基于皮肤区域分割和条件合并的人脸候选对象鲁棒提取

Sung-Hoon Kim, Hyon-Soo Lee, Hyung-Ho Kim
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引用次数: 1

摘要

在人脸检测中,利用肤色信息可以缩小候选人脸的搜索范围。然而,在复杂的场景中,基于肤色的人脸检测在处理相似颜色背景、重叠人脸和划分成多区域的事实人脸等肤色区域时失败。本研究的目的是研究人脸检测系统中候选人脸的鲁棒提取。首先,通过肤色分类器、孔洞滤波和形态学运算检测输入图像中的皮肤区域;其次,利用图像分割技术将皮肤区域划分为均匀区域;最后,通过条件合并正面人脸的纵横比,从该区域的分割中提取有效的候选人脸。将所提出的候选人脸提取方法应用于人脸检测系统,并在不同颜色图像上进行了测试。实验结果表明,在相同的人脸检测系统中,该方法的人脸检测率高于其他人脸候选提取方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust extraction of face candidate through segmentation and conditional merging in skin area
In the face detection, using skin color information can reduce the search range for a face candidate. However, in a complex scene, the face detection based on using skin color failed when it deals with skin color area including similar color background, overlapping faces and factual face divided into multi areas. The aim of this work is focus on robust extraction of face candidate for face detection system. Firstly, the areas of skin in the input image are detected by the skin color classifier, holes filter, and morphological operations. Secondly, it uses image segmentation technique to divide a skin area into the homogeneous regions. Finally, it extracts a valid face candidate from the segments in the area by using conditional merging with the aspect ratio of frontal face. The proposed face candidate extraction method is applied to a face detection system and tested on various color images. The experimental result shows that the face detection rate of our proposed method is higher than other face candidate extraction methods in the same face detection system.
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