Volume 46 Issue 10
Nov.  2017
Turn off MathJax
Article Contents
Article Navigation >  Infrared and Laser Engineering  > 2017  >  46(10): 1017010-1017010(8)

Liu Wei, Zhang Yang, Gao Peng, Yang Fan, Lan Zhiguang, Li Xiaodong, Jia Zhenyuan, Gao Hang. Sub-pixel center extraction method of laser stripe center based on hierarchical processing[J]. Infrared and Laser Engineering, 2017, 46(10): 1017010-1017010(8). doi: 10.3788/IRLA201778.1017010
Citation: Liu Wei, Zhang Yang, Gao Peng, Yang Fan, Lan Zhiguang, Li Xiaodong, Jia Zhenyuan, Gao Hang. Sub-pixel center extraction method of laser stripe center based on hierarchical processing[J]. Infrared and Laser Engineering, 2017, 46(10): 1017010-1017010(8). doi: 10.3788/IRLA201778.1017010
shu

Sub-pixel center extraction method of laser stripe center based on hierarchical processing

doi: 10.3788/IRLA201778.1017010
  • 1.

    School of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China

  • Received Date: 2017-02-05
  • Rev Recd Date: 2017-03-03
  • Publish Date: 2017-10-25
  • A sub-pixel center extraction algorithm based on hierarchical processing was proposed for the implementation of laser stripe processing in the large aerospace parts measurement with high speed and precision. Firstly, the high-resolution image was compressed into low-resolution image with structural invariance. Then, the normal vector of the center of laser stripe was calculated by using quadratic curve fitting in the low-resolution image. The normal vector in the low-resolution image was reproduced to the high-resolution image based on the theory of normal regression. The judgment of gray center on normal direction was established to determine calculated pixels. The sub-pixel center of calculated pixels on the normal direction was accurately calculated by the gray weighted centroid method. Finally, the presented method was utilized to measure a composite material standard part and complex aviation parts in the laboratory and assembly testing machine, respectively. Experimental results show that the precision of the reconstruction of a single stripe on the surface of object is 0.269 mm and the precision of three-dimension surface measurement is 0.268 mm. It indicates that the proposed method can improve the speed and precision of the engineering measurement of large part. Moreover, the method can satisfy the requirements of the in-site measurement of large aerial parts.
  • [1] Li H, Zhang L X, Xiao T Y. Real-time control for CPS of digital airplane assembly with robust H-infinity theory[J]. Tsinghua Science and Technology, 2015, 20(4):376-384.
    [2] Zhao Sihong, Lu Yabing, Chen Xiaoxu, et al. Realization of real-time automatic target reporting system for simulant airborneweapon attacking over ground[J]. Infrared and Laser Engineering, 2014, 43(S1):78-82. (in Chinese)赵思宏, 陆亚兵, 陈晓旭, 等. 航空武器对地模拟攻击实时自动报靶系统的实现[J]. 红外与激光工程, 2014, 43(S1):78-82.
    [3] Gao Yuhan, An Zhiyong, Wang Jinsong, et al. Precision measurement technology of 3D surfaces[J]. Infrared and Laser Engineering, 2011, 40(11):2261-2264. (in Chinese)高瑀含, 安志勇, 王劲松, 等. 三维面型精密测量技术[J]. 红外与激光工程, 2011, 40(11):2261-2264.
    [4] Shi Jinlong, Qian Qiang, Pang Linbin, et al. Three-dimensional measurement and registration for large scale plates[J]. Optics and Precision Engineering, 2014, 22(5):1165-1170. (in Chinese)史金龙, 钱强, 庞林斌, 等. 大尺度钢板的三维测量和拼接[J]. 光学精密工程, 2014, 22(5):1165-1170.
    [5] Zheng Xuehan, Wei Zhenzhong, Zhang Guangjun. Expeditions calibration algorithm of visual tracking and measurement system with field coordinate system for moving target[J]. Infrared and Laser Engineering, 2015, 44(7):2175-2181. (in Chinese)郑学汉, 魏振忠, 张广军. 运动目标视觉跟踪测量系统与场地坐标系的快速统一方法[J]. 红外与激光工程, 2015, 44(7):2175-2181.
    [6] Kieu H, Pan T, Wang Z, et al. Accurate 3D shape measurement of multiple separate objects with stereo vision[J]. Measurement Science and Technology, 2014, 25(1):35-40.
    [7] Qu Hengkuo, Zhang Qingyuan, Ruan Youtian. Laser radar based on scanning image tracking[J]. Chinese Optics, 2012, 5(3):242-247. (in Chinese)屈恒阔, 张清源, 阮友田. 扫描成像跟踪激光雷达[J]. 中国光学, 2012, 5(3):242-247.
    [8] Feng Ping, Liu Zhen. Automatic localization method of the multi-planar strip in rudder angle measurement[J]. Chinese Optics, 2014, 7(6):911-916. (in Chinese)冯萍, 刘震. 舵面角度测量中结构光光条图像自动定位方法[J]. 中国光学, 2014, 7(6):911-916.
    [9] Luks J, Fridrich J, Goljan M. Detecting digital image forgeries using sensor pattern noise[C]//International Society for Optics and Photonics, 2006.
    [10] Steger C. An unbiased detector of curvilinear structures[J]. IEEE Pattern Analysis and Machine Intelligence, 1998, 20(2):113-125.
    [11] Wang Xuejuan, Luo Haibo, Wei Yongwang, et al. Extracting line segments method with HOG feature[J]. Infrared and Laser Engineering, 2013, 42(2):513-518. (in Chinese)王学娟, 罗海波, 魏永旺, 等. 一种采用HOG特征的直线段提取方法[J]. 红外与激光工程, 2013, 42(2):513-518.
    [12] Sun Junhua, Wang Heng, Liu Zhen, et al. Rapid extraction algorithm of laser stripe centerin rail wear dynamic measurement[J]. Optics and Precision Engineering, 2011, 19(3):690-696. (in Chinese)孙军华, 王恒, 刘震, 等. 钢轨磨耗动态测量中激光光条中心的快速提取[J]. 光学精密工程, 2011, 19(3):690-696.
    [13] Heipke C, Steger C, Multhammer R. A hierarchical approach to automatic road extraction from aerial imagery[C]//SPIE, 1995, 2486(5):213122.
    [14] Zhu Jigui, Yu Zhijing. The Principle of Vision Metrology[M]. Beijing:China Machine Press, 2011. (in Chinese)邾继贵, 于之靖. 视觉测量原理与方法[M]. 北京:机械工业出版社, 2011.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Get Citation
PDF
XML

Article Metrics

Article views(343) PDF downloads(89) Cited by()

Related
Proportional views

Sub-pixel center extraction method of laser stripe center based on hierarchical processing

doi: 10.3788/IRLA201778.1017010
  • 1. School of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China
  • Received Date: 2017-02-05
  • Rev Recd Date: 2017-03-03
  • Publish Date: 2017-10-25

Abstract: A sub-pixel center extraction algorithm based on hierarchical processing was proposed for the implementation of laser stripe processing in the large aerospace parts measurement with high speed and precision. Firstly, the high-resolution image was compressed into low-resolution image with structural invariance. Then, the normal vector of the center of laser stripe was calculated by using quadratic curve fitting in the low-resolution image. The normal vector in the low-resolution image was reproduced to the high-resolution image based on the theory of normal regression. The judgment of gray center on normal direction was established to determine calculated pixels. The sub-pixel center of calculated pixels on the normal direction was accurately calculated by the gray weighted centroid method. Finally, the presented method was utilized to measure a composite material standard part and complex aviation parts in the laboratory and assembly testing machine, respectively. Experimental results show that the precision of the reconstruction of a single stripe on the surface of object is 0.269 mm and the precision of three-dimension surface measurement is 0.268 mm. It indicates that the proposed method can improve the speed and precision of the engineering measurement of large part. Moreover, the method can satisfy the requirements of the in-site measurement of large aerial parts.

    HTML

Reference (14)

Catalog

    版权所有 © 2019 《红外与激光工程》编辑部｜ Address: 58 Zhonghuan West Road, Tianjin Airport Economic Zone｜ Post Code: 300308

    津ICP备19007885号-1

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return