The Study On Diseased Spots Recognition And Characteristic Calculation Of Nonlinear Distort Lamina Based On Fuzzy Neural Network

This paper studies the crucial technologies about intellectual diagnosis of diseases of plants and realizes correction of digital images, recognition of diseased area, the extraction and calculation of diseased area's features,according to image processing, neural net and plant pathology.Considering the nonlinear distortion of images of leaves, bilinear map equation is proposed to restore distorted images by utilizing interpolation, so that the correction of distorted images is obtained. Meanwhile, the five-layer fuzzy inference system is given in output layer by the partition of diseased area. Because BP algorithm has a slow convergence and usually is trapped into the local minimum, a new algorithm is proposed, which is a more excellent one that is combining two algorithms: genetic algorithm and BP. The extraction and calculation of features in geometry, color and texture are achieved after the pre-processing of the image with scabs by utilizing smoothing technique according to the factors of intellectual diagnosis for diseased plants. Besides these above, a model is designed that is a three-layer quantum neural network model, whose hidden layer is arctangent function. By the improved model, uncertainty of sample data can be determined during the training process in the given gradient descent algorithm. The results of stimulation indicate that the crucial technology proposed in the paper can achieve remarkable recognition and judgment in diagnosis of potatos'early blight.