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基于支持向量机分类的图像识别研究
引用本文:谈蓉蓉.基于支持向量机分类的图像识别研究[J].安徽农业科学,2010,38(26):14756-14757.
作者姓名:谈蓉蓉
作者单位:无锡广播电视大学;
摘    要:提出了利用支持向量机(SVM)分类的方法对采集图像进行识别。采用计算机图像处理技术针对棉花苗期杂草图像进行分割,提取棉花与杂草的形状特征参数;选取最有效的特征数据组合输入SVM进行分类学习训练,实现杂草的有效识别。结果表明,使用该方法获得的图像识别效率较高,在同等条件下,速度优于人工神经网络。

关 键 词:颜色特征  形状特征  RTS不变性  SVM  图像识别

Image Recognition Research Based on Support Vector Machine Classification
TAN Rong-rong.Image Recognition Research Based on Support Vector Machine Classification[J].Journal of Anhui Agricultural Sciences,2010,38(26):14756-14757.
Authors:TAN Rong-rong
Institution:TAN Rong-rong(Wuxi Radio & Television University,Wuxi,Jiangsu 214000)
Abstract:It was put forward that by using support vector machine(SVM)classification method to identify the image.Computer image processing technology was adopted to segment images of seedling cotton and weeds and extract shape parameters of cotton and weeds.The most effective combination of characteristics data were selected to import SVM to carry classification learning and training,and the weeds were identified effectively.Experimental results showed that the proposed method used to identify weeds was more efficie...
Keywords:Color characteristic  Shape characteristic  RTS invariance  SVM  Image recognition  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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