Paper Title:Image Segmentation : A Matlab Based Approach

Abstract

This paper describes color -based segmentation using K-Means clustering and watershed segmentation to separate touching objects in an image. The watershed transform is often applied to this problem. The watershed transform finds "catchment basins" and "watershed ridge lines" in an image by treating it as a surface where light pixels are high and dark pixels are low. Segmentation using the watershed transform works better if you can identify, or "mark," foreground objects and background locations. By using Statistics and Machine Learning Toolbox and Image processing Toolbox, to segment colors in an automated fashion using the L*a*b* color space and K-means clustering. .


Keywords:K-Means Clustering, Marker-Controlled Watershed Segmentation, Retrospective Image Registration Evaluation (RIRE), Intensity-based registration, Watershed transform..