The region based MMTD energy function for image segmentation

  • Bing Han
  • Lixia Zhang
  • Xinbo Gao


This paper presents a region-based model based on measure of medium truth degree for image segmentation. Firstly, a new energy function based on measure of medium truth degree is constructed. To enhance the robustness against noise, a noise penalty term which is built by spatial distance measure is embedded to the conventional active contour energy function. Then local information is added to the internal and external energy term of the conventional active contour energy function to deal with intensity inhomogeneity images. Finally, to obtain more accurate and smoother boundary, a new stop function is introduced into the boundary smooth term of the conventional active contour energy function. Experiments results demonstrate that relatively complete and accurate boundaries can be obtained by the proposed model compared with the state-of-art methods on aurora images, images with intensity inhomogeneity, images with multi-objects, natural images, medical images.


Graph cuts Measure of medium truth degree Local information Spatial distance measure 



This work was supported in part by the National Natural Science Foundation of China under Grant U1605252, in part by the National Key Research and Development Program of China under Grant 2016QY01W0200, the National Natural Science Foundation of China(41031064; 61572384; 61432014), China’s postdoctoral fund first-class funding (2014M560752), Shanxi province postdoctoral science fund, the central university basic scientific research business fee (JBG150225), ShanXi Key Technologies Research Program(2017KW-017).


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Electronic EngineeringXidian UniversityXi’anChina

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