Fast Arclet transform and its application in circle measurement of industrial CT images

LI Zong-jian; ZOU Xiao-bing

doi:10.3788/OPE.20152308.2400

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Fast Arclet transform and its application in circle measurement of industrial CT images

更新时间：2020-08-12

- Fast Arclet transform and its application in circle measurement of industrial CT images
- Optics and Precision Engineering Vol. 23, Issue 8, Pages: 2400-2406(2015)
- 作者机构：
  
  重庆第二师范学院数学与信息工程系重庆,400067
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152308.2400
  CLC： TP391;TG115.281
- Received：07 May 2015，
  
  Revised：09 June 2015，
  
  Published：25 August 2015
- 稿件说明：
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李宗剑, 邹晓兵,. 快速Arclet变换及其在工业CT图像圆测量中的应用[J]. 光学精密工程, 2015,23(8): 2400-2406

LI Zong-jian, ZOU Xiao-bing,. Fast Arclet transform and its application in circle measurement of industrial CT images[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2400-2406
李宗剑, 邹晓兵,. 快速Arclet变换及其在工业CT图像圆测量中的应用[J]. 光学精密工程, 2015,23(8): 2400-2406 DOI： 10.3788/OPE.20152308.2400.

LI Zong-jian, ZOU Xiao-bing,. Fast Arclet transform and its application in circle measurement of industrial CT images[J]. Editorial Office of Optics and Precision Engineering, 2015,23(8): 2400-2406 DOI： 10.3788/OPE.20152308.2400.

摘要

为了准确描述工业CT图像中的圆形结构

提出一种基于多尺度几何分析工具Arclet的圆测量算法。首先

通过分析单尺度Arclet基函数间的空间关系

设计了单尺度快速Arclet数字变换算法;基于该Arclet数字变换

提取出单尺度上的候选圆特征。然后

考虑Arclet相邻尺度基函数间的空间关系并结合多尺度四叉树结构

按照从根到叶的方向

依次对相邻尺度间的候选圆特征进行取舍。最后

融合各尺度剩余的候选圆特征

得到提取结果

并根据提取结果计算出半径等圆参数。基于实际工业CT图像进行了圆测量试验

结果表明

最大半径绝对误差的绝对值< 0.1 mm

最大半径相对误差的绝对值< 0.5%;即使对原工业CT图像引入不同强度的高斯噪声

测量结果依然满足要求。本文提出的工业CT图像圆测量算法对噪声干扰具有很好的抑制能力

能满足准确描述工业CT图像中圆形结构的要求。

Abstract

To accurately describe the circular structures of industrial CT images

a measurement algorithm based on multi-scale geometric analysis tool

named Arclet

was presented. Firstly

a fast mono-scale Arclet numeric transform algorithm was designed through analysis of the spatial relationship between mono-scale Arclet basis functions. Then

the candidate circular features at mono-scale were extracted based on the mono-scale numeric transform transform. By considering the spatial relationship between Arclet basis functions at adjacent scales and the multi-scale tree structure

the candidate circular features between adjacent scales were chosen from a root to leafs. Finally

the surplus circular feature of each scale was fused to obtain the extracted results

and to calculate the related parameters such as radius based on the extracted results. The circle measurement for an actual industrial CT image was performed and the measurement results show that the absolute value of maximum radius absolute error is less than 0.1 mm and that of maximum radius relative error is less than 5%. Even if adding the Gauss noise of different intensities into the original industrial CT image

the measurement results are still can meet the requirements. The measurement algorithm based on fast Arclet transform has better ability to inhibit the noise interference and meet the requirements of industrial CT images for circular structure description.

关键词

Keywords

references

吕宁, 徐更光. 基于工业计算机断层成像的装药底隙无损检测方法研究[J]. 兵工学报,2015,36(1):157-162. LV N, XU G G. Inspection of base separation of charge by industrial CT imaging[J]. ACTA ARMAMENTARII, 2015,36(1):157-162. (in Chinese)

王林元, 刘宏奎, 李磊, 等. 基于稀疏优化的计算机断层成像图像不完全角度重建综述[J]. 物理学报,2014,63(20): 208702. WANG L Y, LIU H K, LI L, et al.. Review of sparse optimization-based computed tomography image reconstruction from few-view projections[J]. Acta Phys. Sin., 2014,63(20):208702. (in Chinese)

黄娅, 徐荣栏, 沈超, 等. 利用计算机断层成像方法由观测图像重建等离子体层全球密度分布——投影数据不完备问题[J]. 地球物理学报,2012,55(4):1071-1077. HUANG Y, XU R L, SHEN CH, et al.. Deduction of the global density of the plasmasphere reconstructed from the observation images using computer tomography technique—Incomplete projection data[J]. Chinese J. Geophys., 2012,55(4):1071-1077. (in Chinese)

刘丰林, 乔桂锋, 邹斌. 工业CT图像圆精确测量[J]. 光学精密工程,2009,17(11):2842-2848. LIU F L, QIAO G F, ZOU B. Precise measurement of circles in industrial computed tomographic images[J]. Opt. Precision Eng., 2009,17(11):2842-2848. (in Chinese)

CANDES E J, DONOHO D L. Curvelets—a surprisingly effective nonadaptive representation for objects with edges[C]. Proceedings of Curve and Surface Fitting, Saint-Malo, Nashville, TN.,1999.

DO M N, VETTERLI M. The contourlet transform: an efficient directional multiresolution image representation[J]. IEEE Transactions on Image Processing. 2005, 14(12): 2091-2106.

ENNEC E L, MALLAT S. Sparse geometric image representations with bandelets[J]. IEEE Transactions on Image Processing,2005, 14(4): 423-438.

DONOHO D L. Wedgelets: nearly-minimax estimation of edges [J]. Annals of Statistics, 1999 27(3): 859-897.

DONOHO D L, HUO X M. Beamlets and multiscale image analysis[C]. Berlin, Germany: Springer Press, 2001, 20: 149-196.

WILLETT R M, NOWAK R D. Platelets: a multiscale approach for recovering edges and surfaces in photon-limited medical imaging[J]. IEEE Transactions on Medical Imaging, 2003, 22(3): 332-350.

CHANDRASEKARAN V, WAKIN M B, BARON D, et al.. Representation and compression of multidimensional piecewise functions using surflets[J]. IEEE Transactions on Information Theory. 2009, 55(1): 374-400.

彭真明, 景亮, 何艳敏, 等. 基于多尺度稀疏字典的多聚焦图像超分辨融合[J]. 光学精密工程,2014,22(1):169-176. PENG ZH M, JING L, HE Y M, et al.. Superresolution fusion of multi-focus image based on multiscale sparse dictionary[J]. Opt. Precision Eng., 2014,22(1):169-176. (in Chinese)

周妍, 李庆武, 霍冠英. 基于非下采样Contourlet变换系数直方图匹配的自适应图像增强[J]. 光学精密工程,2014,22(8):2214-2222. ZHOU Y, LI Q W, HUO G Y. Adaptive image enhancement based on NSCT coefficient histogram matching [J]. Opt. Precision Eng.,2014,22(8):2214-2222. (in Chinese)

龚俊亮, 何昕, 魏仲慧, 等. 基于贝叶斯估计的剪切波域局部自适应图像去噪[J]. 液晶与显示,2013,28(5):799-804. GONG J L, HE X, WEI ZH H, et al.. Local adaptive image denoising based on Bayesian estimation in shearlet domain[J]. Chinese Journal of Liquid Crystals and Displays,2013,28(5):799-804. (in Chinese)

傅瑶, 孙雪晨, 薛旭成, 等. 基于非下采样轮廓波变换的全色图像与多光谱图像融合方法研究[J]. 液晶与显示,2013,28(3):429-434. FU Y, SUN X CH, XUE X CH, et al.. Panchromatic and multispectral image fusion method based on nonsubsampled contourlet transform[J]. Chinese Journal of Liquid Crystals and Displays,2013,28(3):429-434. (in Chinese)

PONGPIYAPAIBOON P. Development of efficient algorithm for geometrical representation based on arclet decomposition[D]. Bavaria:Munich Technology University,2005.

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