Study on Face Detection Algorithm Based on Skin Color Segmentation and AdaBoost Algorithm

Author(s):  
Liying Lang ◽  
Weiwei Gu
2013 ◽  
Vol 811 ◽  
pp. 417-421
Author(s):  
Shi Lei

Aiming at color images under complex background, this paper put forward a face detection algorithm based on skin color segmentation, combining the geometric characteristics. The skin region can be obtained by using skin color model and OTSU method to automatically optimize threshold segmentation image. By analyzing the characteristics of skin color region, the face position is determined by criterion of ellipse area.


2014 ◽  
Vol 513-517 ◽  
pp. 1590-1594
Author(s):  
Yu Wang ◽  
Xiao Juan Ban ◽  
Xing Yang ◽  
Yi Fei Guo

Skin color segmentation and AdaBoost algorithm always play important roles in various face detection methods. To combine the two smoothly, this paper investigates face detection methods based on skin color feature and AdaBoost algorithm. Experimental results show that the proposed methods can effectively reduce the false alarms.


2011 ◽  
Vol 225-226 ◽  
pp. 437-441
Author(s):  
Jing Zhang ◽  
You Li

Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on skin color segmentation and Support Vector Machine(SVM) is proposed. Firstly, segmenting image using color model to filter candidate faces roughly; And then Eye-analogue segments at a given scale are discovered by finding regions which are darker than their neighborhoods to filter candidate faces farther; at the end, SVM classifier is used to detect face feature in the test image, SVM has great performance in classification task. Our tests in this paper are based on MIT face database. The experimental results demonstrate that the proposed method is encouraging with a successful detection rate.


2014 ◽  
Vol 85 (14) ◽  
pp. 29-34
Author(s):  
Sabiha Sultana ◽  
Md. Saiful Islam ◽  
Md. Golam Moazzam

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