Laser & Optoelectronics Progress, Volume. 54, Issue 11, 111504(2017)
Optimization of Camera Internal Parameters Based on Particle Swarm Algorithm
Aiming at the problem that the calibration accuracy of MATLAB calibration toolbox is proportional to the number of images taken, which means the larger the number of photo frames, the higher the calibration accuracy. A method of internal parameter optimization based on particle swarm algorithm is proposed, and the better effects can be achieved with few pictures. First the camera shoots 4 and 20 calibration plate pictures in different angles, and their internal parameters are obtained with the use of MATLAB calibration toolbox. The objective function is established through the calibration point of the actual coordinates and the back projection coordinates, and then the internal parameters obtained by calibration box are optimized by the particle swarm algorithm. The experimental results show that this method can improve the calibration accuracy of a small number of calibration plate pictures to a certain extent compared with the MATLAB calibration toolbox.
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Guo Tongying, Li Ningning, Liu Yong. Optimization of Camera Internal Parameters Based on Particle Swarm Algorithm[J]. Laser & Optoelectronics Progress, 2017, 54(11): 111504
Category: Machine Vision
Received: Jun. 4, 2017
Accepted: --
Published Online: Nov. 17, 2017
The Author Email: Ningning Li (1224271642@qq.com)