Face Region Detection using a Color Union Model and The Levenberg-Marquadt Algorithm 


Vol. 14,  No. 4, pp. 255-262, Aug.  2007
10.3745/KIPSTB.2007.14.4.255


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  Abstract

This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB, YCbCr, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate.Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space.The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.

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[IEEE Style]

J. O. Kim, "Face Region Detection using a Color Union Model and The Levenberg-Marquadt Algorithm," The KIPS Transactions:PartB , vol. 14, no. 4, pp. 255-262, 2007. DOI: 10.3745/KIPSTB.2007.14.4.255.

[ACM Style]

Jin Ok Kim. 2007. Face Region Detection using a Color Union Model and The Levenberg-Marquadt Algorithm. The KIPS Transactions:PartB , 14, 4, (2007), 255-262. DOI: 10.3745/KIPSTB.2007.14.4.255.

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