灰度自适应边缘检测在煤矸石分选中的应用  

Application of Gray Adaptive Edge Detection in Gangue Sorting

作　　者：巩文迪[1] 卢兆林[2] 唐全[2] 刘佳毅[1] 

机构地区：[1]河北工程大学信息与电气工程学院,河北邯郸056038 [2]中国矿业大学信息与电气工程学院,江苏徐州221116

出　　处：《煤炭技术》2013年第10期95-96,共2页Coal Technology

摘　　要：针对煤和矸石灰度的不同,本文介绍了一种基于灰度的自适应边缘检测法,首先对图像进行灰度增强预处理,然后采用迭代算法求出图像分割的最佳阈值,结合形态学的腐蚀算法从而实现图像的精确边缘检测,并给出了仿真实例。与几种经典的边缘检测算子相比较,该算法效果最佳。Based on the differences of coal and gangue in the gray differences, a adaptave edge detection method is introduced in this paper. Firstly, the image has a gray preprocessing of enhancement;then find out the best image segmentation threshold bv using iterative algorithm and so as to realize the precise image edge detection with combing the corrosion algorithm of morphology, also simulation illustration is provlded.By comparing with seberal classical edge dectection operatol; this algorithm has the best effect.

关 键 词：边缘检测 灰度增强 阈值分割 矸石分选 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]