Research on Identification of Coal and Waste Rock based on GLCM and BP Neural Network

摘要：

when exploring the parameters for the coal and waste rock eight characteristic parameters were selected as the whole characters of an image according to their significant differences in gray scale and texture features. On the basis, the error back-propagation algorithm of neu ral network is applied for the nonlinear identification of samples. The identification network was trained successfully through learning samples. Then, the validity of eight characteristic parameters was verified through the tests of experimental images. Meanwhile, the goal of intelligent identification of coal and waste rock is achieved successfully.

关键词： gray-level co-occurrence matrix (GLCM) characteristic parameters MATLAB BP neural network

作者: Liang Haonan Su Baojin He Yaqun He Jingfeng He Qiongqiong

作者单位: School of Chemical Engineering and Technology China University of Mining and Technology Xuzhou,China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1115-1118

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）