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Paper Abstract and Keywords
Presentation 2007-01-26 16:50
Automatic Extraction of Facial Feature points from Orthogonal Color Images for Surgical Planning
M. Shamsi (Univ. of Tehran/Univ. of the Ryukyus), R. A. Zoroofi, Caro Lucas, M. Sadeghi Hasanabadi (Univ. of Tehran), M. R. Asharif (Univ. of Ryukyus)
Abstract (in Japanese) (See Japanese page) 
(in English) Recent advances in digital human technology combined with the broad availability of high performance computer graphics have created a unique opportunity to develop a novel set of applications meeting the demands of reconstructive and aesthetic plastic surgery. Detection of the facial feature points and measurements based on them plays an essential role in facial reconstructive surgical planning. The appearance of the skin color depends on the lighting conditions. One problem in extraction of feature points is that the image features can be severely corrupted due to illumination, noise, and occlusion, while shadows can cause numerous strong edges. In this paper we presented a fully automatic algorithm based on Gaussian mixture model for segmentation and extraction of facial color skin. Simultaneously, we correct the image shadows from varying illumination. This algorithm will be able to determine accurate contour of facial color skin from two orthogonal views. For this reason, mathematically the varying illumination effect can be expressed as follows:

where is the slowly varying shadow from varying illumination; and is the image noise. Typically, image classes are modeled by a Gaussian distribution with mean and variance . Certainly, replacing one of classes with uniform density probability and amending the EM algorithm appropriately, gives significantly better results. The first step in applying EM algorithm is initialization of the class parameters. This is done with k-means algorithm and then using of the EM parameter estimation. After facial skin localization, we directly locate eyes, mouth and nose based on their feature maps derived from both the luminance and chrominance of frontal image in YCbCr color space. We consider only the area covered by face mask. Finally, the edge information and feature map information combined together for detection of some feature points from frontal view. The combination of edge information with segmented color skin obtained from profile view detects accurately the external edge of face. Then we compute nose tip as a feature point, partition external contour of face in profile view, fit nth order curve and make derivation for feature points detection. 100 patients are selected from ENT section of the Imam Hospital, Tehran, Iran. We have two orthogonal color images from patients. The presented algorithm demonstrates the better results in extraction of face mask and facial features, and is highly robust against shadow from varying illumination in image.
Keyword (in Japanese) (See Japanese page) 
(in English) Facial feature extraction / EM algorithm / , Orthogonal images / Color space / / / /  
Reference Info. IEICE Tech. Rep., vol. 106, no. 509, MI2006-127, pp. 165-168, Jan. 2007.
Paper # MI2006-127 
Date of Issue 2007-01-19 (MI) 
ISSN Print edition: ISSN 0913-5685
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Conference Information
Committee MI  
Conference Date 2007-01-26 - 2007-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) the Cheju National Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2007-01-MI 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Extraction of Facial Feature points from Orthogonal Color Images for Surgical Planning 
Sub Title (in English)  
Keyword(1) Facial feature extraction  
Keyword(2) EM algorithm  
Keyword(3) , Orthogonal images  
Keyword(4) Color space  
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1st Author's Name M. Shamsi  
1st Author's Affiliation University of Tehran/University of the Ryukyus (Univ. of Tehran/Univ. of the Ryukyus)
2nd Author's Name R. A. Zoroofi  
2nd Author's Affiliation University of Tehran (Univ. of Tehran)
3rd Author's Name Caro Lucas  
3rd Author's Affiliation University of Tehran (Univ. of Tehran)
4th Author's Name M. Sadeghi Hasanabadi  
4th Author's Affiliation University of Tehran (Univ. of Tehran)
5th Author's Name M. R. Asharif  
5th Author's Affiliation University of the Ryukyus, Japan. (Univ. of Ryukyus)
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Speaker Author-1 
Date Time 2007-01-26 16:50:00 
Presentation Time 15 minutes 
Registration for MI 
Paper # MI2006-127 
Volume (vol) vol.106 
Number (no) no.509 
Page pp.165-168 
#Pages 4 
Date of Issue 2007-01-19 (MI) 

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