Sub-pixel detection method for an aviation plug based on Zernike moments

To address the multi-aperture detection requirements for aviation plugs in complex aerospace manufacturing environments, a sub-pixel edge detection method based on Zernike moments was proposed. First, a linear ramp edge detection model is constructed on the basis of traditional Zernike moments. By precisely deriving edge parameters in the fuzzy transition region via orthogonal critical moments and integrating an adaptive extraction algorithm to optimize threshold judgment criteria, the sub-pixel localization accuracy is significantly improved. Second, a local optimization mechanism and dynamic parameter adjustment strategy were introduced to refine the RANSAC fitting algorithm. Finally, a high-precision visual inspection system for aviation plugs was developed, integrating the Zernike moment-based sub-pixel edge detection algorithm. The experimental results show that the absolute error between the proposed method and the coordinate measuring machine measurements is ±10µ<i>m</i>, with a root mean square error of 2.99 µm and a detection time of 1.016 s, demonstrating high accuracy and excellent real-time detection performance in complex industrial environments.

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Publication Details

Journal
Applied Optics
Published
2025-12-02
DOI
https://doi.org/10.1364/ao.576086
Primary Topic
Image and Object Detection Techniques
Type
article
Field-Weighted Citation Impact
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article

Sub-pixel detection method for an aviation plug based on Zernike moments

Wei Zhao, Shengnan Qin, Gang Han, Hang Yin et al.
Applied Optics
Image and Object Detection Techniques
article

Sub-pixel detection method for an aviation plug based on Zernike moments

Wei Zhao, Shengnan Qin, Gang Han, Hang Yin, Ji Li
article en

Abstract

To address the multi-aperture detection requirements for aviation plugs in complex aerospace manufacturing environments, a sub-pixel edge detection method based on Zernike moments was proposed. First, a linear ramp edge detection model is constructed on the basis of traditional Zernike moments. By precisely deriving edge parameters in the fuzzy transition region via orthogonal critical moments and integrating an adaptive extraction algorithm to optimize threshold judgment criteria, the sub-pixel localization accuracy is significantly improved. Second, a local optimization mechanism and dynamic parameter adjustment strategy were introduced to refine the RANSAC fitting algorithm. Finally, a high-precision visual inspection system for aviation plugs was developed, integrating the Zernike moment-based sub-pixel edge detection algorithm. The experimental results show that the absolute error between the proposed method and the coordinate measuring machine measurements is ±10µ<i>m</i>, with a root mean square error of 2.99 µm and a detection time of 1.016 s, demonstrating high accuracy and excellent real-time detection performance in complex industrial environments.

Applied OpticsVol. 65(1)
Aviation Industry Corporation of China (China) (CN), Guangdong University of Technology (CN), Craft Group (China) (CN)
Openalex Percentile: Top 61%
Image and Object Detection Techniques
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