Image classification based on textural feature using artificial neural network

Image classification plays an important part in the fields of Remote sensing, Image analysis and Pattern recognition. Image classification can be done using conventional methods. But conventional methods lead to misclassification due to strictly convex boundaries. Textural features are included for better classification but are inconvenient for conventional methods. The proposed system uses textural feature based image classification using neural network. Textural features are extracted using Gray level co-occurrence matrix and artificial neural network is developed for the classification of images into different classes. Neural network is trained by supervised learning using standard back propagation algorithm for the classification of images.