工矿自动化2017，Vol.43Issue(5)：26-30,5.DOI:10.13272/j.issn.1671-251x.2017.05.007
煤与矸石图像纹理特征提取方法
Extraction method of texture feature of images of coal and gangue
摘要
Abstract
In view of problems of less extraction feature parameters and low recognition precision existed in image processing methods of coal and gangue,an extraction method of texture feature of images of coal and gangue fused with local binary pattern and gray level co-occurrence matrix was proposed.Firstly,the preprocessed images of coal and gangue were transformed into local binary pattern images,then the local binary pattern images were used to generate gray level co-occurrence matrix,the mean value and normalization of those texture features including angular second moment,correlation,contrast and entropy were processed.Finally,support vector machine was used for samples training and recognition results were obtained.The experimental results show that the method can effectively extract the texture feature of images of coal and gangue,and the recognition rates of coal and gangue are respectively 94％ and 96％.关键词
煤与矸石/图像处理/纹理特征/局部二值模式/灰度共生矩阵/支持向量机Key words
coal and gangue/image processing/texture feature/local binary pattern/gray level co-occurrence matrix/support vector machine分类
矿业与冶金引用本文复制引用
米强,徐岩,刘斌,徐运杰..煤与矸石图像纹理特征提取方法[J].工矿自动化,2017,43(5):26-30,5.基金项目
山东省研究生教育创新计划项目(01040105305) （01040105305）
山东科技大学教学研究项目(JG201506) （JG201506）
山东科技大学研究生教育创新项目(KDYC13026,KDYC15019). （KDYC13026,KDYC15019）
