title: Color image segmentation based on different color space models using automatic GrabCut.
abstract: This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase. Comparisons with the original GrabCut show the efficiency of the proposed automatic technique in terms of segmentation, quality, and accuracy. As no explicit color space is recommended for every segmentation problem, automatic GrabCut is applied with RGB, HSV, CMY, XYZ, and YUV color spaces. The comparative study and experimental results using different color images show that RGB color space is the best color space representation for the set of the images used.
authors.affiliation: Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt.
authors.forename: Dina
authors.identifier: 0000-0003-1201-1789
authors.initials: D
authors.lastname: Khattab
authors.affiliation: Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt.
authors.forename: Hala Mousher
authors.initials: HM
authors.lastname: Ebied
authors.affiliation: Faculty of Computer Studies, Arab Open University-Headquarters, 13033 Al-Safat, Kuwait.
authors.forename: Ashraf Saad
authors.initials: AS
authors.lastname: Hussein
authors.affiliation: Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt.
authors.forename: Mohamed Fahmy
authors.initials: MF
authors.lastname: Tolba
mesh_terms: D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D003116:Color; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D010364:Pattern Recognition, Visual; D015203:Reproducibility of Results; D013028:Space Perception