Image segmentation using Grey scale weighted average method and type-2 fuzzy logic systems

Abstract

In the paper, the difficulty in image segmentation based on the popular level set framework to handle an arbitrary number of regions has been addressed. There is very few work reported on optimized segmentation with respect to the number of regions. In the proposed model, first the image is classified using type-2 fuzzy logic to handle uncertainty in determining pixels in different color regions. Grey scale average (GSA) method has been applied for finding accurate edge map to segment the image that produces variable number of regions. © 2011 Springer-Verlag.