Subpixel corner point detecting method based on greyscale constraint used for calibrating industrial microscopic systems

To solve the problems of missed detection, repeated detection and low precision in the process of subpixel corner point detection of black-and-white checkerboard used for calibrating microscopic devices in complexed industrial environment, a new detection method based on greyscale constraint on the four-neighbourhood diagonal was proposed in the paper. By analysing geometric characteristics of the four-neighbourhood region and the grayscale features in diagonal direction, the SINC greyscale distribution was adopted to constrain corner point position, which realised rapid detection of subpixel corner point. Comparing with the existing methods, in the new method proposed the rate of repeated detection and missed detection decreased by about 20% and 2% respectively, which achieved a high rate of detecting accuracy over 99.9%. Meanwhile, the maximum error of corner point detection lowered from ±0.6pix to ±0.3pix, which showed that precision improved by about 50%. Finally, microscopic calibrating experiments used for micro-hole centring system were carried out. The results show centring error was reduced from 10 μm (before calibration) to 3 μm (after calibration), and centring precision was increased by about 75%. It demonstrated that the new method improved the accuracy and precision effectively, which verified its applicable feasibility of microscopic calibration used in industry spots.