Maize Lesion Image Preprocessing System

In recent ten years, the performance of computer has undergone a qualitative leap, with theprocessing speed reaching to hundreds of billions. In such a good environment, digital imageprocessing technology experiences a rapid development, and has been applied in many areas.Corn is one of the most important crops in Heilongjiang Reclamation. Corn makes up a largeproportion in crop production. However, plant diseases and insect pests cause great harm tocrops. Corn northern leaf blight and corn southern leaf blight are common diseases inHeilongjiang Reclamation.In this paper, corn northern leaf blight and corn southern leaf blight are used asexperimental objects. By reading a lot of papers, this paper develops a corn lesion imagepreprocessing system by combining digital image processing technology and software. It notonly provides the foundation for image recognition of corn disease, but also reduces the burdenfor experts who research the disease of corn.The main contributions in this paper are as follows:1．According to corn pathological knowledge, select hardware devices to collect the imageof corn left disease, and smooth filtering, median filtering, image preprocessing to images werecollected.2．Using a variety of image segmentation algorithm for preprocessing image to segment,and verifing the multi-scale anisotropic wavelet shrinkage image segmentation algorithm hasgood segmentation effect to image which provides in this paper, and improved the multi-scaleanisotropic wavelet shrinkage image segmentation algorithm, which can be used in color images.3．Feature extraction the corn spot image which is already segmentation, and extractingsuccessfully the color, texture, and shape characteristics, provide the basis for the identificationof the spot.4．Combining WPF and Matlab, developed a set of image storage, image processing, anduser management in one of corn spot image preprocessing system.