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A novel method for image segmentation using reaction–diffusion model

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Abstract

We propose an image segmentation model that is derived from reaction–diffusion equations and level set methods. In our model, a diffusion term is used for regularization of a level set function, and a reaction term has the desired sign property to force the level set function to move up or down and finally identify an object and its background. Our level set function can be initialized to any bounded function (e.g., a constant function). The proposed model can be applied to a wider range of images with promising results, especially for real images that have high noise and blurred boundaries. This study gives a new method for the further investigations of reaction–diffusion equations directly for segmentation.

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Acknowledgments

This work was supported by the Natural Science Foundation of Jiangxi Province (Grant No. 20142BAB217012), the National Natural Science Foundation of China (Grant Nos. 61462032, 61502399 and 61461021), Natural Science Foundation Project of Chongqing CSTC (Grant No. cstc2015jcyjA40039), the Fundamental Research Funds for the Central Universities (XDJK2015C077), and SRF for ROCS, SEM.

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Authors and Affiliations

  1. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, 330013, China

    Wenying Wen

  2. College of Mathematics and Statistics, Chongqing University, Chongqing, 401331, China

    Chuanjiang He

  3. School of Electronics and Information Engineering, Southwest University, Chongqing, 400715, China

    Yushu Zhang

  4. College of Electronic and Electrical Engineering, Shanghai university of Engineering Science, Shanghai, 201620, China

    Zhijun Fang

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  1. Wenying Wen
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  2. Chuanjiang He
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Correspondence to Wenying Wen.

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Wen, W., He, C., Zhang, Y. et al. A novel method for image segmentation using reaction–diffusion model. Multidim Syst Sign Process 28, 657–677 (2017). https://doi.org/10.1007/s11045-015-0365-0

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  • DOI: https://doi.org/10.1007/s11045-015-0365-0

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