A Paper On Edge Detection In Images Using Fuzzy K Means Clustering Approach

Abstract

Edge Detection plays a major role in Image processing applications. K means clustering using fuzzy logic is a technique which produces high quality images. There are existences of many edge detection methods.  Among these this approach using Fuzzy logic elevates the performance in the output for Gray scale images. The features considered for edge detection are Mean, Standard Deviation, Entropy and image gradient. Using these features the image quality has been improved by this Fuzzy K means Clustering approach.