棉花异性纤维图像特征提取  

Image Feature Extraction of Cotton Foreign Fibre

作　　者：刘双喜[1] 张馨[1] 郑文秀[1] 王金星[1] 

机构地区：[1]山东农业大学机械与电子工程学院,泰安271018

出　　处：《农业机械学报》2010年第3期158-162,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金："十一五"国家科技支撑计划资助项目(2006BAD11A14-3)

摘　　要：针对棉花加工过程中存在的异性纤维,采用机器视觉技术,通过图像处理方法提取异性纤维目标,采集异性纤维特征数据,应用一种改进型粗糙集理论,进行异性纤维图像目标特征向量的提取,得到有效的特征向量。最后采用决策树理论,利用提取的特征向量进行识别,实验表明,所提取的特征向量对于识别棉花异性纤维是有效的,识别率达到95%。For the existence of foreign fibre during cotton processing,machine vision technology and image processing were used in order to not only extract foreign fibre goals,but also collect characteristic data of foreign fibre.Decision tree theory and feature vectors extracted were used to recognize foreign fibre after eigenvectors of aimed foreign images were effectively extracted through an improved version of rough set theory.Experimental results showed that feature vectors extracted from the image of foreign fibre for the identification of cotton foreign fibre was effective and the recognition rate reached more than 95%.

关 键 词：棉花 异性纤维 特征提取 粗糙集 决策树 

分 类 号：TP274.3[自动化与计算机技术—检测技术与自动化装置]