测绘通报 ›› 2017, Vol. 0 ›› Issue (3): 13-16.doi: 10.13474/j.cnki.11-2246.2017.0074

• 学术研究 • 上一篇    下一篇

基于方向膨胀的核安全壳锈蚀识别算法

徐亚明1,2, 孙雪妍1, 王震1, 喻爽3   

  1. 1. 武汉大学测绘学院, 湖北 武汉 430079;
    2. 精密工程与工业测量国家测绘地理信息局重点实验室, 湖北 武汉 430079;
    3. 武汉市测绘研究院, 湖北 武汉 430079
  • 收稿日期:2016-07-12 修回日期:2017-01-03 出版日期:2017-03-25 发布日期:2017-03-31
  • 作者简介:徐亚明(1964-),男,教授,博士生导师,主要从事精密工程测量和近景摄影测量研究工作。E-mail:1539715830@qq.com
  • 基金资助:
    国家自然科学基金(41474005);现代城市测绘国家测绘地理信息局重点实验室开放课题(20131205WY)

Rusting Recognition Algorithm for the Containment of the Nuclear Power Plant Based on Contour Directed Dilation

XU Yaming1,2, SUN Xueyan1, WANG Zhen1, YU Shuang3   

  1. 1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    2. Key Laboratory of Precise Engineering and Industry Surveying, National Administration of Surveying, Mapping and Geoinformation, Wuhan 430079, China;
    3. Wuhan Geomatic Institute, Wuhan 430079, China
  • Received:2016-07-12 Revised:2017-01-03 Online:2017-03-25 Published:2017-03-31

摘要: 核安全壳锈蚀影像噪声密集,锈蚀缺损严重,颜色相似的干扰强。本文提出了一种基于方向膨胀的锈蚀识别算法。利用锈蚀的黄橙色特征对影像进行RGB三通道阈值分割提取锈蚀基础信息,根据锈蚀的圆环形态特征,按照轮廓延伸方向进行多角度分块。设计了八方向膨胀核,对相应轮廓块进行不同方向膨胀以补全圆环轮廓,计算轮廓矩进行圆度识别。试验证明,该算法能滤除大量噪声和颜色相似的干扰信息,正确识别并定位锈蚀。

关键词: 锈蚀识别, 阈值分割, 方向膨胀, 圆度识别, 锈蚀定位

Abstract: For defective rusting on nuclear containment image, with lots of noise and interference similar in color, in this paper a rusting recognition algorithm of contour directed dilation is proposed. Using the characteristic yellowish orange color, extract basic rusting information through RGB multi-channel threshold segmentation. On the basis of rusting's annulus shape feature, the rusting by multi-direction according to contour's extension direction is divided. Contour fragment is dilated by the self-design eight-direction kernels in order to complement annulus rusting. The real rusting is recognized by roundness calculated according to contour moments. Experiments show that the algorithm can undo amounts of noise and interference similar in color so as to recognize and position the real rusting on the image.

Key words: rusting recognition, threshold segmentation, directed dilation, roundness recognition, rusting position

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