A novel approach to sub-pixel corner detection of the grid in camera calibration

In order to improve the precision of camera calibration in the field of computer vision, we have to detect the points of the calibration pattern precisely. A new approach to sub-pixel corner detection of a grid is proposed in this paper, which is based on the combination of Hough Transform and least square fit. The procedure of the approach is as follows: (1) The image is divided into small regions to avoid the influence of camera lens distortion on linear fitting and each region has only one corner definitely. Edges of the grid in each region are detected by the Canny arithmetic operator. (2) Straight lines in each region are detected by Hough Transform. (3) Two straight lines with a certain separation angle are selected arbitrarily in each region as initial location. Then, edge-points are searched and recorded in the neighborhoods of each straight line in view of that the results of Hough Transform may not be sufficient for the edge location in practice. (4) Four straight lines are fitted by least square using the edge-points detected in each region. Center of the quadrilateral formed by the straight lines is calculated as the sub-pixel corner location. Finally, experimental results show that sub-pixel corner location of the grid can be obtained correctly and precisely, and none of them are missed. Consequently, it has been proved that this approach is feasible in the application of sub-pixel corner detection of a grid.