A New Image Segmentation Approach Based on the Louvain Algorithm
Thanh-Khoa Nguyen, Mickaël Coustaty, Jean‐Loup Guillaume · 2018
This paper presents an image segmentation strategy using an idea coming from the social networks analysis domain. This strategy relies on the use of community detection algorithms in order to cluster pixels that belong to the same group of information. The main issue with this approach is that community detection based image segmentation often leads to over-segmented results. In order to address this problem, we propose an algorithm that agglomerates homogeneous regions using their color properties. Our algorithm is tested on the publicly available Berkeley Segmentation Dataset and experimental results show that the proposed algorithm produces sizable segmentation and achieves object-level segmentation to some extent.