ClusterCat color image segmentation using Cat Swarm Optimization algorithm - Tan, Christian Roy C. (2011)
Image segmentation is an important technique in image processing. It is the process of segregating parts of an image into groups that exhibit a common attribute. Many image processing techniques rely on a segmented image since it makes an image more meaningful which, in effect, makes it easier to analyze. Algorithms and approaches for this technique are continually being developed to produce satisfactory results. This research aims to use Cat Swarm Optimization algorithm which is based on the behavior of the cats, to be used in clustering based image segmentation. The RGB component of a pixel in an image was used as the basis for grouping the pixels of the image. Experiment results showed the feasibility of the CSO algorithm in the image segmentation process. CSO was able to segment images in full color and grayscale images and with varying dimensions.