This paper compares the performance of RGB, YCbCr, XYZ, and HSV color spaces in image segmentation. Four segmentation techniques, namely K-means, Fuzzy C-means, Region Growing, and Graph Cut, are evaluated using color images from the Berkeley database. The results indicate that combining color components can improve segmentation accuracy.