Comparison of spacing detection algorithms for optical straight fringes images

Yuexin Wang; Fuzhong Bai; Xiaojuan Gao; Ying Wang

doi:10.1117/12.2512071

7 March 2019 Comparison of spacing detection algorithms for optical straight fringes images

Yuexin Wang, Fuzhong Bai, Xiaojuan Gao, Ying Wang

Proceedings Volume 11053, Tenth International Symposium on Precision Engineering Measurements and Instrumentation; 110532W (2019) https://doi.org/10.1117/12.2512071
Event: 10th International Symposium on Precision Engineering Measurements and Instrumentation (ISPEMI 2018), 2018, Kunming, China

Abstract

Optical fringe is one of important output information from the optical systems. Some important optical or system parameters can be obtained by analyzing the fringe information from optical system such as interferometer system or diffraction setup. The straight fringe is a kind of optical fringes frequently appearing in Young’s double slit interference and single-slit diffraction and other optical structures. For the information extraction of straight fringes, it is often necessary to calculate the fringe spacing parameters. Popular straight fringes analysis methods include the fringe center method and the Fourier transform method. In addition, some image processing methods realized line detection can also be used to analyze this straight fringes image, which include Hough transform and Radon transform. In this paper, four algorithms for fringe analysis are discussed and compared, which focus on method’s principle, algorithm’s simulation and performance when they be applied to detect the fringes spacing. At the same time, the anti-noise performance of two image processing algorithms including Hough transform and Radon transform are analyzed.

Citation Download Citation

Yuexin Wang, Fuzhong Bai, Xiaojuan Gao, and Ying Wang "Comparison of spacing detection algorithms for optical straight fringes images", Proc. SPIE 11053, Tenth International Symposium on Precision Engineering Measurements and Instrumentation, 110532W (7 March 2019); https://doi.org/10.1117/12.2512071

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