基于颜色特征和属性约简的黄瓜病害识别方法

摘要

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.%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。