“…First, the Berkeley image dataset does not have calibrated images and, consequently, we can not assure a good transformation from sRGB to CIE Luv. Second, because the size of L, u and v, is not the same and the method will require six parameters, instead of two, that is, − → σ L , − → σ u Figure 5 shows some results for the mean shift segmentation, corresponding to (h s , h r ) = { (7,15), (13,19), (17,23), (20,25), (25,30), (30, 35)}. These results point out the main advantage of RAD in favor of MS, namely, the capability of RAD to capture the DS of a histogram, whereas MS is ignorant to the physical processes underlying the structure of the DSs as Abd-Almageed and S. Davis explain in [10].…”