Corner detection method based on rotation invariance

Aiming at the error detection of the chessboard corners caused by distortion and blur of microscopic imaging during the calibration processing of the micro stereovision, a corner detection method of chessboard based on rotation invariance is proposed, which studies the geometry of chessboard corners and sorts all the characteristic corners. Mathematical model is established through experiments, the confidence level of filtered characteristic corners are calculated, which extracts positions of the chessboard corners and validate the accuracy, the number of noise and the precision through a series of experiments. The results show that the accuracy rate of the corner detection based on rotation invariance reaches 91.2 %, and the mean square error of the re-projection error is approximately 0.1 pixels, which has a comparatively high accuracy and high precision.