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Color Image Face Detection: An Algorithm

机译:彩色图像人脸检测:一种算法

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摘要

This paper puts forward a solution for real-time color-imaged human face detection. The color face image in RGB space is first transformed into human face color models under r,g,b chrominance which can be used to differentiate skin pixels from non-skin pixels. The color image is then divided into grid units which are arranged as a rectangle, and the ratio of skin pixels to all pixels in the grid unit is computed and the grid unit is regarded as a skin unit the ratio of which is greater than a threshold. The adjoining skin units are concatenated. The resulting area is labeled as a candidate face if its shape is quasi-ellipse or quasi-rectangle complying with proper ratios. Otherwise the resulting area should be disregarded. Finally the gray image of face area is matched to the face template to discern the real face. This algorithm overcomes the influence of complex background upon face detection and obtains higher accuracy of detection. In particular, the time consumed by this algorithm is much less than the traditional template matching method. Under a resolution of 320*240 it can reach 10 frames per second and is suitable for real-time face detection system.
机译:提出了一种实时彩色图像人脸检测的解决方案。首先将RGB空间中的彩色人脸图像转换为r,g,b色度下的人脸颜色模型,该模型可用于区分皮肤像素与非皮肤像素。然后将彩色图像划分为排列为矩形的网格单元,并计算皮肤像素与该网格单元中所有像素的比率,并将该网格单元视为其比率大于阈值的皮肤单元。相邻的皮肤单元是串联的。如果结果区域的形状为符合适当比例的准椭圆或准矩形,则将其标记为候选面。否则应忽略所得区域。最后,将面部区域的灰色图像与面部模板进行匹配,以识别真实面部。该算法克服了复杂背景对人脸检测的影响,获得了较高的检测精度。特别是,该算法消耗的时间比传统的模板匹配方法要少得多。在320 * 240的分辨率下,它可以达到每秒10帧,适用于实时面部检测系统。

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