冰形表面激光光带中心线快速提取方法

康含玉; 刘桂华; 王斌; 牛乾

doi:10.11729/syltlx20170058

冰形表面激光光带中心线快速提取方法

doi: 10.11729/syltlx20170058

康含玉^1, ,,
刘桂华¹,
王斌^{2, 3},
牛乾¹

1.
西南科技大学信息工程学院, 四川绵阳 621000
2.
中国空气动力研究与发展中心设备设计及测试技术研究所, 四川绵阳 621000
3.
中国空气动力研究与发展中心空气动力学国家重点实验室, 四川绵阳 621000

基金项目:

国家自然科学基金 11602292

四川省科技厅科技支撑项目 2016GZ0183

详细信息

作者简介:
康含玉(1990-), 女, 河南平顶山人, 硕士研究生。研究方向:图像处理、机器视觉。通信地址:四川省绵阳市涪城区西南科技大学东七A座(博雅轩)(621000)。E-mail:360613216@qq.com

通讯作者:
康含玉, E-mail:360613216@qq.com

中图分类号: V211.752
计量
- 文章访问数: 252
- HTML全文浏览量: 118
- PDF下载量: 8
- 被引次数: 0
出版历程
- 收稿日期: 2017-05-10
- 修回日期: 2017-07-17
- 刊出日期: 2017-10-25

A fast method of extracting the laser light bar's centerline in the ice model

Kang Hanyu^{1
, ,},
Liu Guihua¹,
Wang Bin^{2, 3},
Niu Qian¹

1.
School of Information Engineering, University of Southwest Science and Technology, Mianyang Sichuan 621000, China
2.
Facility Design and Instrumentation Institute, China Aerodynamics Research and Development Center, Mianyang Sichuan 621000, China
3.
State Key Loboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang Sichuan 621000, China

摘要

摘要: 在风洞结冰模型3D冰形测量中，激光三角测量法相对传统测量方法检测速度快、精确度高，具有极高研究价值。然而由于冰体对激光透射严重，影响激光中心线提取精度从而影响测量精度。针对此问题，提出一种冰形表面激光光带中心线快速提取方法。该算法具体实现步骤为：首先，采用基于三维块匹配去噪算法对图像进行降噪，并对图像进行视觉显著性计算，分割出光带区域；其次，求取梯度图并转换至频域空间，根据图像频谱特征求取能量中心区域；最后，对区域采用灰度重心法求取中心线亚像素级位置。采用冰箱冻结的半径已知圆柱冰块评估该算法，测得算法处理时效为28.57FPS，使用该算法的冰形轮廓重建精度达到0.017mm。实验证明算法满足冰形在线测量技术要求，为开展结冰实验中结冰生长过程在线三维检测技术奠定技术基础。
- 结冰模型 /
- 图像处理 /
- 显著图 /
- 中心线提取 /
- 频域变换
Abstract: The laser centerline extraction is an important step in the measurement of the ice cross sectional profile, and the extraction accuracy directly affects the accuracy of the measurement system. Especially the ice on the structural light transmission is serious, the center line extraction algorithm is put forward a higher requirement. A fast centerline extraction method based on frequency domain transform is proposed to extract the center line in the three-dimensional measurement of ice. First, the image is subjected to noise reduction based on the technique of Block-matching and 3D filtering. Second, in order to reduce the computational complexity, the visual significance of the image is calculated by using the quaternion Fourier transform of phase spectrum, and then extract the optical band's region. Third, obtain the gradient map and convert to the frequency domain space, according to the image spectrum characteristics, we can obtain the center line position. The experimental results show that the algorithm is 28.57FPS, and the accuracy of ice contour reconstruction is 0.017mm.
- icing model /
- image processing /
- significant figure /
- centerline extraction /
- frequency domain transform

HTML全文

图 1 激光刀切法冰形三维轮廓测量原理

Figure 1. The principle of 3D contour measurement of ice-cutting

下载: 全尺寸图片幻灯片

图 2 冰体表面激光投射效果图以及3D显示

Figure 2. The laser onto the ice model and 3D display effect

下载: 全尺寸图片幻灯片

图 3 BM3D去噪流程

Figure 3. Process of BM3D denoising

下载: 全尺寸图片幻灯片

图 4 去噪效果对比

Figure 4. Filtering effect

下载: 全尺寸图片幻灯片

图 5 视觉显著性提取结果

Figure 5. Visual significance extraction

下载: 全尺寸图片幻灯片

图 6 硬件实验平台

Figure 6. ardware experiment platform

下载: 全尺寸图片幻灯片

图 7 圆柱体冰块测量图像(a)及激光中心线提取结果(b)

Figure 7. The captured laser line image (a)on cylindrical ice surface and the extracted center-line (b)of laser line image

下载: 全尺寸图片幻灯片

图 8 单条激光线重建结果对比

Figure 8. Comparison the results of single laser light reconstruction

下载: 全尺寸图片幻灯片

图 9 算法性能对比图

Figure 9. Algorithm performance comparison

下载: 全尺寸图片幻灯片

表 1 算法耗时

Table 1. Time-consuming

Methods	Time/ms
Ours	35
Skeleton extraction	58
Gradient center of gravity	200
Steger based on Hessian Matrix	650

下载: 导出CSV

表 2 基于不同中心线提取算法的重建精度

Table 2. Reconstruction accuracy

Methods	Accuracy /mm
Ours	0.017
Skeleton extraction	0.045
Gradient center of gravity	0.018
Steger based on Hessian Matrix	0.015

下载: 导出CSV

参考文献(17)

[1]	Lynch F T, Khodadoust A. Effects of ice accretions on aircraft aerodynamics[J]. Progress in Aerospace Sciences, 2001, 37(8):669-767. doi: 10.1016/S0376-0421(01)00018-5
[2]	巫瑞锐. 结冰力学特性的理论与实验研究[D]. 南京: 南京航空航天大学, 2014. Wu R R. Research on theories and experiments of mechanical properties of impact ice[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2014.
[3]	范洁川, 于涛.飞机结冰风洞试验模拟研究[J].实验流体力学, 2007, 21(1):1-7. http://www.syltlx.com/CN/abstract/abstract9525.shtml Fan J C, Yu T. A study of simulation for airplane icing tests in icing wind tunnel[J]. Journal of Experiments in Fluid Mechanics, 2007, 21(1):1-7. http://www.syltlx.com/CN/abstract/abstract9525.shtml
[4]	易贤. 飞机积冰的数值计算与积冰试验相似准则研究[D]. 绵阳: 中国空气动力研究与发展中心, 2007. Yi X. Numerical computation of aircraft icing and study on icing test scaling law[D]. Mianyang:China Aerodynamics Research and Development Center, 2007.
[5]	Gong X L, Bansmer S. 3-D ice shape measurements using mid-infrared laser scanning[J]. Optics Express, 2015, 23(4):4908-4926. doi: 10.1364/OE.23.004908
[6]	王斌, 刘桂华, 张利萍, 等.基于线结构光的冰横截面轮廓测量[J].实验流体力学, 2016, 30(3):14-20. http://www.syltlx.com/CN/abstract/abstract10928.shtml Wang B, Liu G H, Zhang L P, et al. Ice cross sectional profi-le measurement based on line structured light[J]. Journal of Experiments in Fluid Mechanics, 2016, 30(3):14-20. http://www.syltlx.com/CN/abstract/abstract10928.shtml
[7]	Tsai R Y. An efficient and accurate camera calibration technique for 3D machine vision[C]//Proceeding of IEEE Conference on Computer Vision & Pattern Recognition, 1986:364-374.
[8]	Zhang Z. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11):1330-1334. doi: 10.1109/34.888718
[9]	Zhou F, Zhang G. Complete calibration of a structured light vision sensor through planar target of unknown otientations[J]. Image and Vision Computing, 2005, 23(1):59-67. doi: 10.1016/j.imavis.2004.07.006
[10]	Saeed K, Dzki M, Rybnik M, et al. A universal algorithm for image skeletonization and a review of thinning thchniques[J]. International Journal of Applied Mathmatics & Computer Science, 2010, 20(2):317-335. https://www.degruyter.com/view/j/amcs.2010.20.issue-2/v10006-010-0024-4/v10006-010-0024-4.xml
[11]	苏小勤, 熊显名.快速线结构光中心线提取算法[J].计算机应用, 2016, 36(1):238-242. doi: 10.11772/j.issn.1001-9081.2016.01.0238 Su X Q, Xiong X M. High-speed method for extracting center of line structured light[J]. Journal of Computer Applications, 2016, 36(1):238-242. doi: 10.11772/j.issn.1001-9081.2016.01.0238
[12]	吴家勇.基于梯度重心法的线结构光中心亚像素提取方法[J].中国图像图形学报, 2009, 14(7):1354-1360. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB200907022.htm Wu J Y. Method of linear structured light sub-pixel center position extracting[J]. Journal of Image and Graphics, 2009, 14(7):1354-1360. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB200907022.htm
[13]	Steger C. Extracting curvilinear structures:a differential geometric approach[J]. Computer Vision-ECCV'96 Lecture Notes in Computer Science, 1996, 1064:630-641. doi: 10.1007/BFb0015518
[14]	Steger C. An unbiased detector of curvilinear structures[J]. IEEE Transactions on Pattern Analysis and machine Intelligence, 1998, 20(2):113-125. doi: 10.1109/34.659930
[15]	Dabov K, Foi A, Egiazarian K. Image denoising with block-matching and 3D filtering[J]. The International Society for Optical Engineering, 2006, 6064:354-365. http://www.cs.tut.fi/~foi/3D-DFT/
[16]	汪成. 图像显著区域检测算法研究[D]. 南京: 南京信息工程大学, 2016. http://cdmd.cnki.com.cn/Article/CDMD-10300-1016197870.htm Wang C. Research of saliency region detection of images[D]. Nanjing:Nanjing University of Information Science & Technology, 2016. http://cdmd.cnki.com.cn/Article/CDMD-10300-1016197870.htm
[17]	Itti L, Koch C, Niebur E. A model of saliency based visual attention for rapid scene analysis[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1998, 20(11):1254-1259. http://ieeexplore.ieee.org/abstract/document/730558/