Coal Rock Fracture Detection Based on Mathematical Morphology and Self-organizing Map Neural Network
Coal rock fracture detection is the key way to develop coalbed methane.In order to detect the fracture of the coal rock image,a method of combining multi-structure elements morphology with self-organizing map (SOM) neural network clustering is presented in this paper.Firstly,multi-structure elements morphological edge detection algorithm is used to detect all edges of the coal rock image,and then the feature parameters of coal rock image edges are calculated as the inputs of SOM neural network.Finally,the fracture edges and the non-fracture edges are classified by the SOM-based clustering algorithm,and the fracture edges of image are gained.Experimental results show this new method can effectively detect and extract the fracture information of coal rock image.
Coal rock image Fracture detection Mathematical morphology Self-organizing map (SOM)
Bao-Rong FAN Wei ZHANG Chao-Feng LI Yi-Wen JU
School of Internet of Things Engineering,Jiangnan University,Wuxi Jiangsu 214122,China School of Internet of Things Engineering,Jiangnan University,Wuxi Jiangsu 214122,China;Key Laborator Key Laboratory of Computational Geodynamics,College of Earth Science,University of Chinese Academy o
国内会议
杭州
英文
1-9
2014-10-18（万方平台首次上网日期，不代表论文的发表时间）