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Image segmentation is an important
pre-processing step towards higher level tasks such as object recognition,
computer vision or image compression. Most of the existing segmentation
algorithms deal with grayscale images only. But in the modern world, color
images are extensively used in many situations. A new approach for color image
segmentation is presented in this paper. There are many ways to deal with image
segmentation problem and in these techniques; a particular class of algorithms
traces their origin from region-based methods. These algorithms group
homogeneous pixels, which are connected to primitive regions. They are easy to
implement and are promising. Therefore, here one of the most efficient
region-based segmentation algorithms is explained. The color image is quantized
adaptively, using a wavelet transform. Then the region growing process is
adopted. As preprocess, before actual region merging, small regions are
eliminated by merging them with neighbor regions depending upon color
similarity. After this, homogeneous regions are merged to get segmented output.