High-precision stepwise calibration method for binocular microscopic vision system with shallow depth of field

To address the challenges posed by the shallow depth of field in the Binocular Microscopic Vision System (BMVS) of the Ophthalmic micro-Surgical Robot (OmSR), a high-precision, stepwise calibration method, which utilizes predefined movements of the calibration plate, is proposed in this study. The method innovatively decomposes the calibration of camera parameters, thereby addressing the accuracy limitations inherent in the closed-form calibration method due to insufficient constraints. Furthermore, the method integrates plane-parallel constraints with bundle adjustment to achieve global parameter optimization. Compared to the classical Zhang’s method, the proposed method yields lower reprojection error and significantly improves three-dimensional measurement accuracy. Experimental results demonstrate that the BMVS parameters calibrated using the proposed method fully meet the precision requirements for the position measurement of the OmSR’s micro-forceps.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-01-01
DOI
https://doi.org/10.1109/jsen.2025.3592779
Primary Topic
Image Processing Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

High-precision stepwise calibration method for binocular microscopic vision system with shallow depth of field

Xiaodong Zhang, Yachun Wang, Ning Wang, Hongcheng Liu et al.
IEEE Sensors Journal
Image Processing Techniques and Applications
article

High-precision stepwise calibration method for binocular microscopic vision system with shallow depth of field

Xiaodong Zhang, Yachun Wang, Ning Wang, Hongcheng Liu, Zirui Zhao
article en

Abstract

To address the challenges posed by the shallow depth of field in the Binocular Microscopic Vision System (BMVS) of the Ophthalmic micro-Surgical Robot (OmSR), a high-precision, stepwise calibration method, which utilizes predefined movements of the calibration plate, is proposed in this study. The method innovatively decomposes the calibration of camera parameters, thereby addressing the accuracy limitations inherent in the closed-form calibration method due to insufficient constraints. Furthermore, the method integrates plane-parallel constraints with bundle adjustment to achieve global parameter optimization. Compared to the classical Zhang’s method, the proposed method yields lower reprojection error and significantly improves three-dimensional measurement accuracy. Experimental results demonstrate that the BMVS parameters calibrated using the proposed method fully meet the precision requirements for the position measurement of the OmSR’s micro-forceps.

IEEE Sensors Journal
Xi'an Jiaotong University (CN)
Openalex Percentile: Top 74%
Image Processing Techniques and Applications
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