计算机应用与软件Issue(12)：186-190,5.DOI:10.3969/j.issn.1000-386x.2014.12.044
基于多特征融合和 SVM 分类器的植物病虫害检测方法
A PLANT PESTS AND DISEASES DETECTION METHOD BASED ON MULTI-FEATURES FUSION AND SVM CLASSIFIER
摘要
Abstract
For plant pests and diseases detection issue in agriculture field, we propose a detection method to realise the fast detection of plant pests and diseases in agricultural production, which is based on the SVM with the feature of high-definition video image fusion.For four kinds of features of each plant leaf image, the colour, HSV, texture and directional gradient histogram, the method adopts the bag of features-based multi-features fusion approach to form the eigenvector, and uses SVM classifier to train the classification.The method raised in the paper has higher accuracy rate, this is proved by the comparative test between the SVM classifiers with the function of mono-feature and of fusion feature.关键词
植物病虫害/多特征融合/特征包/支持向量机/分类器Key words
Plant pests and diseases/Multi-feature fusion/Bag of Features/Support vector machine/Classification分类
信息技术与安全科学引用本文复制引用
蒋龙泉,鲁帅,冯瑞,郭跃飞..基于多特征融合和 SVM 分类器的植物病虫害检测方法[J].计算机应用与软件,2014,(12):186-190,5.基金项目
国家高技术研究发展计划项目（2011AA 100701）；上海市科委科技创新行动计划项目（12511501602）；上海市宝山区科委产学研合作项目（ CXY-2011-11）。 （）
