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Multi-threshold image segmentation of 2D OTSU inland ships based on improved genetic algorithm

Author

Listed:
  • Zhongbo Peng
  • Lumeng Wang
  • Liang Tong
  • Han Zou
  • Dan Liu
  • Chunyu Zhang

Abstract

Waterway transportation is a crucial mode of transportation, but ensuring navigational safety in waterways requires effective guidance of ships by the Water Resources Bureau. However, supervisors may only be interested in the ship portion of a complex image and need to quickly obtain relevant ship information. Therefore, this paper proposes a two-dimensional OTSU inland ships multi-threshold image segmentation algorithm based on the improved genetic algorithm. The improved algorithm enhances search accuracy and efficiency, improving image thresholding accuracy and reducing algorithm time complexity. Experimental verification shows the algorithm has excellent evaluation indexes and can achieve real-time segmentation of complex images. This method can not only address the challenges of complex inland navigation environments and difficult acquisition of target data sets, but also be applied to optimization problems in other fields by combining various metaheuristic algorithms.

Suggested Citation

  • Zhongbo Peng & Lumeng Wang & Liang Tong & Han Zou & Dan Liu & Chunyu Zhang, 2023. "Multi-threshold image segmentation of 2D OTSU inland ships based on improved genetic algorithm," PLOS ONE, Public Library of Science, vol. 18(8), pages 1-17, August.
    • Handle: RePEc:plo:pone00:0290750
    DOI: 10.1371/journal.pone.0290750
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