基于图像校正技术的大豆病害自动诊断模型

Automatic soybean disease diagnosis model based on image correction technology

为解决大豆病害无损采集的非线性失真图像与病种之间映射关系的问题,将数字图像处理技术与神经网络推理机制相结合,提出了基于图像校正技术的大豆病害自动诊断模型.通过自制标定模板无损采集大豆病害数字图像,利用双线性投影映射算法校正病害图像的几何失真,同时计算病斑区域的形状特征、颜色特征及纹理特征参数,以此多维特征指标为基础,应用神经网络的强自适应性自动取得大豆病种推理规则,建立大豆病害自动诊断模型.仿真试验表明:大豆病害的失真图像校正精度达到99%以上,其病害种类诊断准确率为98.33%,实现了大豆病害自动诊断和精确测报.

To solve the problem of nondestructive collection of nonlinear distortion images of soybean diseases and the mapping relationship between disease types, the digital image processing technology and the neural network reasoning mechanism were combined to propose the automatic diagnosis model of soybean disease by image correction technology.The nondestructive collection of digital images of soybean diseases was conducted by selfmade calibration templates, and the bilinear projection mapping algorithm was used to correct the geometric distortion of disease images.The shape of lesion area characteristics,the color feature and the texture feature parameter were calculated based on the multidimensional feature index. The inference rules of soybean disease were automatically obtained by applying the strong adaptability of neural network, and the automatic diagnosis model of soybean disease was established.The simulation experiments show that the distortion correction accuracy of soybean diseases is more than 99%, and the diagnostic accuracy of disease types is 98.33%. The automatic diagnosis and the accurate measurement of soybean diseases are realized.