基于颜色特征和属性约简的黄瓜病害识别方法  

Cucumber disease recognition based on color feature and attribute reduction

作　　者：谢泽奇[1] 张会敏[1] 张善文[1] 张云龙[1] 

机构地区：[1]郑州大学西亚斯国际学院,河南郑州451150

出　　处：《江苏农业学报》2015年第3期526-530,共5页Jiangsu Journal of Agricultural Sciences

基　　金：国家自然科学基金项目(61272333);河南省科技厅科技攻关项目(142102310518;142400410853;142300410309);河南省教育厅科学技术研究重点项目(14B520064;15A520100);郑州大学西亚斯国际学院校级科研项目(2014KYYB23)

摘　　要：为了减少黄瓜叶部病害给农业生产带来的损失,提高病害的识别率和精度,提出了一种基于颜色特征和属性约简算法的黄瓜病害叶片分割与识别方法。该方法首先利用最大类间方差(Otsu)阈值法对黄瓜病害叶片图像进行病斑分割;其次提取病斑图像的36个分类特征,再利用基于区分矩阵的属性约简算法进行特征选择;最后利用最近邻分类器进行病害识别。该方法在5种常见黄瓜病害叶片图像数据库上进行了病害识别试验,结果表明,识别率高达94.8%。说明,该方法对作物病害叶片图像识别是有效可行的。To reduce the loss caused by cucumber leaf disease, and improve disease recognition rate and accuracy, a leaf image segmentation and disease recognition method for cucumber was proposed based on color feature and attribute re-duction algorithm. Firstly, the Otsu algorithm was applied to segment the cucumber diseased leaf image. Secondly, 36 di-agnostic characters of disease lesion were extracted, and selected by using attribute reduction algorithm based on discern-ibility matrix. Finally, the crop diseases were recognized using the nearest neighbor classifier. As an effective and feasible approach for crop disease recognition, this method could recognize as high as 94. 8% of five cucumber diseases.

关 键 词：颜色特征 属性约简 病斑分割 病害识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]