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基于支持向量机技术的粮虫图像分类技术研究
引用本文:党培,谭联.基于支持向量机技术的粮虫图像分类技术研究[J].数字社区&智能家居,2009(18).
作者姓名:党培  谭联
作者单位:河南工业大学机电工程学院;华北水利水电学院电力学院;
基金项目:河南工业大学科研基金资助项目(06XJC005)
摘    要:介绍了支持向量机的基本思想,提出了一个基于支持向量机的粮虫模式识别系统。该系统先对粮虫图像进行小波边缘提取,根据灰度共生矩阵和局部统计方法提取小波分割后的图像纹理特征。最后利用支持向量机对粮虫图像进行分类。

关 键 词:特征提取  小波变换  支持向量机  图像识别  

Study on Stored-Product Pests Recognition Based on Support Vector Machine
DANG Pei,TAN Lian.Study on Stored-Product Pests Recognition Based on Support Vector Machine[J].Digital Community & Smart Home,2009(18).
Authors:DANG Pei  TAN Lian
Affiliation:DANG Pei1,TAN Lian2 (1.School of Mechanical & Electrical Engieering,Henan University of Technology,Zhengzhou 450007,China,2.School of Electric Power,North China Institute of Water Conservancy , Hydroelectric Power,China)
Abstract:The foundations of support vector machines are introduced. An evaluation model based on SVM is made, and the model is tested to obtain better results. Edge detction based on wavelet multi-scale identity is made.The statistics features based on regional gray and the co-occurrence matrix of gray level are taken as performing image segmentation. It is expected that the SVM method would be further applied to the field.
Keywords:feature extraction  wavelet transform  SVM  image recognition  
本文献已被 CNKI 等数据库收录!
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