Surface detection with subvoxel accuracy using facet model and IDDG operator

A surface detection algorithm with subvoxel accuracy is presented to extract edge and surface information from computed tomography (CT) images for virtual measurement and reverse engineering. The proposed algorithm employs the facet model and 3D IDDG operator to estimate the gradient vector and 3D directional derivatives. Subvoxel accuracy is achieved by locating the zeros of the 3D second directional derivative along the estimated gradient direction. Adaptive gradient threshold is used for the surface detector to improve the algorithm performance when applied to images with non-uniform contrast caused by CT artifacts, such as beam-hardening. Experiment results are presented to demonstrate the efficacy of the proposed method