Journals Proceedings

Abstract

Image Segmentation and its performance evaluation are very difficult but important problems in computer vision. Image segmentation, i.e., identification of homogeneous regions in the image, has been the subject of considerable research activity over the last three decades. Many algorithms have been elaborated for Colour Image Segmentation. This Paper elaborate a global optimization method Biogeography-based optimization for automatically grouping the pixels of an color image into disjoint homogenous regions. Biogeography is the study of the distribution of animals and plants over time and space. It generates different clusters from a desired input image that share certain visual characteristics such as colours, intensity or texture pattern. This proposed algorithm computes performance evaluation in terms of migration rate such as 0.4 as compared to other evolutionary algorithm (Generic algorithm). One Biogeography Based Optimization characteristic which makes it distinctive from Genetic Algorithm is its migration mechanism, which affects selection pressure. It has good optimization performance due to its migration operator. It also provides noise free image and compute fast computational speed as compared to other algorithm in terms of 1.28 seconds. Therefore, Biogeography Based Image Segmentation is more reliable and faster for Image Segmentation.