips etc. In our method we assume that frontal face image is readily available. At first face regions detected by detecting the eye regions. After detecting the face region other feature points such as nostril, corners of eyes, corners of lips etc are extracted. At first eye pairs are obtained by finding and verifying possible eye regions. After detecting the eye regions, the distance between the eyes is used to find a possible face candidate. Next, the face is divided into different regions and facial features are extracted from the corresponding regions.
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