Detection and 3-D Visualization of Human Tooth Surface Cracks Using Line Structured Light

Surface crack on teeth is a manifestation of structural damage, severely impacting individuals’ health and quality of life. Inspired by the achievement of 3-D computer vision technology in surface defect detection, a method is proposed for crack detection based on line structured light and digital image correlation, aiming at achieving 3-D detection and visualization of cracks on the surface of teeth. This approach discerns cracks by scrutinizing high-strain zones in the point cloud data, derived from the tooth surface through line structured light. To obtain good visualization results, this method refines the detected cracks in the principal strain field and extracts the 3-D skeleton of the cracks. The similarity between the crack shapes extracted by this method and those observed via microscope is over 98%. Experimental results demonstrate that this method provides an accurate and visually effective solution for 3-D detection of cracks on tooth surface. The proposed method offers a viable solution for surface crack detection in other engineering structures.