Abstract: Disease will seriously affect the yield and quality of cucumber and cause economic losses to farmers. Therefore, the research of recognition for cucumber disease is necessary. In this paper, cucumber disease characteristic parameters were extracted after image processing. Then cucumber diseases were identified using neural network. Cucumber leaves of bacterial angular leaf spot and downy mildew were collected for image recognition. The images of cucumber disease leaves would be processed by using a series of image pre-processing methods, such as image transforming, image smoothing and image segmentation. White was chosen as the background of diseased leaf, median filter was utilized to effectively wipe out the disturbance of noise, and two-apex method was applied to separate the disease images from the background. In the experiment of cucumber lesion site segmentation, this paper attempted to process images by using edge detection method and maximum inter-class variance method. The contour of lesion site extracted by edge detection method was not very complete, while the Image segmentation result by using maximum inter-class variance method was better. First, the lesion site was extracted from R branch image by the method of maximum inter-class variance. The background image was obtained from B branch image by the method of histogram threshold segmentation. The lesion image could be obtained by subtraction of the two images. The shape characteristics of the lesion could be extracted after regional marker. In the experiment of identification for cucumber bacterial angular leaf spot and downy mildew, 10 shape features were extracted. Each class of 30 samples, a total of 60 samples was selected as training samples and input to neural network. After the neural network had been trained, the remaining 20 samples of each class, a total of 40 samples were inputted to the neural network as test samples. The correct recognition rate is 100%. The result of the experiment shows that the identification method for cucumber bacterial angular leaf spot and downy mildew based on lesion site shape and neural network is feasible.