Affiliation:
1. Institute of Optics and Electronics Chinese Academy of Sciences
2. University of Chinese Academy of Sciences
Abstract
We proposed a calibration method for high-precision zoom lenses of optical measurement machines based on Fully Connected Neural Network (FNN), using a 5-layer neural network instead of a camera calibration model, to achieve continuous calibration of zoom lenses at any zoom setting by calibrating typical zooms. From the experimental verification, the average calibration error of this method is 9.83×10−4mm and the average measurement error at any zoom setting is 0.01317mm. The overall calibration precision is better than that of Zhang's calibration method and can meet the application requirements of a high-precision optical measurement machine. The method proposed in this paper provided a new solution and a new idea for the calibration of zoom lenses, which can be widely used in the fields of precision parts inspection and machine-vision measurement.
Funder
Sichuan Province Science and Technology Support Program
Bureau of Development and Planning, Chinese Academy of Sciences
Subject
Atomic and Molecular Physics, and Optics
Cited by
3 articles.
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