Surface detection with subvoxel accuracy using facet model and IDDG operator

A surface detection algorithm with sub voxel 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 3-D IDDG operator to estimate the gradient vector and 3-D directional derivatives. Subvoxel accuracy is achieved by locating the zeros of the 3-D 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.