Total views : 264

Analysis on the Characteristics of Camera Lens Distortion

Affiliations

  • Department of Multimedia, Namseoul University, 91 Daehak-ro Seonghwan-eup Seobuk-gu Cheonan-si Chungnam, 31020, Korea, Republic of

Abstract


Objectives: Recent high zoom lens as CCD (Charge Coupled Device) camera is released with the resolution to be able to easily acquire the digital image that has been variously utilized, from day-to-day utilization to take advantage of specialized domain such as computer vision (computer vision). It has a number of advantages for obtaining a normal zoom lens CCD camera video which is now commercially available, however the camera calibration in the actual image process geometrically have been the considerable difficulties due to the unstable capture and the movement of the pick-up process in a variety of zoom lens camera. Methods: The camera parameters for the zoom lens calibration will be test variables calculated over a camera lens, a variety of focal lengths whenever the zoom occur, especially if you already have zoom movement at the point the lens test is complete, recalculation of the camera calibration parameters cause the difficulties. In this research the zoom lens to correct the distortion of image obtaining the camera calibration, and a method that extracts the camera parameters through the DLT (Direct Linear Transformation) test method is proposed. Findings: DLT accuracy of the camera is black was carried out in the following two aspects. The first was to analyze the three dimensional position differences between the estimated position and the actual three-dimensional observation that is calculated by the model formula to moderate, and the second is that pixel position that is pixels accuracy projected onto the image plane in the three-dimensional space of the object the accuracy was evaluated in an absolute manner. In this study, under the assumption that the aperture condition is fixed zoom, the zoom was determined the relationship between the camera and variable focus for the condition setting. A zoom lens camera model by setting the zoom and focus conditions at regular intervals as short-focus lens model was established by the DLT method and each camera parameter is tested individually. Applications: In future research the image correction software will be develop for the 3-dimensional location information based on three-dimensional information generating process based on camera calibration method by the DLT method.

Keywords

Camera Lens, Camera Parameter, Computer Vision, Direct Linear Transformation.

Full Text:

 |  (PDF views: 217)

References


  • Linear infrastructure mapping using airborne video imagery and subsequent integration into a GIS [Internet]. [Cited 2000 Jul 24]. Available from: http://ieeexplore.ieee.org/document/858388/?reload=true&arnumber=858388.
  • Chen Y-S, Shih S-W, Hung Y-P, Fuh C-S. Simple and efficient method of calibrating a motorized zoom lens. Image and Vision Computing. 2001 Jun; 19:1099–110.
  • Zitnick CL, Kanade T. A cooperative algorithm for stereo matching and occlusion detection. IEEE Transactions on Pattern Analysis Machine Intelligence. 2000 Jul; 22(7):675–84.
  • Salvi J, Armangue X, Batle J. A comparative review of camera calibrating methods with accuracy evaluation. Pattern Recognition. 2002 Jul; 35(7):1617–35.
  • Willey AG, Wong KW. Geometric calibration of zoom lenses for computer vision metrology. Photogrammetric Engineering and Remote Sensing. 1995 Jan; 61(1):587–93.
  • Weng J, Cohen P, Herniou M. Camera calibration with distortion models and accuracy evaluation. IEEE Pattern Analysis and Machine Intelligence. 1992 Oct; 14(10):965–80.
  • Camera calibration with a viewfinder [Internet]. [Cited 2002 May]. Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.5.5296&rep=rep1&type=pdf.
  • Willson RG. Modeling and calibration of automated zoom lenses, Doctoral Dissertation; 1994.
  • Horn BKP, Brooks MJ. Shape from shading. M.I.T. Press; 1989.
  • Oren M, Nayar SK. Generalization of the Lambertian model and implications for machine vision. International Journal of Computer Vision. 1995 Apr; 14(3):227–51.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.