revised_manuscript_20180502.pdf (3.63 MB)
Automatic checkerboard detection for camera calibration using self-correlation
journal contributionposted on 2019-02-21, 11:36 authored by Y Yan, P Yang, L Yan, J Wan, Y Sun, K Tansey, A Asundi, H Zhao
The checkerboard is a frequently-used pattern in camera calibration, an essential process to get intrinsic parameters for more accurate information from images. An automatic checkerboard detection method that can detect multiple checkerboards in a single image is proposed in this paper. It contains a corner extraction approach using self-correlation and a structure recovery solution using constraints related to adjacent corners and checkerboard block edges. The method utilizes the central symmetric feature of the checkerboard crossings as well as the spatial relationship of neighboring checkerboard corners and the grayscale distribution of their neighboring pixels. Five public datasets are used in the experiments to evaluate the method. Results show high detection rates and a short average runtime of the proposed method. In addition, the camera calibration accuracy also presents the effectiveness of the proposed detection method with re-projected pixel errors smaller than 0.5 pixels.
This work was supported by the National Natural Science Foundation of China [grant number 41571432]; the National Key Research and Development Program of China [grant number SQ2017YFGX040110]; the National Key Research and Development Program of China [grant number 2017YFB0503004]; the State Administration of Foreign Experts Affairs program of China [grant number GDT0161100077].
CitationJournal of Electronic Imaging, 2018, 27 (3), 033014
Author affiliation/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment/GIS and Remote Sensing
- AM (Accepted Manuscript)