Guangjun Zhang

A new sub-pixel detector for grid target points in camera calibration

Sub-pixel detection of target points is an important task in camera calibration. Grid target points are widely used in camera calibration for their junctions can be easily detected. Traditional method detects the sub-pixel position of grid-point by calculating the intersection of two beelines fitted by centers of grid-lines. Generally, this method yields low precision because of the effect of projective distortion of camera lens. In this paper, we propose a new sub-pixel detector for grid target points. We firstly use a new shape operator based on Hessian matrix to detect the pixel position of grid-point. Then the intensity of sub-pixel points in the neighborhood of grid point is calculated by cubic interpolation. A minimum restriction for searching grid-point is deduced by the fact that the grid-point to be detected is just the extremal point of local intensity profile. According to this restriction, the sub-pixel position of grid-point is finally determined by a graded morphological shrinking operation. Computer simulation results indicate that our new algorithm is more accurate and robust than the traditional algorithm.

A calibration method for a distance detection camera

A technique is developed to calibrate a camera which is equipped on mobile robot and detect a distant scene. A flexible calibration target, on which calibration feature points are generated according to cross-ratio invariability, is employed in this paper. As can be extended as needed, the target has a flexible size and can be used at discretionary distance from the camera. To guarantee the generating accuracy of calibration points, coordinates of principal point and radial lens distortion coefficients of first two orders are determined previously. Experiment results revealed the effectiveness of the presented method and higher accuracy than traditional method.