Abstract
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.