Sub-Pixel Displacement Measurement with Swin Transformer: A Three-Level Classification Approach

In order to avoid the dependence of traditional sub-pixel displacement methods on interpolation method calculation, image gradient calculation, initial value estimation and iterative calculation, a Swin Transformer-based sub-pixel displacement measurement method (ST-SDM) is proposed, and a square da...

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Bibliographic Details
Main Authors: Yongxing Lin, Xiaoyan Xu, Zhixin Tie
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/5/2868
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Summary:In order to avoid the dependence of traditional sub-pixel displacement methods on interpolation method calculation, image gradient calculation, initial value estimation and iterative calculation, a Swin Transformer-based sub-pixel displacement measurement method (ST-SDM) is proposed, and a square dataset expansion method is also proposed to rapidly expand the training dataset. The ST-SDM computes sub-pixel displacement values of different scales through three-level classification tasks, and solves the problem of positive and negative displacement with the rotation relative tag value method. The accuracy of the ST-SDM is verified by simulation experiments, and its robustness is verified by real rigid body experiments. The experimental results show that the ST-SDM model has higher accuracy and higher efficiency than the comparison algorithm.
ISSN:2076-3417