Grid-Based Corner Detection of the Microscopic Camera Calibration

Abstract:

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Camera calibration is one of the key technologies of Computer Vision. This paper presented a microscope camera calibration method based on grid corner detection for the particular application area of microscopic measurement. The method considered not only the radial distortion, but also other non-linear factors, such as centrifugal distortion and thin-prism distortion. First of all, the actual corner coordinates information of the grid was obtained through the improved corner detection method. Then, the matrixes of lens distortion parameters and camera internal parameters were gotten according to the camera imaging model. Finally, through the established non-linear camera model, the average error between fore-projection and re-projection grid corner coordinates was obtained by re-projecting the grid corner coordinates. Experimental results show that the corner detection algorithm is accurate and the final calibration error is 0.6319 pixel, which is applicable to microscopic camera calibration.

Info:

Periodical:

Advanced Materials Research (Volumes 301-303)

Edited by:

Riza Esa and Yanwen Wu

Pages:

1145-1150

DOI:

10.4028/www.scientific.net/AMR.301-303.1145

Citation:

W. Yuan et al., "Grid-Based Corner Detection of the Microscopic Camera Calibration", Advanced Materials Research, Vols. 301-303, pp. 1145-1150, 2011

Online since:

July 2011

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Price:

$35.00

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