Dr. Guiju Song Profile

Dr. Guiju Song

at GE Research

SPIE Involvement:

Author

Proceedings Article | 14 May 2015 Paper

Development of feature extraction analysis for a multi-functional optical profiling device applied to field engineering applications

Xu Han, Guangping Xie, Brandon Laflen, Ming Jia, Guiju Song, Kevin Harding

Proceedings Volume 9489, 948907 (2015) https://doi.org/10.1117/12.2177281

KEYWORDS: Mirrors, Feature extraction, Metrology, Inspection, Profiling, Collimation, Charge-coupled devices, CCD image sensors, Calibration, Cameras

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Proceedings Article | 14 May 2015 Paper

3D tracking for borescope inspections

Yong Yang, Guiju Song, Kevin Harding

Proceedings Volume 9489, 94890L (2015) https://doi.org/10.1117/12.2176636

KEYWORDS: Sensors, Inspection, Fiber optics sensors, Computer aided design, Solid modeling, Image sensors, Image analysis, 3D modeling, Structured optical fibers, Inspection equipment

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Proceedings Article | 18 August 2014 Paper

Blade counting tool with a 3D borescope for turbine applications

Kevin Harding, Jiajun Gu, Li Tao, Guiju Song, Jie Han

Proceedings Volume 9204, 92040Q (2014) https://doi.org/10.1117/12.2063742

KEYWORDS: Inspection, Video, Cameras, Filtering (signal processing), Feature extraction, Video processing, Detection and tracking algorithms, Motion analysis, Binary data, Resistance

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Proceedings Article | 20 November 2012 Paper

OCT for industrial applications

Guiju Song, Kevin Harding

Proceedings Volume 8563, 85630N (2012) https://doi.org/10.1117/12.2000462

KEYWORDS: Optical coherence tomography, Composites, Inspection, Manufacturing, Process control, Carbon, Metrology, Interferometry, Imaging systems, Sensors

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Proceedings Article | 11 November 2010 Paper

Calibration and image enhancement algorithm of portable structured light 3D gauge system for improving accuracy

Li Tao, Kevin Harding, Ming Jia, Guiju Song

Proceedings Volume 7855, 78550Y (2010) https://doi.org/10.1117/12.872022

KEYWORDS: Calibration, Image enhancement, 3D metrology, Image filtering, Image processing, Charge-coupled devices, Inspection, Sensors, 3D image processing, Structured light

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Proceedings Article | 29 August 2008 Paper

3D surface defect analysis and evaluation

B. Yang, M. Jia, G. Song, L. Tao, K. Harding

Proceedings Volume 7066, 706608 (2008) https://doi.org/10.1117/12.799883

KEYWORDS: Clouds, 3D metrology, Binary data, Inspection, Computer aided design, Digital filtering, Metrology, Solid modeling, Optical spheres, Structured light

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Proceedings Article | 13 October 2006 Paper

Image enhancement for phase shift analysis sensors

Gil Abramovich, Kevin Harding, Ralph Isaacs, Matthew Radebach, Kevin Kenny, Zhaohui Sun, Joe Ross, Ming Jia, Li Tao, Guiju Song, Jianming Zheng, Martha Gardner, Dirk Padfield

Proceedings Volume 6382, 63820Q (2006) https://doi.org/10.1117/12.686354

KEYWORDS: Detection and tracking algorithms, Gaussian filters, Image enhancement, Phase shifts, Image filtering, Sensors, Image analysis, Edge detection, Anisotropic filtering, Speckle

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Proceedings Article | 14 August 2006 Paper

Effect of varied fringe width on measured profile in structured line projection method

Guiju Song, Ming Jia, Yu Ning, Jianming Zheng, Kevin Harding

Proceedings Volume 6292, 62920T (2006) https://doi.org/10.1117/12.681577

KEYWORDS: Phase shifting, CCD cameras, Inspection, Fringe analysis, Algorithm development, Interferometry, Error analysis, Optimization (mathematics), Integrated optics, Data acquisition

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In industry, there are needs to accurately measure the 3-D profile of edges parts in order to evaluate edge condition. Optical methods are increasingly used for this purpose due to its advantages such as being non-contact, fast, accurate, and easy to integrate with software for data acquisition and feature analysis. We utilized structured line projection technology to measure edge's profile. In this method a structured light distribution, created by the transmission of a sinusoidal grating, was projected onto the inspected parts at a certain incidence angle. The projected light lines were deformed due to the depth change on the edge surface. A CCD camera sitting at a different angle was used to record the deformed fringes. From the deformed fringes the 3D surface profile was extracted based on triangulation principal. Because the projected grating pattern can be interpreted as an interference pattern, we used the spatial carrier phase shifting and phase unwrapping method as in classic interferometry to extract the phase information from the intensity distribution of fringes. Due to the limited depth-of-range of the fringe image and depth-of-focus of the imaging lens on the CCD camera, the observed deformed fringes have different widths and frequencies at different depth. According to the definition of depth-of-focus, the fringe width out of focus can be on the order of the square root of 2 wider than that which is in focus. The width change can also be due to a tilt across the object. This width change affects the accuracy of the spatial carrier phase shifting and subsequently the accuracy of extracted profile. In this paper, we proposed to monitor the change of the fringe width with imaging depth. According to the width of the fringes, we defined a parameter called compressing rate, to use in computing the edge profile. For different edge types, the compressing rate was optimized in order to get the profile that can match the results from traditional the methods. By using this method, the system repeatability can be improved significantly.