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Spiking Neural P System with weight model of majority voting technique for reliable interactive image segmentation

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Abstract

Interactive image segmentation is a method for precisely segmenting of the object from background using information entered by the user. However, most interactive segmentation techniques are sensitive to the location and the number of seed points. To obtain a satisfactory result, the user should repeat the segmentation process over and over, and also based on employed technique, it may work well in some limited conditions and applications. To overcome these limitations and enhance the robustness of interactive image segmentation algorithm, this paper proposes a parallel fusion model using the majority voting technique, which not only is more reliable than existing methods, but also requires less user interaction. To this end, at first the input image is segmented by several segmentation methods independently. Then the obtained results are combined using majority voting technique to extract final segmentation result. To reduce the computational overhead of the proposed scheme, a spiking neural-like P system model for parallel implementation of majority voting technique is also proposed. The proposed model has been evaluated and compared with state-of-the-art methods using different metrics, and the obtained results show its efficiency compared to other methods.

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Funding

(Information that explains whether and by whom the research was supported): No funds, grants, or other support was received for this study.

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Authors and Affiliations

  1. Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran

    Mehran Dalvand, Abdolhossein Fathi & Arezoo Kamran

Authors
  1. Mehran Dalvand
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  2. Abdolhossein Fathi
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  3. Arezoo Kamran
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Contributions

All authors contributed to the study conceptualization and design. Material preparation, data collection, analysis and writing of the first draft of paper were performed by Mehran Dalvand. The supervision and writing, review and editing of the manuscript were done by Abdolhossein Fathi and Arezoo Kamran. All authors read and approved the final manuscript.

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Correspondence to Abdolhossein Fathi.

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Dalvand, M., Fathi, A. & Kamran, A. Spiking Neural P System with weight model of majority voting technique for reliable interactive image segmentation. Neural Comput & Applic 35, 9035–9051 (2023). https://doi.org/10.1007/s00521-022-08162-9

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  • DOI: https://doi.org/10.1007/s00521-022-08162-9

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