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Skin color modeling for face detection and segmentation: a review and a new approach

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Abstract

Detecting skin-colored pixels, although seems a straightforward easy task, has proven to be quite a challenging task in images that are captured under complex unconstrained imaging conditions. Color segmentation is an important method of segmenting the body in images. In this paper, we first provides a review of skin color modeling research works for face detection. In particular, we focus on discussing the challenges of skin color modeling, detection, and segmentation, and then we present the skin color modeling and region-based skin segmentation. We also propose a new approach to analyze the hue characteristics of monitoring personnel in coal mine. We determine the skin color boundaries of the miners using the boundary detection method based on the response of visual hue. And then, we apply to determining hue area method using dual hue detector to segment skin color for miners. Experiments show that the method has excellent ability to segment skin regions of miners. We also summarize the most widely used methods for skin detection approaches and collecting their numerical evaluation results.

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Acknowledgments

This work was sponsored by Qing Lan Project, the National Natural Science Foundation of China (Grant No. 51104157,51404258), the China Postdoctoral Science Foundation (Grant Nos.2013T60574, 20100481181), the Ph.D. Programs Foundation of Ministry of Education of China (Grant No. 20110095120008), and Natural Science Foundation of Jiangsu Province (Grant No. BK20140202).

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  1. College of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China

    Wei Chen, Ke Wang, Haifeng Jiang & Ming Li

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  1. Wei Chen
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  2. Ke Wang
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  4. Ming Li
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Correspondence to Wei Chen.

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Chen, W., Wang, K., Jiang, H. et al. Skin color modeling for face detection and segmentation: a review and a new approach. Multimed Tools Appl 75, 839–862 (2016). https://doi.org/10.1007/s11042-014-2328-0

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  • DOI: https://doi.org/10.1007/s11042-014-2328-0

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