1. A method for sectioning an input image into a plurality of regions, the method comprising the steps of: (a) converting each pixel of the input image into color coordinates in an arbitrary color space including a luminance (L) axis; (b) partitioning the color space into a plurality of layers along the luminance (L) axis and partitioning each of the plurality of layers into a plurality of bins along color (&agr; and &bgr;) axes; (c) obtaining an upper last circle by a mean-shift analysis, the upper last circle encircling the largest number of pixels having features most similar to those of a base pixel located at a predetermined position within a bin having the largest number of pixels in the color space among bins included in an upper layer; (d) obtaining a lower last circle by the mean-shift analysis, the lower last circle including the largest number of pixels having features most similar to those of a base pixel located at the same position as the center of the upper last circle in a lower layer adjacent to the upper layer; (e) including the upper last and lower last circles in the same cluster if a distance between the centers of the upper last and lower last circles is less than a first threshold value, and if another lower layer adjacent to the lower layer exists, determining the lower layer and the adjacent lower layer as a new upper layer and a new lower layer, respectively, and returning to step (d); (f) if the distance between the centers of the upper last and lower last circles is no less than the first threshold value or if the adjacent lower layer does not exist, partitioning the cluster using a last circle including the smallest number of pixels in the color space used in calculating an average color, an average texture, and an average position among the last circles included in the cluster; and (g) performing steps (c)-(f) on the remaining pixels not included in the upper last or the lower last circle and generating an image graph using clusters obtained for all pixels in the color space.