A method for detecting miners based on helmets detection in underground coal mine videos  

作　　者：Cai Limei Qian Jiansheng 

机构地区：[1]School of Information and Electrical Engineering, China University of Mining ＆ Technology, Xuzhou 221116, China

出　　处：《Mining Science and Technology》2011年第4期553-556,共4页矿业科学技术（英文版）

基　　金：provided by the National High Technology Research and Development Program of China (No.2008AA062202)

摘　　要：In order to monitor dangerous areas in coal mines automatically,we propose to detect helmets from underground coal mine videos for detecting miners.This method can overcome the impact of similarity between the targets and their background.We constructed standard images of helmets,extracted four directional features,modeled the distribution of these features using a Gaussian function and separated local images of frames into helmet and non-helmet classes.Out experimental results show that this method can detect helmets effectively.The detection rate was 83.7%.In order to monitor dangerous areas in coal mines automatically, we propose to detect helmets from underground coal mine videos for detecting miners, This method can overcome the impact of similarity between the targets and their background. We constructed standard images of helmets, extracted four directional features, modeled the distribution of these features using a Gaussian function and separated local images of frames into helmet and non-helmet classes. Out experimental results show that this method can detect helmets effectively. The detection rate was 83.7%.

关 键 词：Human detection Helmet detection Coal mine Gaussian model Image pattern recognition 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] X928.02[自动化与计算机技术—计算机科学与技术]