4.6 Article

A Camera Intrinsic Matrix-Free Calibration Method for Laser Triangulation Sensor

期刊

SENSORS
卷 21, 期 2, 页码 -

出版社

MDPI
DOI: 10.3390/s21020559

关键词

calibration; laser triangular sensor; one-dimensional target

资金

  1. National Natural Science Foundation of China [51775215]
  2. Key R&D project of Hubei Province [2020BAB035]

向作者/读者索取更多资源

A novel LTS calibration method without knowing the camera intrinsic matrix is proposed, which significantly improves the precision of displacement measurement through parameter optimization.
Laser triangulation sensors (LTS) are widely used to acquire depth information in industrial applications. However, the parameters of the components, e.g., the camera, of the off-the-shelf LTS are typically unknown. This makes it difficult to recalibrate the degenerated LTS devices during regular maintenance operations. In this paper, a novel one-dimensional target-based camera intrinsic matrix-free LTS calibration method is proposed. In contrast to conventional methods that calibrate the LTS based on the precise camera intrinsic matrix, we formulate the LTS calibration as an optimization problem taking all parameters of the LTS into account, simultaneously. In this way, many pairs of the camera intrinsic matrix and the equation of the laser plane can be solved and different pairs of parameters are equivalent for displacement measurement. A closed-form solution of the position of the one-dimensional target is proposed to make the parameters of the LTS optimizable. The results of simulations and experiments show that the proposed method can calibrate the LTS without knowing the camera intrinsic matrix. In addition, the proposed approach significantly improves the displacement measurement precision of the LTS after calibration. In conclusion, the proposed method proved that the precise camera intrinsic matrix is not the necessary condition for LTS displacement measurement.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据