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It is necessary to stitch small area of images together for large surface analysis while the measurement instrument used with a limited measurement area, e.g. White-light Interferometry (WLI)-based system. A new stitching method is proposed in this paper for diamond grinding wheel surface analysis. The images are captured by a WLI-based system and the 3D images’ stitching requires an overlapping region of 30%~50%. First, two-step intensity correlation matching method is used to obtain several pairs of matched points fast and the RANSAC (Random Sample Consensus) algorithm is adopted to screen them to get exact pairs of matched points. Then the measurement errors are adjusted and a stitched topography is got after data fusion. Experiments show that this method can effectively stitch 3D images of diamond grinding wheel together in less than 4 minutes with a correlation coefficient above 0.9 for two horizontal overlapping regions after adjustment.

The topograpgy characterization of grinding wheel grain is indispensable for precision grinding, it depends on accurate edge detecting and recognition of abrasive grains from wheel bond to a large extent. Due to different reflective characteristics arising among different materials, difference between maximum and minimum intensity (Δ ) of diamond is larger than that of bond. This paper uses a new method for grain edge detection of resin-bonded diamond grinding wheel that combines the improved Canny operator in Method of Maximum Classes Square Error (called as OTSU) with ΔI obtained by the white light interferometry (WLI). The experimental results show that the method based on improved Canny operator can effectively detect the edge of diamond grain.