Human Face Detection in Color Images Using HSV Color Histogram and WLD

2014 International Conference on Computational Intelligence and Communication Networks Pub Date : 2014-11-14 DOI:10.1109/CICN.2014.54

J. Das, Hiranmoy Roy

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引用次数: 10

Abstract

In this paper, a new algorithm is proposed for detecting human faces in color images and as well as for removing background from a single face color image. The proposed algorithm combines color histogram for skin color (in the HSV space), a threshold value of gray scale image to easily detect skin regions in a given image. Then, in order to reduce the number of non-face regions, we calculate the number of holes of these selected regions. If the value is less than a particular threshold, then the region is selected. Also, ratio of the height and width of the detected skin region is calculated to differentiate face and non-face regions. Finally, Weber Local Descriptor (WLD) is calculated for each selected regions and then, each regions are divided into equal size block and corresponding entropy values of each block are calculated and compared with training samples to get the Euclidian distance between them. If the distance value is in between a tested threshold values, then the region block is face, otherwise it is non-face. The proposed algorithm has been tested on various real images and its performance is quite satisfactory.

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基于HSV颜色直方图和WLD的彩色图像人脸检测

本文提出了一种新的彩色人脸检测算法，并对单幅彩色人脸图像进行背景去除。该算法结合了肤色直方图(HSV空间)和灰度图像的阈值，方便地检测给定图像中的皮肤区域。然后，为了减少非表面区域的数量，我们计算这些选定区域的孔数。如果该值小于特定阈值，则选择该区域。此外，计算被检测皮肤区域的高度和宽度的比值，以区分人脸和非人脸区域。最后，对选取的每个区域计算Weber局部描述子(WLD)，然后将每个区域划分为大小相等的块，计算每个块对应的熵值，并与训练样本进行比较，得到它们之间的欧几里得距离。如果距离值在被测阈值之间，则该区域块为面，否则为非面。该算法已在各种真实图像上进行了测试，取得了令人满意的效果。

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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来源期刊

2014 International Conference on Computational Intelligence and Communication Networks

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