T. Ohashi, Z. Aghbari, and A. Makinouchi (Japan)
Color-based image segmentation, Hill-Climbing
In this paper, we present a novel image segmentation
method that produces a set of visually coherent regions.
The method is based on a hill-climbing approach and
achieves the segmentation by performing two main tasks.
First, the hill-climbing algorithm detects local maxima of
clusters in the global three-dimensional color histogram
of an image. Then, the algorithm associates the pixels of
an image with the detected local maxima; as a result,
several visually coherent segments are generated. The
segmentation algorithm is simple and fast. Moreover, the
whole segmentation process is performed without any
hand-tuning of parameters. This method does not assume
any a priori knowledge on the number of clusters or the
content of an image.