计算机科学 ›› 2025, Vol. 52 ›› Issue (6A): 240700089-7.doi: 10.11896/jsjkx.240700089
费春国, 陈世洪
FEI Chunguo, CHEN Shihong
摘要: 在基于图像处理分割机场跑道异物(FOD)的方法中,基于深度学习的方法不能准确感知未经训练的异物。对此,提出基于双通道麻雀改进大津法(OTSU)的分割方法(DS-OTSU)来分割感知异物。该分割方法将麻雀搜索算法与OTSU相结合,在麻雀搜索算法中加入佳点集优化初始种群,同时在双通道中分别加入正反两个方向的扰动,从而改变麻雀搜索算法目标函数的计算方法,通过加入双重动态的萤火虫扰动改变种群更新方式,将双通道的运行结果进行对比融合,将原本只能单阈值分割图像的OTSU优化为可以分割阈值段的方法,滤除图像背景部分,最终得到FOD的分割结果。实验分析表明,所提方法在分割精度和收敛速度上均优于其他方法。
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