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当前位置: 首页 > 文章 > 基于机器视觉的甘蔗茎节特征提取与识别 农业机械学报 2010,41 (10) 190-194
Position: Home > Articles > Recognition and Features Extraction of Sugarcane Nodes Based on Machine Vision Transactions of the Chinese Society for Agricultural Machinery 2010,41 (10) 190-194

基于机器视觉的甘蔗茎节特征提取与识别

作  者：
陆尚平;文友先;葛维;彭辉
单  位：
华中农业大学工程技术学院;广西农业厅市场与经济信息处
关键词：
甘蔗茎节;识别;机器视觉;支持向量机;聚类
摘  要：
为实现含有蔗芽的有效蔗种片段机器智能切断,引入机器视觉技术识别甘蔗茎节。以甘蔗图像HSV颜色空间的S分量经阈值分割、数学形态滤波处理作为模板,和H分量经阈值分割的反图像进行与运算得到合成图;将合成图划分为64个列块区域,提取质心比、粗度比和白点比等7个特征指标,再用支持向量机分类识别茎节与节间列块,得到茎节与节间的平均识别率为93.359%;对支持向量机分类出的茎节列块进行聚类分析,得到茎节数与位置的平均识别率分别为94.118%、91.522%。
译  名：
Recognition and Features Extraction of Sugarcane Nodes Based on Machine Vision
作  者：
Lu Shangping1 Wen Youxian1 Ge Wei2 Peng Hui1 (1.College of Engineering and Technology,Huazhong Agricultural University,Wuhan 430070,China 2.Market and Economic Information Department,Department of Agriculture of Guangxi Zhuang Autonomous Region,Nanning 530022,China)
关键词：
Sugarcane nodes,Recognition,Machine vision,Support vector machine,Clustering
摘  要：
To achieve machine intelligence cutting of effective sugarcane kinds of fragments with sugarcane bud,machine vision was introduced to identify sugarcane nodes.Through acquiring the S component of HSV color space by threshold,mathematical morphology filtering as template and the anti-phase image of the H-component by threshold was added to get synthesized image.Synthetic image was divided into 64 regions and obtained seven characteristic indicators,such as centroid ratio,roughness ratio and white point ratio,and so on.Then support vector machine was introduced to identify sugarcane nodes and sugarcane internodes.The average recognition rate of sugarcane nodes between internodes was 93.359%.Clustering analysis was introduced to identify sugarcane nodes blocks which were got by support vector machine(SVM) classification.The average recognition rates of the sugarcane numbers and the sugarcane nodes position were 94.118% and 91.522% respectively.

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