Optical Textures Classification of Coke Microscopic Image based on SVM

摘要：

In the view of characteristics of coke optical texture in micrograph, a classification method, which is based on Support Vector Machine and combining color and texture features, is proposed. Firstly, color features of the coke microscopic images of different optical textures are analyzed. With color features, isotropic and anisotropic components are classified. Then the gray level co-occurrence matrix of anisotropic components is calculated, the texture features (such as entropy) of each anisotropic components are computed. With texture features, each subclass in anisotropic component is further classified. Experimental results show that with the proposed method the classification among different optical textures of coke is more reasonable and effective than traditional techniques, including neural networks.

关键词： coke optical texture micrograph support vector machine color feature texture feature

作者: Peizhen WANG Ke ZHOU Fang ZHOU Dailin ZHANG

作者单位: School of Electrical & Information Anhui University of Technology Maanshan, China Anhui Key Laboratory of clean conversion and utlization Anhui University of Technology Maanshan, Ch

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 596-600

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）