A Robust Recognition Technique for Dense Checkerboard Patterns

The checkerboard pattern is widely used in computer vision techniques for camera calibration and simple geometry acquisition, both in practical use and research. However, most of the current techniques fail to recognize the checkerboard pattern under distorted, occluded or discontinuous conditions, especially when the checkerboard pattern is dense. This paper proposes a novel checkerboard recognition technique that is robust to noise, surface distortion or discontinuity, supporting checkerboard recognition in dynamic conditions for a wider range of applications. When the checkerboard pattern is used in a projector camera system for geometry reconstruction, by using epipolar geometry, this technique can recognize the corresponding positions of the crossing points, even if the checkerboard pattern is only partly detected.