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面向刀具磨损图像区域分割的改进分水岭算法

刘建军 刘丽冰 彭伟尧 张艳蕊 杨泽青

刘建军, 刘丽冰, 彭伟尧, 张艳蕊, 杨泽青. 面向刀具磨损图像区域分割的改进分水岭算法[J]. 机械科学与技术, 2020, 39(5): 729-735. doi: 10.13433/j.cnki.1003-8728.20190196
引用本文: 刘建军, 刘丽冰, 彭伟尧, 张艳蕊, 杨泽青. 面向刀具磨损图像区域分割的改进分水岭算法[J]. 机械科学与技术, 2020, 39(5): 729-735. doi: 10.13433/j.cnki.1003-8728.20190196
Liu Jianjun, Liu Libing, Peng Weiyao, Zhang Yanrui, Yang Zeqing. An Improved Watershed Algorithm for Segmenting Tool Wear Images[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(5): 729-735. doi: 10.13433/j.cnki.1003-8728.20190196
Citation: Liu Jianjun, Liu Libing, Peng Weiyao, Zhang Yanrui, Yang Zeqing. An Improved Watershed Algorithm for Segmenting Tool Wear Images[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(5): 729-735. doi: 10.13433/j.cnki.1003-8728.20190196

面向刀具磨损图像区域分割的改进分水岭算法

doi: 10.13433/j.cnki.1003-8728.20190196
基金项目: 

天津市自然科学基金项目 16JCYBJC19100

河北省自然科学基金项目 E2017202294

国家自然科学基金项目 51305124

河北省科技计划项目 16211803D

详细信息
    作者简介:

    刘建军(1996-), 硕士研究生, 研究方向为数控机床刀具视诊、数字图像处理, junlcr7@163.com

    通讯作者:

    张艳蕊, 高级实验师, 硕士, 研究方向为健康监控, 2008021@hebut.edu.cn

  • 中图分类号: TH166

An Improved Watershed Algorithm for Segmenting Tool Wear Images

  • 摘要: 原始刀具图像通常存在背景纹理复杂、噪声大等问题,导致磨损区域分割结果的准确性较差,为此本文提出了一种基于形态学成分分析(MCA)的改进分水岭算法,用于提取刀具磨损区域并估算其面积。首先分析了刀具磨损图像各组成成分的形态差异;然后研究了各成分对应字典的选取方法,将原始刀具图像分解成目标刀具图像、背景图像和噪声;最后对目标刀具图像使用分水岭算法提取磨损区域并估算面积。以铣刀磨损图像作为样本完成了多次方法验证,结果表明:传统分水岭算法的检测误差为80%左右,而该方法的检测误差为5%以下,可见使用该算法可以分割得到更加准确的磨损区域。
  • 图  1  基于MCA的改进分水岭算法流程图

    图  2  铣刀图像的MCA分解模型

    图  3  实验装置及刀具磨损测量

    图  4  铣刀图像的MCA分解结果

    图  5  传统分水岭算法和基于MCA的改进分水岭算法的分割结果

    表  1  刀具图像磨损面积估算

    图像 手工 传统分水岭算法 本文算法
    磨损区域面积/μm2 错检率/% 磨损区域面积/μm2 错检率/%
    1 5 962.47 31 142.84 80.85 5 702.34 4.56
    2 31 074.39 168 351.98 81.54 30 162.10 3.02
    3 32 857.95 152 938.26 78.52 32 762.11 0.29
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-05-06
  • 刊出日期:  2020-05-05

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