Current Optics and Photonics

Optical Society of Korea (한국광학회)
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Vignetting Dimensional Geometric Models and a Downhill Simplex Search

  • Kim, Hyung Tae (Digital Transformation R&D Department, Korea Institute of Industrial Technology) ;
  • Lee, Duk Yeon (Robotics R&D Department, Korea Institute of Industrial Technology) ;
  • Choi, Dongwoon (Robotics R&D Department, Korea Institute of Industrial Technology) ;
  • Kang, Jaehyeon (Robotics R&D Department, Korea Institute of Industrial Technology) ;
  • Lee, Dong-Wook (Robotics R&D Department, Korea Institute of Industrial Technology)
  • Received : 2021.10.15
  • Accepted : 2021.12.28
  • Published : 2022.04.25
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Abstract

Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.

Keywords

Acknowledgement

This research was supported by the Year 2022 Culture Technology R&D Program developed by the Ministry of Culture, Sports and Tourism (MCST) and the Korea Creative Content Agency (KOCCA). (Development of the system for digital data acquisition of modern and contemporary fine arts and supporting science-based art credibility analysis).

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