摘要
针对现有大多数煤与矸石图像识别方法只单一地利用灰度均值和灰度方差进行识别,存在识别准确度和效率不高等问题,提出了一种煤与矸石图像灰度信息和纹理特征提取方法。该方法提取具有代表性的特征参数,如灰度均值、平滑度及灰度共生矩阵的能量、对比度、相关性、熵等,作为识别煤与矸石的重要依据。Matlab仿真分析结果表明,以上特征参数可以有效地描述煤与矸石的图像特征,可为煤与矸石的自动识别与分选提供重要参考依据。
In view of problems of low identification accuracy and efficiency existed in most recognition method of coal and gangue image which only used gray mean and gray variance,an extraction method of gray information and texture features of coal and gangue image was proposed.The representative feature parameters such as gray average,smoothness and energy,contrast,correlation,entropy of gray co-occurrence matrix are extracted,which are taken as the important basis for identification of coal and gangue.Matlab simulation results show that the gray information and the texture feature can well describe characteristics of the coal and the gangue image,which can provide an important reference for automatic identification and separation of coal and gangue.
作者
谭春超
杨洁明
TAN Chunchao YANG Jieming(Electronic and Mechanical Research Institute, Taiyuan University of Technology, Taiyuan 030024, China Key Lab of Advanced Transducers and Intelligent Control System, Ministry of Education and Shanxi Provence, Taiyuan University of Technology, Taiyuan 030024, China)
出处
《工矿自动化》
北大核心
2017年第4期27-31,共5页
Journal Of Mine Automation
基金
山西省科技攻关项目(20120321004-03)
关键词
煤与矸石识别
图像处理
灰度信息
纹理特征
灰度均值
平滑度
灰度共生矩阵
对比度
coal and gangue identification
image process
gray information
texture feature
gray mean
smoothness
gray co-occurrence matrix
contrast