Using Skin Color and HAD-AdaBoost Algorithm for Face Detection in Color Images

作     者：Li-Jie Xue School of Electronic and Information Engineering,Jiangsu University Zhenjiang,PR of China Zheng-Ming Li School of Electronic and Information Engineering,Jiangsu University Zhenjiang,PR of China 

会议名称：《2012 National Conference on Information Technology and Computer Science》

会议日期：2012年

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：supported by Project supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(Jiangsu provincial government general office documents No.6) 

关 键 词：face detection skin color segmentation AD AdaBoost heuristics-structured cascade 

摘      要：Owing to the interference of the complex background in color image,high false positive rate is a problem in face detection based on AdaBoost algorithm.In addition,the training process of AdaBoost is very time consuming.To address these problems,this paper proposes a two-stage face detection method using skin color segmentation and heuristics-structured adaptive to detection AdaBoost （HAD-AdaBoost） algorithm.Firstly,skin color segmentation is applied to remove most of the background.Then,the HAD-AdaBoost cascade classifier is performed on the candidates to make a final face location.By introducing the algorithm of adaptive to detection AdaBoost algorithm （AD AdaBoost） and heuristicsstructured cascade to our system,the resulting classifier consisting of fewer weak classifiers achieves lower error rates.The experimental results demonstrate that our system retrieves 90.24% of the detection rate with 1.69% false alarms on the color image set.