00000ctmaa22000003a 4500 UP-1685675941123923277 Buklod 20151013152502.0 aa rb |||1 u| ta 151013s xx d r |||| u| (iLib)UPTAC-00017720385 UPVTC eng LG 993.5 2011 C66 T36 Tan, Christian Roy C. author. ClusterCat color image segmentation using Cat Swarm Optimization algorithm Christian Roy C. Tan; John Paul T. Yusiong, adviser. 2011. [4], 76 leaves illustrations. Undergraduate thesis (B.S. Computer Science) -- University of the Philippines, Tacloban. 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. Image segmentation. Clustering. Swarm Intelligence. Cat Swarm Optimization. Yusiong, John Paul T. adviser. FI UP UPTAC UPTAC LG 993.5 2011 C66 T36 Thesis