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A Robust Algorithm for Detection of Human Faces in Color Images

机译:彩色图像中人脸检测的鲁棒算法

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摘要

In this paper, an efficient algorithm for detecting human faces in color images is proposed. The first step of our algorithm is to segment the possible skin-like regions in an image by using color information. One of the major problems of using skin color is that a face region may not be detected under poor or intense lighting conditions, or if the lighting conditions vary over the face region. Our approach considers the distribution of the color components of skin pixels under different illumination. This information can be used to identify skin color pixels reliably under different lighting conditions. The skin color regions are then clustered and verified as human face regions or not. In order to improve the reliability of detection, an eigenmask that has a large magnitude at the important facial features of a human face is devised. Experimental results show that this algorithm can detect human faces under different lighting conditions reliably.
机译:本文提出了一种有效的彩色图像人脸检测算法。我们算法的第一步是通过使用颜色信息来分割图像中可能的类皮肤区域。使用肤色的主要问题之一是,在不良或强烈的光照条件下,或者光照条件在整个面部区域变化时,可能无法检测到面部区域。我们的方法考虑了在不同光照下皮肤像素的颜色分量的分布。该信息可用于在不同照明条件下可靠地识别肤色像素。然后将肤色区域聚类并验证是否为人脸区域。为了提高检测的可靠性,设计了在人脸的重要面部特征处具有较大幅度的本征掩模。实验结果表明,该算法能够在不同光照条件下可靠地检测人脸。

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