NON-PARAMETRIC TEXTURE EXTRACTION USING NEURAL NETWORK

In this paper, a method using a neural network was applied for the purpose of urilizing spatial features. The adopted model of neural network the three-layered architecture, and the training algorithm is the back-propagation algorithm. Co-occurrence matrix which is generated from original imge was used for imput pattern to the neural network in order to tolerate variations of patterns like rotation of displacement. Co-occurrence matrix is explained in appendix. To evaluate this method, classification was executed with this method and texture features method over the city area and sand area, which cannot be separated with the conventional method mentioned aboved. In the results of this method and texture features proposed by Haralick the method using texture features was separation rate of 67%~89%. On the contrary, the method using neural network proposed in this research was stable and high separation rate of 80%~98%.