彩色图像中的多人脸检测

T. Archana, T. Venugopal, M. P. Kumar
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引用次数: 7

摘要

面孔是传递身份的主要指标。人脸自动检测是一个有趣的研究领域。近二十年来,数字图像的人脸检测受到了人们的重视和关注,在各个领域都有广泛的应用。计算机化处理需要多种图像处理方法。提出了一种基于色基分割和形态学运算的人脸检测方法。该算法采用彩色平面提取、背景减法、阈值分割、形态学操作(如侵蚀和扩张)、滤波(避免误检)。然后进行粒子分析,只检测图像中的面部区域,而不检测身体的其他部分。利用视觉模块提取颜色平面,将RGB颜色空间转换为HSV、YCbCr等合适的颜色空间。该算法既可以检测图像中的单个人物,也可以检测图像中的多个人物。实验结果表明,该算法能够很好地检测人脸,准确率达到93%,即检测效率达到93%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple face detection in color images
Face is the primary index for imparting the identity. Automated face detection is one of the interesting field of research. Face detection of digital image has acquired much importance and interest in last two decades, which has applications in different fields. Computerizing the process needs many image processing methods. In this paper, a new face detection approach using color base segmentation and morphological operations is presented. The algorithm uses color plane extraction, background subtraction, thresholding, morphological operations (such as erosion and dilation), filtering (to avoid false detection). Then particle analysis is done to detect only the face area in the image and not the other parts of the body. The color planes are extracted using vision module the RGB color space is converted into suitable color space such as HSV and YCbCr. The algorithm can be used to detect both single as well as multiple persons in a image. Experimental results of the algorithm show that, it is good enough to detect the human faces with an accuracy of 93% i.e., the efficiency of the detection is up to 93%.
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