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基于增强型哈里斯鹰优化的 Otsu 阈值快速检测坝区边界。

Fast detection of dam zone boundary based on Otsu thresholding optimized by enhanced harris hawks optimization.

机构信息

State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin, 300072, China.

出版信息

PLoS One. 2023 Feb 6;18(2):e0271692. doi: 10.1371/journal.pone.0271692. eCollection 2023.

Abstract

Earth-rock dams are among the most important and expensive infrastructure projects. A key safety issue is dam zone boundary detection to prevent the intrusion of materials from different zones. However, existing detection methods strongly highly depend on human judgement, which is time consuming and labor intensive. To solve this problem, this work proposes a fast boundary detection method based on the Otsu algorithm optimized by enhanced Harris hawks optimization (HHO). Compared with the original Otsu algorithm, the proposed method has a higher computation speed to meet the time requirements of engineering projects. Particle swarm optimization is adopted to enhance the exploration stage of HHO. In addition, a tangent function and chaotic sine map are used to improve the convergence speed and robustness. The application of the proposed method to a real-life project shows that the calculation time can be reduced to 20 s, which is approximately 18.8% of the original calculation time.

摘要

土石坝是最重要和最昂贵的基础设施项目之一。一个关键的安全问题是坝区边界检测,以防止不同区域的材料侵入。然而,现有的检测方法严重依赖于人工判断,既耗时又费力。为了解决这个问题,本工作提出了一种基于 Otsu 算法的快速边界检测方法,该方法通过增强型哈里斯鹰优化(HHO)进行了优化。与原始的 Otsu 算法相比,所提出的方法具有更高的计算速度,可以满足工程项目的时间要求。采用粒子群优化来增强 HHO 的探索阶段。此外,使用正切函数和混沌正弦映射来提高收敛速度和鲁棒性。将该方法应用于实际工程表明,计算时间可以减少到 20s,大约是原始计算时间的 18.8%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2784/9901759/9271afd3aada/pone.0271692.g001.jpg

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