基于自适应阈值法的合金弹头缺陷尺寸测量算法研究

韩婧, 陈友兴

韩婧, 陈友兴. 基于自适应阈值法的合金弹头缺陷尺寸测量算法研究[J]. 应用光学, 2013, 34(5): 841-844.
引用本文: 韩婧, 陈友兴. 基于自适应阈值法的合金弹头缺陷尺寸测量算法研究[J]. 应用光学, 2013, 34(5): 841-844.
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HAN Jing, CHEN You-xing. Measurement methods of warhead scratch defect size based on adaptive threshold[J]. Journal of Applied Optics, 2013, 34(5): 841-844.
Citation: HAN Jing, CHEN You-xing. Measurement methods of warhead scratch defect size based on adaptive threshold[J]. Journal of Applied Optics, 2013, 34(5): 841-844.
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基于自适应阈值法的合金弹头缺陷尺寸测量算法研究

  • 1.

    中北大学仪器科学与动态测试重点实验室,山西 太原 030051;

  • 2.

    中北大学信息与通信工程学院,山西 太原 030051

详细信息
    通讯作者:

    韩婧(1987-), 女, 山西太原人，硕士研究生, 主要从事信号与信息处理技术研究。 Email:panggeniuniu@163.com

  • 中图分类号: TN215

Measurement methods of warhead scratch defect size based on adaptive threshold

  • 1.

    Key Laboratory of Instrumentation Science &Dynamic Measurement,North University of China,Taiyuan 030051,China;

  • 2.

    School of Information and Communication Engineering,North University of China,Taiyuan 030051,China

摘要

    摘要
  • 摘要: 在合金弹头缺陷尺寸检测中，针对传统分割算法无法在复杂背景下将缺陷完整分割的问题，采用了自适应阈值分割算法。该算法在分割时，图像的每个像素对应的阈值不同，可避免缺陷和背景错误划分，而且可以在保证缺陷完整分割的情况下避免噪声带来的干扰。给出了缺陷分割过程，完成了缺陷尺寸计算，并对尺寸计算的准确度进行了分析。实验结果表明，在缺陷与背景灰度差较小的情况下，该算法仍可较为完整地将缺陷分割出来，测量结果的标准差为0.122 8，不确定度为0.368 4。
    Abstract: As it cannot integrally divide the defects under the complex background by the traditional measurement methods of the warhead scratch defect size, the method of adaptive threshold segmentation is used to solve this problem. Using this method for image segmentation, each pixel of the image corresponds to the different threshold, it can avoid the error division between defects and background, and the noise interference can also be avoid when the defects are completely divided. Defect segmentation process are given, the defect size is calculated, and the precision of the size measurement is analyzed. Experimental results shows that the defects can be completely divided by this methods when the gray level are different between the defects and the background, standard error is 0.122 8, and the uncertainty is 0.368 4.
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  • 刊出日期:  2013-09-14

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