Fuzzy classification of image pixels

Abstract

We present a neuro-fuzzy approach for classification of image pixels into three classes: contour, regular or texture points. Exploiting the processing capabilities of a neural network, fuzzy classification rules are derived by learning from data and applied to classify pixels in grey-level images. To derive a proper set of training data, the spatial properties of the image features and a multiscaled representation of images are considered. The effectiveness of the proposed approach is illustrated on some sample images.