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Multi-feature driven active contour segmentation model for infrared image with intensity inhomogeneity

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Abstract

Active contour model is one of the most widely used image segmentation tools at present, but the existing methods only utilize single feature information of image to minimize the energy function, which is easy to cause false segmentations in infrared (IR) images. In this paper, we propose a multi-feature driven active contour segmentation model to handle IR images with intensity inhomogeneity. Firstly, an especially-designed signed pressure force (SPF) function is constructed by combining the global information calculated by global average gray information and the local multi-feature information calculated by local entropy, local standard deviation and gradient information. Then, we draw upon adaptive weight coefficient computed by local range to incorporate the afore-mentioned global term and local term. Next, the SPF function is substituted into the level set formulation (LSF) for further evolution. Finally, the LSF converges after a finite number of iterations and the IR image segmentation result is obtained from the corresponding convergence result. Experimental results demonstrate that the presented method outperforms typical models in terms of precision rate and overlapping rate in IR test images. The code is available at: https://github.com/MinjieWan/MFDACM.

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Acknowledgements

This research was supported by National Natural Science Foundation of China (No. 62001234), Natural Science Foundation of Jiangsu Province (No. BK20200487), China Postdoctoral Science Foundation (No. 2020M681597), Postdoctoral Science Foundation of Jiangsu Province (No. 2020Z051), Shanghai Aerospace Science and Technology Innovation Foundation (No. SAST2020-071), and the Fundamental Research Funds for the Central Universities (No. JSGP202102).

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Authors and Affiliations

  1. Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing University of Science and Technology, Nanjing, 210094, China

    Qinyan Huang, Minjie Wan, Xin Chen, Kan Ren, Qian Chen & Guohua Gu

  2. Shanghai Institute of Spaceflight Control Technology, Shanghai, 201109, China

    Weiwen Zhou

Authors
  1. Qinyan Huang
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  2. Weiwen Zhou
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  3. Minjie Wan
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  4. Xin Chen
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  5. Kan Ren
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  6. Qian Chen
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  7. Guohua Gu
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Correspondence to Minjie Wan or Guohua Gu.

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Huang, Q., Zhou, W., Wan, M. et al. Multi-feature driven active contour segmentation model for infrared image with intensity inhomogeneity. Opt Quant Electron 53, 367 (2021). https://doi.org/10.1007/s11082-021-03000-z

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