Automatic checkerboard detection for camera calibration using self-correlation
Date of Issue2018
School of Mechanical and Aerospace Engineering
Centre for Optical and Laser Engineering
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. 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 reprojected pixel errors smaller than 0.5 pixels.
Journal of Electronic Imaging
© 2018 Society of Photo-optical Instrumentation Engineers (SPIE) and IS&T. This paper was published in Journal of Electronic Imaging and is made available as an electronic reprint (preprint) with permission of Society of Photo-optical Instrumentation Engineers (SPIE) and IS&T. The published version is available at: [http://dx.doi.org/10.1117/1.JEI.27.3.033014]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.