An algorithm for unsupervised color image segmentation

In a great number of fields of computer vision image segmentation plays an essential role as a preliminary step towards further and higher levels of image processing. An original algorithm for unsupervised segmentation of color images is here presented; it resorts to a palletized representation of images, it uses the low spatial frequency content of color which is represented in the CIELUV space and in this space it builds and thresholds hue and chroma histograms finding out the color clusters which allow the image to be segmented. Evidence of the algorithm's effectiveness is reported.