Improvement of haar feature based face detection incorporating human skin color analysis

M. A. S. Mollah, M. Akash, Mahtab Ahmed, M. Akhand
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引用次数: 3

Abstract

Face detection from a digital image or video stream is used often for various purposes. But sometimes a system detects an object or area as a face where there is no face at all. This paper presents a technique to reduce such wrong detection rate introducing human skin color (HSC) characteristic. The general property of human skin in RGB color space is that it possess R>G>B (i.e., red values are higher than green value and green value is higher than blue). In this study, such HSC property has been incorporated with the popular Haar feature based face detection (HFFD), to reduce wrong detection of faces. Proposed HFFD with HSC (HFFD-HSC) has been tested and compared with standard HFFD rigorously on a large number images with single and multiple faces. Experimental results identified the effectiveness of HSC incorporation in HFFD to improve its performance reducing wrong detection of faces.
基于haar特征的人脸检测改进及肤色分析
从数字图像或视频流中进行人脸检测通常用于各种目的。但有时系统会将根本没有人脸的物体或区域检测为人脸。本文介绍了一种引入人的肤色特征来降低错误检测率的方法。人体皮肤在RGB色彩空间中的一般性质是R>G>B(即红色值高于绿色值,绿色值高于蓝色值)。在本研究中,将这种HSC特性与流行的基于Haar特征的人脸检测(HFFD)相结合,以减少人脸的错误检测。本文在大量单面和多面图像上对HFFD (HFFD-HSC)和标准HFFD进行了严格的测试和比较。实验结果表明,在HFFD中加入HSC可以有效地提高HFFD的性能,减少人脸的错误检测。
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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