Segmentation Using ‘new’ Texture Feature

Color, texture, shape and luminance are the prominent features for image segmentation. Texture is an organized group of spatial repetitive arrangements in an image and it is a vital attribute in many image processing and computer vision applications. The objective of this work is to segment the texture sub images from the given arbitrary image. The main contribution of this work is to introduce “NEW” texture feature descriptor to the image segmentation field. The NEW texture descriptor labels the neighborhood pixels of a pixel in an image as N,W,NW,NE,WW,NN and NNE(N-North, W-West).To find the prediction value, the gradient of the intensity functions are calculated. Eight component binary vectors are formed and compared to prediction value. Finally end up with 256 possible vectors. Fuzzy c-means clustering is used to segment the similar regions in textural image Extensive experimentation shows that the proposed methodology works better for segmenting the texture images, and also segmentation performance are evaluated. .