The main use can be for image retrieval. This colour and maybe amount could be used as a “feature” of the image, and then compared with the rest of the images to check for similarity. Also there are other descriptors like the colour structure descriptor, colour layout descriptor, and the basic histograms. Combined with these, an effective feature can be formed and used for the required application.
Firstly, the standard uses the CIE L*a*b colour space. This is because the Euclidean distances are more perceptual in this domain rather than the conventional RGB. (i.e. some distance X in RGB may not change the colour equally in all directions). The MPEG-7 standard suggests the so-called top-down technique. In this strategy, we first obtain one dominant colour, as the centroid of all pixels in the image.
The algorithm then follows by splitting this cluster. The cluster with the highest distortion is divided into two clusters by adding a small perturbation vector. However, note that this vector is not just any random vector. It is computed (using eigen values and vectors of the covariance matrix) in the direction of maximum variance. Thus we obtain two new centroid locations. These are further updated by the generalized Lloyd algorithm, i.e. assign each point to cluster of closer proximity, and then re-compute the centroid for the given set of points.
Since, we pick and split the centroids with max distortion, it is possible to get any number of dominant colours for the image. Below are example images of the original image, and 3 (left top), 4 (right top), 5, 6, 7 (left bottom) and 8 (right bottom) dominant colour images (click for larger view).