Abstract

Camera calibration is the basic of machine vision, the accuracy of feature point detection and the automation of camera calibration process is very important in actual high precision measurement. The planar pattern with circle feature has its own advantage compared with chessboard calibration pattern; it is easy to manufacture, and insensitive to threshold. Although there is a position distortion in detecting the projected centre of circle for perspective projection, the feature point which is the image of the center of the circle can be computed accurately based on the geometric and algebraic constrains of projected concentric circles. After the feature points is detected, the set of feature points on the calibration pattern and the points in the camera images must be matched, manual or user assisted methods are often used to solve the matching problem. This paper also describes a simple technique based on Delaunay triangulation to automatically match the feature points recovered by concentric circles. The experiments show that the method is excellent in actual camera calibration using concentric circles array.

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