An Efficient Agglomerative Algorithm Cooperating with Louvain Method for Implementing Image Segmentation

Abstract

The idea that brings social networks analysis domain into image segmentation quite satisfies with most authors and harmony in those researches. However, the community detection based image segmentation often produces over-segmented results. To address this problem, we propose an efficient agglomerative homogeneous regions algorithm by considering image histograms which are contributed into bins of the color group properties. Our method is tested on the publicly available Berkeley Segmentation Dataset. And experimental results show that the proposed algorithm produces sizable segmentation and outperforms almost other known image segmentation methods in term of accuracy and comparative PRI scores.