A comparative study of different color space models using FCM-based automatic grabcut for image segmentation

Abstract

GrabCut is one of the powerful color image segmentation techniques. One main disadvantage of GrabCut is the need for initial user interaction to initialize the segmentation process which classifies it as a semi-automatic technique. The paper presents the use of Fuzzy C-means clustering as a replacement of the user interaction for the GrabCut automation. Several researchers concluded that no single color space model can produce the best results of every image segmentation problem. This paper presents a comparative study of different color space models using automatic GrabCut for the problem of color image segmentation. The comparative study includes the test of five color space models; RGB, HSV, XYZ, YUV and CMY. A dataset of different 30 images are used for evaluation. Experimental results show that the YUV color space is the one generating the best segmentation accuracy for the used dataset of images.