
High-accuracy calibration of low-cost camera using image disturbance factor
Author(s) -
Zhen Liu,
Qun Wu,
Xu Chen,
Yong Yin
Publication year - 2016
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.24.024321
Subject(s) - homography , artificial intelligence , feature (linguistics) , calibration , computer vision , computer science , camera resectioning , image plane , projection (relational algebra) , point spread function , feature detection (computer vision) , noise (video) , image (mathematics) , image processing , mathematics , algorithm , linguistics , statistics , philosophy , projective test , projective space
Nonindustrial low-cost cameras have the advantages of cheap and simple structure, but have the disadvantages of low resolution and large image noise. When the existing camera calibration methods are used to calibrate nonindustrial low-cost cameras, high-accuracy calibration cannot be obtained. A high-accuracy calibration method using a high-accuracy planar target is introduced in this study to solve this problem. First, the initial values and the uncertainties of all image feature points are determined by the multiscale image analysis method. Then, the image disturbance factor is added to each target image feature point. In addition, the image projection error is established as the minimum objective function according to the homography matrix between the target plane and the image plane. Thus, the optimal coordinates of all image feature points are obtained by the nonlinear optimization method. Finally, the calibration of the intrinsic and extrinsic parameters of the camera will be achieved by using Zhang's method according to the image feature points obtained from the previous step. Simulative and real experiments have been conducted to evaluate the performance of the proposed method, and results show that the calibration accuracy of the proposed method is at least three times that of Zhang's method.