肤色检测和Hu矩在安全帽识别中的应用  

Skin Color Detection and Hu Moments in Helmet Recognition Research

作　　者：刘晓慧[1] 叶西宁[1] 

机构地区：[1]华东理工大学信息科学与工程学院,上海200237

出　　处：《华东理工大学学报（自然科学版）》2014年第3期365-370,共6页Journal of East China University of Science and Technology

基　　金：国家自然科学基金(60974066)

摘　　要：安全帽在工业生产中的应用非常广泛,为了防止事故发生,确保生产安全,建立对安全帽的自动检测及报警系统变得越来越迫切。主要对安全帽的识别算法进行了研究,采用肤色检测的方法定位到人脸区域,并以此获得脸部以上的区域图像,将Hu矩作为图像的特征向量,分别比较神经网络和支持向量机(SVM)两种分类模型。实验结果表明:SVM对安全帽的识别有很好的效果,将会对监控系统实现智能化提供有力的支持和实际的指导意义。Helmet has been widely used in industrial production. In order to prevent accidents and ensure production safety, it is quite important to set up an automatic detecting and warning system. This paper focuses on the recognition algorithm on helmet. By using skin color detection to locate the face region, the region images above the face can be obtained. Moreover, Hu moments are taken as image feature vectors to compare neural network and SVM as classification models. Experimental results show that SVM can attain a better recognition on helmet and provides a stronger support and practical guidance for the realization of intelligent monitoring system.

关 键 词：肤色检测 HU矩 神经网络 SVM 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]