%0 Journal Article
	%A Elham Alaee and  Mousa Shamsi and  Hossein Ahmadi and  Soroosh Nazem and  Mohammadhossein Sedaaghi
	%D 2014
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 90, 2014
	%T Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
	%U https://publications.waset.org/pdf/9998526
	%V 90
	%X Human face has a fundamental role in the appearance
of individuals. So the importance of facial surgeries is undeniable.
Thus, there is a need for the appropriate and accurate facial skin
segmentation in order to extract different features. Since Fuzzy CMeans
(FCM) clustering algorithm doesn’t work appropriately for
noisy images and outliers, in this paper we exploit Possibilistic CMeans
(PCM) algorithm in order to segment the facial skin. For this
purpose, first, we convert facial images from RGB to YCbCr color
space. To evaluate performance of the proposed algorithm, the
database of Sahand University of Technology, Tabriz, Iran was used.
In order to have a better understanding from the proposed algorithm;
FCM and Expectation-Maximization (EM) algorithms are also used
for facial skin segmentation. The proposed method shows better
results than the other segmentation methods. Results include
misclassification error (0.032) and the region’s area error (0.045) for
the proposed algorithm.

	%P 973 - 977