Color space selection for unsupervised color image segmentation by histogram multi-thresholding
Résumé
We propose a new color image segmentation algorithm by unsupervised classification of pixels. This procedure iteratively constructs the classes by histogram multi-thresholding. For this purpose, the procedure selects different color spaces in which the modes of the 1D-histograms are separated as well as possible, so that each mode corresponds effectively to a region in the image.