1 November 2008 Improved robust and accurate camera calibration method used for machine vision application
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Abstract
Camera calibration is an important step for vision-based measurement applications. A well-known flexible camera calibration method is analyzed that uses the checkerboard pattern plane and in which the camera can be moved freely. When using a perspective projection camera model, characteristics of both the objective plane and the image plane are utilized and accurate results can be obtained. However, the method's results may fail when the rotation angles of the planar pattern are small, and the distortion coefficients obtained under the perspective projection model can not be used for a real-time vision application. We solve the ill-conditioned equations using the genetic algorithm, and the correct camera parameters are always obtained. We compute the distortion coefficients of the inverse projection model, which can be used for general vision applications. The influence of the corner detection precision is taken into consideration. Simulation shows that the best results may be obtained when the planar pattern is placed in a close range and its rotation angle is small. Simulations and real-world experiments illustrate that the improved calibration algorithm can always obtain robust and accurate results.
© (2008) Society of Photo-Optical Instrumentation Engineers (SPIE)
Zhiyong Zhang, Dayong Zhu, Jing Zhang, Zhenming Peng, "Improved robust and accurate camera calibration method used for machine vision application," Optical Engineering 47(11), 117201 (1 November 2008). https://doi.org/10.1117/1.3027554 . Submission:
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