Image Segmentation using Biogeography based Optimization and its Comparison with K Means Clustering

Babita Chauhan, Preeti Sondhi

Abstract: Image segmentation plays vital role to understand an image. Only proper understanding of an image tells that what it represents and various objects present in the image. In this project we are using new approach Biogeography Based Optimization for the segmentation of Medical images and its comparison with K means Clustering on the basis of elapsed time in sec. Image segmentation are done with many techniques like PSO, ACO etc. BBO is a Biogeography technique used for image segmentation which provided more accurate segmented images as compared to other optimization method. So BBO can be used in MRI image segmentation to detect any disease. BBO is a population based optimization algorithm and it does not involve reproduction or the generation.

Keywords: Image segmentation, edge detection, fuzzy clustering, thresh-holding, biogeography-based optimization

How to Cite?: Babita Chauhan, Preeti Sondhi, "Image Segmentation using Biogeography based Optimization and its Comparison with K Means Clustering", Volume 10 Issue 9, September 2021, International Journal of Science and Research (IJSR), Pages: 649-652, https://www.ijsr.net/getabstract.php?paperid=MR21912174148, DOI: https://dx.doi.org/10.21275/MR21912174148