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Local reverse entropy weighted LBF model solving by Split Bregman for image segmentation

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Abstract

In this paper, an efficient level set model is proposed for image segmentation. Firstly, the original local binary fitting (LBF) model is redefined as a weighted energy integral, whose weight coefficient is the fast local reverse entropy of the image, and the total energy functional is then incorporated into a variational level set formulation. Secondly, the global convex segmentation method is used to construct a simplified convex segmentation model, at the same time, the edge information obtained by an edge indicator function is embedded into the total variation norm to further enhance the model’s target capture capability. Thirdly, the Split Bregman method is introduced to solve the generated convex optimization problem. Experimental results on synthetic and real images demonstrate that the proposed model has considerable improvements in terms of quantitative evaluation (being verified on the complete PASCAL VOC 2012 dataset), convergence rate, sensitivity to initial contour and robustness to noise interference compared with the state-of-the-art models. We also compare the proposed model with the famous FCN and Mask R-CNN, and make a special analysis on the adaptability of our method to occluded targets.

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Acknowledgements

This work is supported by the Fundamental Research Funds for the Central Universities of China under Grant No. ZYGX2018J079. The authors gratefully acknowledge the financial support from China Scholarship Council (CSC) under Grant No. 201706075068. The authors would like to thank the anonymous reviewers for their valuable comments and advices.

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Authors and Affiliations

  1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Dengwei Wang

  2. Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu, 611731, China

    Dengwei Wang

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  1. Dengwei Wang
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Correspondence to Dengwei Wang.

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Wang, D. Local reverse entropy weighted LBF model solving by Split Bregman for image segmentation. Multimed Tools Appl 79, 23669–23693 (2020). https://doi.org/10.1007/s11042-020-09094-z

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