|Table of Contents|

[1] Chen Ping, Zhang Zhisheng, Dai Min, Chen Kai, et al. Sub-pixel extraction of laser stripe and its applicationin laser plane calibration [J]. Journal of Southeast University (English Edition), 2015, 31 (1): 107-112. [doi:10.3969/j.issn.1003-7985.2015.01.018]
Copy

Sub-pixel extraction of laser stripe and its applicationin laser plane calibration()
Share:

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
31
Issue:
2015 1
Page:
107-112
Research Field:
Computer Science and Engineering
Publishing date:
2015-03-30

Info

Title:
Sub-pixel extraction of laser stripe and its applicationin laser plane calibration
Author(s):
Chen Ping Zhang Zhisheng Dai Min Chen Kai
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
Keywords:
sub-pixel extraction center line extraction laser plane calibration progressive probabilistic Hough transform(PPHT) principal component(PC)angle 2D Taylor expansion
PACS:
TP391.4;TN911.73
DOI:
10.3969/j.issn.1003-7985.2015.01.018
Abstract:
For calibrating the laser plane to implement 3D shape measurement, an algorithm for extracting the laser stripe with sub-pixel accuracy is proposed. The proposed algorithm mainly consists of two stages: two-side edge detection and center line extraction. First, the two-side edge of laser stripe is detected using the principal component angle-based progressive probabilistic Hough transform and its width is calculated through the distance between these two edges. Secondly, the center line of laser strip is extracted with 2D Taylor expansion at a sub-pixel level and the laser plane is calibrated with the 3D reconstructed coordinates from the extracted 2D sub-pixel ones. Experimental results demonstrate that the proposed method can not only extract the laser stripe at a high speed, nearly average 78 ms/frame, but also calibrate the coplanar laser stripes at a low error, limited to 0.3 mm. The proposed algorithm can satisfy the system requirement of two-side edge detection and center line extraction, and rapid speed, high precision, as well as strong anti-jamming.

References:

[1] Tupin F, Maître H, Mangin J, et al. Detection of linear features in SAR images: application to road network extraction [J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(2): 434-453.
[2] Hinz S, Baumgartner A. Automatic extraction of urban road network from multi-view aerial imagery [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2003, 58(1/2): 83-98.
[3] Kussul N, Shelestov A, Skakun S. Grid system for flood extent extraction from satellite images [J]. Earth Science Informatics, 2008, 1(3/4): 105-117.
[4] Kirbas C, Quek F K H. Vessel extraction techniques and algorithms: a survey [C]//Proc of the Third IEEE Symposium on BioInformatics and BioEngineering. Bethesda, MD: IEEE Press, 2003. 238-245.
[5] Hoover A, Goldbaum M. Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels [J]. IEEE Transactions on Medical Imaging, 2003, 22(8): 951-958.
[6] Wei Z, Zhou F, Zhang G. 3D coordinates measurement based on structured light sensor [J]. Sensors and Actuators A: Physical, 2005, 120(2): 527-535.
[7] Zhang G, Liu Z, Sun J, et al. Novel calibration method for a multi-sensor visual measurement system based on structured light [J]. Optical Engineering, 2010, 49(4): 043602.
[8] Steger C. Unbiased extraction of curvilinear structures from 2D and 3D images [M]. München: Herbert Utz Verlag, 1998: 27-76.
[9] Chen J, Sato Y, Tamura S. Orientation space filtering for multiple orientation line segmentation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(5): 417-429.
[10] Steger C. Unbiased extraction of lines with parabolic and Gaussian profiles [J]. Computer Vision and Image Understanding, 2013, 117(2): 97-112.
[11] Jin X, Zhang Y, Li L, et al. Robust PCA-based abnormal traffic pattern isolation and loop detector fault detection [J]. Tsinghua Science and Technology, 2008, 13(6): 829-835.
[12] Hodge V J, Austin J. A survey of outlier detection methodologies [J]. Artificial Intelligence Review, 2004, 22(2): 85-126.
[13] Matas J. Robust detection of lines using the progressive probabilistic Hough transform [J]. Computer Vision and Image Understanding, 2000, 78(1): 119-137.
[14] Galambos C, Kittler J, Matas J. Gradient based progressive probabilistic Hough transform [J]. IEE Proceedings on Vision, Image and Signal Processing, 2001, 148(3): 158-165.
[15] Zhou F, Zhang G. Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations [J]. Image and Vision Computing, 2005, 23(1): 59-67.

Memo

Memo:
Biographies: Chen Ping(1987—), male, graduate; Zhang Zhisheng(corresponding author), male, doctor, professor, oldbc@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.50805023), the Science and Technology Support Program of Jiangsu Province(No.BE2008081), the Research and Innovation Project for College Graduates of Jiangsu Province(No.CXZZ13_0086), Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1401).
Citation: Chen Ping, Zhang Zhisheng, Dai Min, et al. Sub-pixel extraction of laser stripe and its application in laser plane calibration[J].Journal of Southeast University(English Edition), 2015, 31(1):107-112.[doi:10.3969/j.issn.1003-7985.2015.01.018]
Last Update: 2015-03-20