The infrared (IR)—visible light (VIS) dual-camera system provides complementary cues for image fusion, but issues such as geometric mismatch caused by different imaging methods, inconsistent resolution/field-of-view, and installation offsets often lead to ghosting and artifacts. This study aims to develop a fast-deployable and repeatable calibration workflow based on cost-effective calibration board. We designed an infrared-visible high-contrast checkerboard plate that can be generated through structural parameterization and efficiently manufactured using Python/OpenSCAD. We also established a corner-based registration pipeline that estimates global homography to align the visible-light images onto the infrared pixel grid for fusion and quantitative evaluation. Experiments conducted in a controlled indoor environment demonstrated stable sub-pixel performance within a range of 1.5–2.5 m, with an average re-projection error of 0.47–0.50 pixels per frame and a 95th percentile lower than 0.51 pixels. The corner position re-projection error test further confirmed stability near image boundaries, with a median value of 0.53–0.63 pixels and a 95th percentile of 0.54–0.64 pixels. Overall, the proposed target design and workflow can achieve practical infrared-visible calibration under typical deployment constraints and have repeatable accuracy, providing geometrically consistent input for subsequent fusion and dataset construction.
Shao et al. (Sat,) studied this question.