New quartile-based region merging algorithm for unsupervised image segmentation using color-alone feature

This study concerns the image segmentation problem and the use of a color-alone feature for reducing the system complexity. On the basis of the color-based mathematical morphology method, the similarity measure between neighboring regions can be obtained as the solution of a ranking problem. To avoid the creation of a false color and false segmentation, a hybrid ordering approach was used instead of vectorized and marginal ordering approaches. Ordering methods that use black as the reference color to sort pixels face a problem: the scope of distance measurement is not optimal. To avoid this problem, we present a scheme for selecting a global reference color. Moreover, for determining orders of color vectors, the hue–saturation–intensity color distance was used instead of the Euclidean distance. The aforementioned scheme involves segmentation that is in accord with human visual perception. Quartile analysis indicated that threshold determination for region-merging showed less sensitivity to context variations of images. To evaluate the algorithm, it was experimentally compared with two typical segmentation schemes on the basis of four quantitative indices.