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An improved fuzzy algorithm for image segmentation using peak detection, spatial information and reallocation

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Abstract

Image segmentation is a crucial step in image processing, especially for medical images. However, the existence of partial volume effect, noise and other artifacts makes this problem much more complex. Fuzzy c-means (FCM), as an effective tool to deal with partial volume effect, cannot deal with noise and other artifacts. In this paper, one modified FCM algorithm is proposed to solve the above problems, which includes three main steps: (1) peak detection is used to initialize cluster centers, which can make the initial centers close to the final ones and in turn decrease the number of iterations; (2) fuzzy clustering incorporating spatial information is implemented, which can make the algorithm robust to image artifacts; (3) the segmentation results are refined further by detecting and reallocating the misclassified pixels. Experiments are performed on both synthetic and medical images, and the results show that our proposed algorithm is more effective and reliable than other FCM-based algorithms.

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Acknowledgments

The research was supported by NSF of China (61232016, U1405254, 61373078, 61202150, 61472220, 61502218), the Priority Academic Program Development of Jiangsu Higer Education Institutions (PAPD), Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), NSF of Shandong Province (ZR2014FM005, ZR2013FL008), Shandong Province Higher Educational Science and Technology Program (J14N20), Shandong Province Science and Technology Plan Projects (2015GSF116001), and Doctoral Foundation of Ludong University (LY2015035).

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Authors and Affiliations

  1. School of Information and Electrical Engineering, Ludong University, Yantai, 264025, China

    Xiaofeng Zhang, Gang Wang & Qingtang Su

  2. School of Computer Science and Technology, Shandong University, Jinan, 250014, China

    Qiang Guo & Caiming Zhang

  3. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Beijing Chen

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  1. Xiaofeng Zhang
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  2. Gang Wang
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  3. Qingtang Su
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  4. Qiang Guo
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  5. Caiming Zhang
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  6. Beijing Chen
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Correspondence to Xiaofeng Zhang.

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Conflict of interest

Xiaofeng Zhang declares that he has no conflict of interest. Gang Wang declares that he has no conflict of interest. Qingtang Su declares that he has no conflict of interest. Qiang Guo declares that he has no conflict of interest. Caiming Zhang declares that he has no conflict of interest. Beijing Cheng declares that he has no conflict of interest. This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Zhang, X., Wang, G., Su, Q. et al. An improved fuzzy algorithm for image segmentation using peak detection, spatial information and reallocation. Soft Comput 21, 2165–2173 (2017). https://doi.org/10.1007/s00500-015-1920-1

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  • DOI: https://doi.org/10.1007/s00500-015-1920-1

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