Based on the function connected perceptron neural network texture classification method. It uses 2 Gaussian Markov Random Field Model (GM RF) to describe the texture, the model parameters is the texture feature, parameter estimation using least squares error obtained. the estimated parameters as the expression of texture feature vector, using the characteristics of sensor networks for classification, and the use of function to resolve connection problems can not be separated from linear. of texture images of the experiments show that this approach can enhance the learning speed, to simplify the calculation process and obtain a better effect of texture classification.

textureclassfication.pdf

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