A Robust Face Detection Method Based on Skin Color and Edges


Deepak Ghimire, Joonwhoan Lee, Journal of Information Processing Systems Vol. 9, No. 1, pp. 141-156, Mar. 2013  

https://doi.org/10.3745/JIPS.2013.9.1.141
Keywords: Face Detection, Image Enhancement, Skin Tone Percentage Index, Canny Edge, Facial Features
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Abstract

In this paper we propose a method to detect human faces in color images. Many existing systems use a window-based classifier that scans the entire image for the presence of the human face and such systems suffers from scale variation, pose variation, illumination changes, etc. Here, we propose a lighting insensitive face detection method based upon the edge and skin tone information of the input color image. First, image enhancement is performed, especially if the image is acquired from an unconstrained illumination condition. Next, skin segmentation in YCbCr and RGB space is conducted. The result of skin segmentation is refined using the skin tone percentage index method. The edges of the input image are combined with the skin tone image to separate all non- face regions from candidate faces. Candidate verification using primitive shape features of the face is applied to decide which of the candidate regions corresponds to a face. The advantage of the proposed method is that it can detect faces that are of different sizes, in different poses, and that are making different expressions under unconstrained illumination conditions


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Cite this article
[APA Style]
Ghimire, D. & Lee, J. (2013). A Robust Face Detection Method Based on Skin Color and Edges. Journal of Information Processing Systems, 9(1), 141-156. DOI: 10.3745/JIPS.2013.9.1.141.

[IEEE Style]
D. Ghimire and J. Lee, "A Robust Face Detection Method Based on Skin Color and Edges," Journal of Information Processing Systems, vol. 9, no. 1, pp. 141-156, 2013. DOI: 10.3745/JIPS.2013.9.1.141.

[ACM Style]
Deepak Ghimire and Joonwhoan Lee. 2013. A Robust Face Detection Method Based on Skin Color and Edges. Journal of Information Processing Systems, 9, 1, (2013), 141-156. DOI: 10.3745/JIPS.2013.9.1.141.