A new approach for finding face features in color images

A. Popov, D. Dimitrova
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引用次数: 3

Abstract

This paper considers the problem of finding facial features in frontal color images by offering a method for efficient detection. For a given image, our method firstly detects the skin regions on by color segmentation. This segmentation is performed in a 2D projection of the selected color space (HSV, YES, YCrCb or normalized RGB). After that face candidates are found. Then we apply fuzzy mathematical morphology methods to locate precisely the right eyebrow (if exists). Thus we obtain a meaningful feature. A computer implementation in MATLAB is made for experimentation. The visual results of the experiments show the plausibility of proposed techniques.
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彩色图像中人脸特征的一种新方法
本文研究了正面彩色图像中人脸特征的识别问题,提出了一种有效的人脸识别方法。对于给定的图像,我们的方法首先通过颜色分割来检测皮肤区域。这种分割是在所选颜色空间(HSV, YES, YCrCb或标准化RGB)的2D投影中执行的。之后,面孔候选人被找到。然后应用模糊数学形态学方法精确定位右眉(如果存在)。这样我们就得到了一个有意义的特征。并在MATLAB中进行了计算机实现。实验的可视化结果表明了所提出技术的可行性。
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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