On 2D-3D Image Feature Detections for Image-To-Geometry Registration in Virtual Dental Model

3D digital smile design (DSD) gains great interest in dentistry because it enables esthetic design of teeth and gum. However, the color texture of teeth and gum is often lost/distorted in the digitization process. Recently, the image-to-geometry registration shade mapping (IGRSM) method was proposed for registering color texture from 2D photography to 3D mesh model. It allows better control of illumination and color calibration for automatic teeth shade matching. In this paper, we investigate automated techniques to find the correspondences between 3D tooth model and color intraoral photographs for accurately perform the IGRSM. We propose to use the tooth cusp tips as the correspondence points for the IGR because they can be reliably detected both in 2D photography and 3D surface scan. A modified gradient descent method with directional priority (GDDP) and region growing are developed to find the 3D correspondence points. For the 2D image, the tooth tips contour lines are extracted based on luminosity and chromaticity, the contour peaks are then detected as the correspondence points. From the experimental results, the proposed method shows excellent accuracy in detecting the correspondence points between 2D photography and 3D tooth model. The average registration error is less than 15 pixels for 4752×3168 size intraoral image.