Segmentation of Images on the Basis of Algorithm of Communities Separation on the Graph
In the article we propose the image segmentation algorithm using its representation as an undirected weighted graph, followed by separation of the communities on the graph. Each community corresponds to the image segment. The function of the difference between the intensity of the colors in the space of RGB increasing exponentially is used as the measure of arcs weight. To separate the communities a greedy algorithm is built. The modularity function introduced by Newman is used to assess the quality of the graph separation into communities. Computer experiment is provided. It is shown that segments sizes depend on the parameter value in the edges weight function. The proposed algorithm is robust to impulse noise.