Article

Nonmetric calibration of camera lens distortion: differential methods and robust estimation

Electr. Eng. Dept., Assiut Univ., Egypt
IEEE Transactions on Image Processing (Impact Factor: 3.11). 09/2005; DOI: 10.1109/TIP.2005.846025
Source: IEEE Xplore

ABSTRACT This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. Our approach is based on the analysis of distorted images of straight lines. We derive new distortion measures that can be optimized using nonlinear search techniques to find the best distortion parameters that straighten these lines. Unlike the other existing approaches, we also provide fast, closed-form solutions to the distortion coefficients. We prove that including both the distortion center and the decentering coefficients in the nonlinear optimization step may lead to instability of the estimation algorithm. Our approach provides a way to get around this, and, at the same time, it reduces the search space of the calibration problem without sacrificing the accuracy and produces more stable and noise-robust results. In addition, while almost all existing nonmetric distortion calibration methods needs user involvement in one form or another, we present a robust approach to distortion calibration based on the least-median-of-squares estimator. Our approach is, thus, able to proceed in a fully automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered projections of three-dimensional linear segments. Experiments to evaluate the performance of this approach on synthetic and real data are reported.

0 Bookmarks
 · 
101 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents two methods of star camera calibration to determine camera calibrating parameters (like principal point, focal length etc) along with lens distortions (radial and decentering). First method works autonomously utilizing star coordinates in three consecutive image frames thus independent of star identification or biased attitude information. The parameters obtained in autonomous self-calibration technique helps to identify the imaged stars with the cataloged stars. Least Square based second method utilizes inertial star coordinates to determine satellite attitude and star camera parameters with lens radial distortion, both independent of each other. Camera parameters determined by the second method are more accurate than the first method of camera self calibration. Moreover, unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters, the second method has the advantage of computing spacecraft attitude independent of camera calibrating parameters except lens distortions (radial). Finally Kalman filter based sequential estimation scheme is employed to filter out the noise of the LS based estimation.
    Journal of Intelligent and Robotic Systems 01/2014; DOI:10.1007/s10846-014-0068-z · 0.81 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Arthroscopic images are subject to distortion, which may increase when using arthroscope lenses with greater reflecting angles and/or viewing structures at oblique angles. The purpose of this study was to determine the magnitude of image distortion experienced when using arthroscopes with different lens angles and when the line-of-sight (i.e., viewing angle) is not directly perpendicular to the target.
    Knee Surgery Sports Traumatology Arthroscopy 09/2014; DOI:10.1007/s00167-014-3336-3 · 2.84 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A riverbed topographic survey is one of the most important tasks for river model experiments. To improve measurement efficiency and solve the riverbed interference problem in traditional methods, this study discussed two measurement methods that use digital image-processing technology to obtain topographic information. A new and improved approach for calibrating camera radial distortion, which comes from originally distorted images captured by our camera, was proposed to enhance the accuracy of image measurement. Based on perspective projection transformation, we described a 3D reconstruction method based upon multiple images, which is characterized by using an approximated maximum likelihood estimation method (AMLE) considering the first-order error propagation of the residual error to compute transformation parameters. Moreover, a theoretical derivation of 3D topography according to grey information from a single image was carried out. With the diffuse illumination model, assuming that the ideal grey value and topographic elevation value are positively correlated, we derived a novel closed formula to explain the relationship of 3D topographic elevation, grey value, grey gradient, and the solar direction vector. Experimental results showed that our two methods both have some positive advantages even if they are not perfect.
    Journal of Zhejiang University - Science A: Applied Physics & Engineering 01/2014; 15(1):68-82. DOI:10.1631/jzus.A1300317 · 0.61 Impact Factor