ABSTRACT
Image segmentation is a critical, yet essential task in many applications. Segmentation subdivides an image into a set of homogeneous and meaningful regions, such that the pixels in each partitioned region possess identical set of properties or attributes and the union of any two adjacent regions is non-homogeneous (Gonzalez and Woods, 2002). The set of properties may include gray levels, color, contrast, spectral values, or textural properties. The color image segmentation has gained paramount importance in recent times largely due to the availability inexpensive digital cameras, increasing computational power of the computers and decreasing cost of computation. The applications of color image segmentation include medical image diagnostics, video object segmentation, object based video compression, object detection from remotely sensed images, and many more.
