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Techniques for calibration of the scale factor and image center for high accuracy 3-D machine vision metrology

Lenz, R.K., Tsai, R.Y.·1988·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

Techniques are described for calibrating certain intrinsic camera parameters for machine vision. The parameters to be calibrated are the horizontal scale factor, and the image center. The scale factor calibration uses a one-dimensional fast Fourier transform and is accurate and efficient. It also permits the use of only one coplanar set of calibration points for general camera calibration. Three groups of techniques for center calibration are presented: Group I requires using a laser and a four-degree-of-freedom adjustment of its orientation, but is simplest in concept and is accurate and reproducible; Group II is simple to perform, but is less accurate than the other two; and the most general, Group II, is accurate and efficient, but requires a good calibration plate and accurate image feature extraction of calibration points. Group II is recommended most highly for machine vision applications. Results of experiments are presented and compared with theoretical predictions. Accuracy and reproducibility of the calibrated parameters are reported, as well as the improvement in actual 3-D measurement due to center calibration.>

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Metadata

Authors
Lenz, R. K., & Tsai, R. Y.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
1988-09
Volume
10
Issue
5
Pages
713-720
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
OpenAlex
W1981673675
Cited by
557
References
0
FWCI
19.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Techniques for calibration of the scale factor and image center for high accuracy 3-D machine vision metrology. https://app.cochat.ai/papers/10.1109/34.6781
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Lenz, R. K., & Tsai, R. Y. (1988). Techniques for calibration of the scale factor and image center for high accuracy 3-D machine vision metrology. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.6781

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