Color based segmentation using K-mean clustering and watershed segmentation

Color image segmentation is an upcoming topic of the research for researchers in image processing. There is a vital need for better segmentation approach because of its utmost importance in the technique known as image processing. Clustering is mostly used methodology for the segmentation of images. This content is a combined approach for the segmentation of images. Here, we are combining K-mean Clustering Technique and Watershed segmentation algorithm. Color space has most starring impact on segmentation process, we have chosen l*a*b* color space in our approach. When we perform segmentation process or fetching of the clusters from an image, noise arises in that image. To eliminate that noise filters are being used. First, we will check the type of noise and then we will decide what kind of filter is being used.