Current Optics and Photonics

Optical Society of Korea (한국광학회)
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Adaptive Extraction Method for Phase Foreground Region in Laser Interferometry of Gear

  • Xian Wang (School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology) ;
  • Yichao Zhao (School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology) ;
  • Chaoyang Ju (School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology) ;
  • Chaoyong Zhang (School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology)
  • Received : 2023.05.18
  • Accepted : 2023.07.05
  • Published : 2023.08.25
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Abstract

Tooth surface shape error is an important parameter in gear accuracy evaluation. When tooth surface shape error is measured by laser interferometry, the gear interferogram is highly distorted and the gray level distribution is not uniform. Therefore, it is important for gear interferometry to extract the foreground region from the gear interference fringe image directly and accurately. This paper presents an approach for foreground extraction in gear interference images by leveraging the sinusoidal variation characteristics shown by the interference fringes. A gray level mask with an adaptive threshold is established to capture the relevant features, while a local variance evaluation function is employed to analyze the fluctuation state of the interference image and derive a repair mask. By combining these masks, the foreground region is directly extracted. Comparative evaluations using qualitative and quantitative assessment methods are performed to compare the proposed algorithm with both reference results and traditional approaches. The experimental findings reveal a remarkable degree of matching between the algorithm and the reference results. As a result, this method shows great potential for widespread application in the foreground extraction of gear interference images.

Keywords

Acknowledgement

NSFC grant number 52205067, 61805195, 52004213; Natural Science Basic Research Program of Shaanxi grant number 2022JQ-403; China Postdoctoral Science Foundation grant number 2020M683683XB.

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