Textural feature based image classification using artificial neural network

Abstract

Image classification plays an important part in the fields of Remote sensing, Image analysis and Pattern recognition. Digital image classification is the process of sorting all the pixels in an image into a finite number of individual classes. The conventional statistical approaches for land cover classification use only the gray values. However, they lead to misclassification due to strictly convex boundaries. Textural features can be included for better classification but are inconvenient for conventional methods. Artificial neural networks can handle non-convex decisions. The uses of textural features help to resolve misclassification. This paper describes the design and development of a hierarchical network by incorporating textural features. The effect of inclusion of textual features on classification is also studied. © 2011 Springer-Verlag Berlin Heidelberg.