光学学报, 2020, 40(14): 1415002, 网络出版: 2020-07-01
Checkerboard Corner Detection Algorithm for Calibration of Focused Plenoptic Camera
1海军航空大学, 山东 烟台 264001
2国防科技大学前沿交叉学科学院, 湖南 长沙 410073
3国防科技大学计算机学院, 湖南 长沙 410073
机器视觉 聚焦型光场相机 角点检测 标定 原始图 光场圆域特征 machine vision focused plenoptic camera corner detection calibration raw image plenoptic disc feature
Accurate calibration can develop the role of a focused plenoptic camera in the fields like scene reconstruction and non-contact measurement. One of the keys to improve the calibration precision is the accurate feature extraction algorithm. In order to improve the accuracy and efficiency of feature detection, we present a checkerboard corner detection algorithm based on the raw images. First, a robust corner detection operator is used to detect the checkerboard corners in the raw images, and the corresponding relationship between the 2D corners and the 3D plenoptic disc features is used to screen the detected results. Then, the sub-pixel optimization is carried out using the image consistency. The simulated corner detection and calibration experiments are carried out, and the distance measurement experiment is also carried out based on the reconstructed corners obtained by the R29 focused plenoptic camera. The experimental results show that the accuracy of the proposed corner detection algorithm is higher than those of the existing algorithms, and the calibration algorithm based on the proposed corner detection algorithm can achieve more accurate results.