Face Detection Method Based on a New Nonlinear Transformation of Color Spaces

Zhengzhen Zhang, Yuexiang Shi
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引用次数: 6

Abstract

In this paper, against Hsu R L skin tone detection algorithm, which has high missing detection ratio when the facial brightness of an image is high, we introduce a new nonlinear transformation method of the YCb "Cr" color skin space, which is the color segmentation of the human face for regional analysis and extraction; Then implement image rotation and template matching. Experimental results indicate that when the facial brightness of an image is high, the new proposed nonlinear color space conversion algorithm based on YCbCr color space is better than the simple method, which wipes off the effect of the brightness directly, and Hsu R L skin detection algorithm. The series of experimental results demonstrate clearly that our new method has a higher detection ratio on high bright facial images, and can drop the false or missing detection ratio on high luminance images. Besides, we have more detailed testing results on the eyes, eyebrows, mouth and other parts.
基于一种新的非线性色彩空间变换的人脸检测方法
本文针对Hsu R L肤色检测算法在人脸亮度较高时缺失检测率较高的问题,提出了一种新的YCb“Cr”色肤色空间非线性变换方法,即对人脸的颜色分割进行区域分析和提取;然后实现图像旋转和模板匹配。实验结果表明,当图像的面部亮度较高时,本文提出的基于YCbCr色彩空间的非线性色彩空间转换算法优于直接抹去亮度影响的简单方法和Hsu R L皮肤检测算法。一系列实验结果表明,该方法对高亮度人脸图像具有较高的检测率,并且可以降低高亮度人脸图像的误检率或漏检率。此外,我们对眼睛、眉毛、嘴巴等部位有更详细的检测结果。
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