Abstract
First disease spot color and texture features were extracted from barley field images in Gansu, and the feature vectors were used as input vector to establish barley diseases classifier model. Then the neural network was applied to rain classified model with collected images as training set. Finally, two groups of random selected images as test sets were used to perform classified verification experiments. The experimental results show that the overall accuracy of barley dis-eases recognition model is above 86.7%. Therefore, Barley disease image recognition based on neural net-work provides a new technology for the classified treatment of barley diseases.
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