基于图像处理技术的玉米叶部病害识别研究

Studies on Image Processing of Maize Leaf Diseases

本文结合玉米作物病害的图像特征,首先进行图像的预处理,实现叶部病斑的分割;随后以6个参量来描述玉米叶部病斑的形状特征;将图像由RGB坐标向HSI坐标系统转换,提取参量描述病斑颜色特征;采用灰度共生矩阵提取玉米叶部病斑的纹理特征;引入粒子群优化算法对传统神经网络算法进行改进,使之具备准确分类并识别玉米叶部病害的能力;最后构建了玉米叶部病害图像识别系统,并通过实验与比较,证明了所构建的系统识别病害的准确度。

IIn order to identify the disease by using computer, digital image processing technique and pattern recognition technique were used in the paper, which was composed of image acquisition, image preprocessing, feature extraction and matching. The image is converted from RGB model to HIS. A gray level co-occurrence matrix was used to capture the texture features. The particle swarm optimization algorithm was used to improve the bp neural network algorithm. A maize leaf disease features＇ extraction and recognition system was constructed at last. The rationality and validity were validated experimentally.