A checkerboard pattern corners auto-detection method so-called circle corner detector for camera calibration is presented based on the grey-level difference, and it can detect the checkerboard corners from the noise-image or blurred image without any image preprocessing. Firstly, a circle corner detector is designed for checkerboard corners detection, getting a preliminary result by the grey-level difference between the corner and its neighboring points. Secondly, the pixel level corners can be obtained through sifting the preliminary results according to the feature of the checkerboard pattern corners whose angle are nearly right-angle and grey value nearby is symmetry. Finally, a sub-pixel level corner can be achieved by grey-level squared weight-center method and therefore correct position of the checkerboard corner can be determined. The experiment results show that a high accuracy of checkerboard pattern corner detection has been achieved, and the corner reprojection error is less than 0.1 pixel level even though the image is blurred. For the circle-corner-detector based checkerboard pattern corners auto-detection method can obtain the splayed angle value of the corner, it can also be applied for various corner detection with special angles, and also for its high calculating speed and high accuracy, it can be appropriate for on-line camera calibration in machine vision.