  Image segmentation is the process of partitioning an image into meaningful
segments. The meaning of the segments is subjective due to the definition of
homogeneity is varied based on the users perspective hence the automation of
the segmentation is challenging. Watershed is a popular segmentation technique
which assumes topographic map in an image, with the brightness of each pixel
representing its height, and finds the lines that run along the tops of ridges.
The results from the algorithm typically suffer from over segmentation due to
the lack of knowledge of the objects being classified. This paper presents an
approach to reduce the over segmentation of watershed algorithm by assuming
that the different adjacent segments of an object have similar color
distribution. The approach demonstrates an improvement over conventional
watershed algorithm.
