Checkerboard Corner Detection Algorithm for Calibration of Focused Plenoptic Camera

Qingsong, 刘青松 Liu; Xiaofang, 谢晓方 Xie; Xuanzhe, 张烜喆 Zhang; Yu, 田瑜 Tian; Jun, 黎军 Li; Yan, 王彦 Wang; Xiaojun, 许晓军 Xu

doi:10.3788/aos202040.1415002

Cited by 2 publications

(1 citation statement)

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“…To reduce the influence of the wrong image corners on the calibrations, the PDFs are used to correct the position of all corner points. 23 According to the concept of the PDF, there is a geometric constraint relationship between the corners of the corner cluster. The PDF ½ M u M v R t is calculated from the corner cluster…”

Section: Corner Detection Of Checkerboard Imagesmentioning

confidence: 99%

Improved blur circle detection method for geometric calibration of multifocus light field cameras

Chen¹,

Lu²,

Wang³

et al. 2022

Opt. Eng.

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Multifocus light field cameras are increasingly gaining attention in the field of computational imaging and machine vision due to their ability to capture spatial and angular information of light rays. Accurate calibration of the geometric parameters of multifocus light field cameras is the prerequisite for implementing computational imaging techniques, such as digital refocusing, depth reconstruction, and three-dimensional reconstruction. We propose an improved blur circle detection method for the calibration of multifocus light field cameras. The circular Hough transform-based circle detection method is used to obtain the subimage centers accurately in white raw images. On this basis, the subimages in the checkerboard images are classified, and the image corners are detected to determine the clusters of image corners corresponding to checkerboard corners. Then, the centers of plenoptic disc features are used as projection points of checkerboard corners on the light field image to calculate the camera pose. Levenberg-Marquardt method is further used to solve the calibration model. Finally, the calibration experiments of multifocus light field cameras are carried out to evaluate the improved blur circle detection method. Experimental results indicated that the improved blur circle detection method has higher calibration accuracy of multifocus light field camera than the blur circle detection method, while the mean reprojection error of the microlens centers and the image corners are 0.12 and 0.33 pixels, and the mean relative distance error between adjacent checkerboards is 2.53%.

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Section: Corner Detection Of Checkerboard Imagesmentioning

confidence: 99%