The Design and Implementation of Digital ImageSegmentation in HSV Color Space

Segmentation subdivides an image into its constituent parts or objects. The purpose of segmentation is to simplify or change from a digital image to the more meaningful and easier to analyze. Most of the segmentation process is done in RGB representation. In this paper, the segmentation process is done in HSV representation. The process consist several steps: changing the representation from RGB to HSV, search the centroid points using maximin algorithm, clustering by K-Means, and post processing of the results of clustering to eliminate noise and unnecessary detail. This application was created with C #. net with Microsoft Visual Studio 2005 as its IDE. The result indicates that the segmentation results are influenced by the centroid points. With determining the exact number of centroids, it gives clear segmentation result. Factors that can affect the centroid are intensity light and color range on the digital image.