  In computer vision, image segmentation is always selected as a major research
topic by researchers. Due to its vital rule in image processing, there always
arises the need of a better image segmentation method. Clustering is an
unsupervised study with its application in almost every field of science and
engineering. Many researchers used clustering in image segmentation process.
But still there requires improvement of such approaches. In this paper, a novel
approach for clustering based image segmentation is proposed. Here, we give
importance on color space and choose lab for this task. The famous hard
clustering algorithm K-means is used, but as its performance is dependent on
choosing a proper distance measure, so, we go for cosine distance measure. Then
the segmented image is filtered with sobel filter. The filtered image is
analyzed with marker watershed algorithm to have the final segmented result of
our original image. The MSE and PSNR values are evaluated to observe the
performance.
