Translator Disclaimer
13 October 2006 Image enhancement for phase shift analysis sensors
Author Affiliations +
Proceedings Volume 6382, Two- and Three-Dimensional Methods for Inspection and Metrology IV; 63820Q (2006)
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Phase shift analysis sensors are popular in inspection and metrology applications. The sensor's captured image contains the region of interest of an object overlaid with projected fringes. These fringes bend according to the surface topography. 3D data is then calculated using phase shift analysis. The image profile perpendicular to the fringes is assumed to be sinusoidal. A particular version of phase shift analysis is the image spatial phase stepping approach that requires only a single image for analysis, but it is sensitive to noise. When noise, such as surface texture, appears in the image, the sinusoidal behavior is partially lost. This causes an inaccurate or noisy measurement. In this study, three digital de-noising filters are evaluated. The intent is to retrieve a smoother sine-like image profile while precisely retaining fringe boundary locations. Four different edge types are used as test objects. "Six Sigma" statistical analysis tools are used to implement screening, optimization, and validation. The most effective enhancement algorithms of the selection comprise (1) line shifting followed by horizontal Gabor filtration and vertical Gaussian filtering for chamfer edge measurement and (2) edge orientation detection followed by 2-D Gabor filter for round edges. These algorithms significantly improve the gauge repeatability.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gil Abramovich, Kevin Harding, Ralph Isaacs, Matthew Radebach, Kevin Kenny, Zhaohui Sun, Joe Ross, Ming Jia, Li Tao, Guiju Song, Jianming Zheng, Martha Gardner, and Dirk Padfield "Image enhancement for phase shift analysis sensors", Proc. SPIE 6382, Two- and Three-Dimensional Methods for Inspection and Metrology IV, 63820Q (13 October 2006);


On edge detector using local histogram analysis
Proceedings of SPIE (June 23 2003)
Morphologic edge detection in range images
Proceedings of SPIE (July 01 1991)
Finding corners in images by foveated search
Proceedings of SPIE (January 19 2006)
K AVE + GNN + Sobel = an effective, highly...
Proceedings of SPIE (September 19 1997)

Back to Top