A method of performing automated three-dimensional image registration of a part remotely positionable within an inspection cell, the method comprising the steps of: receiving model data for a three-dimensional model of the part; receiving data representing points on at least one surface of a part when in a measured pose within the inspection cell defining range data; and aligning the three-dimensional model of the part to the measured pose of the part, characterized by that the operation of aligning including: performing a registration of the three-dimensional model to the range data including utilizing data points on the three-dimensional model of the part defining model data as a source and the range data as a target, and determining a set of points in the range data having a high probability of corresponding to actual points on the three-dimensional model, and a transformation therebetween; and wherein the set of points in the range data having a high probability of corresponding to actual points in the three-dimensional model are a set of points in the range data that are closest to corresponding points in the three-dimensional model as calculated using an iterative closest point algorithm, and performing a registration of the determined set of points in the range data having a high correspondence probability to the three-dimensional model to include utilizing the range data having a high probability of corresponding to actual points on the three-dimensional model as a source and data points on the three-dimensional model of the part as a target. receiving model data for a three-dimensional model of the part; receiving data representing points on at least one surface of a part when in a measured pose within the inspection cell defining range data; and aligning the three-dimensional model of the part to the measured pose of the part, characterized by that the operation of aligning including: performing a registration of the three-dimensional model to the range data including utilizing data points on the three-dimensional model of the part defining model data as a source and the range data as a target, and determining a set of points in the range data having a high probability of corresponding to actual points on the three-dimensional model, and a transformation therebetween; and wherein the set of points in the range data having a high probability of corresponding to actual points in the three-dimensional model are a set of points in the range data that are closest to corresponding points in the three-dimensional model as calculated using an iterative closest point algorithm, and performing a registration of the determined set of points in the range data having a high correspondence probability to the three-dimensional model to include utilizing the range data having a high probability of corresponding to actual points on the three-dimensional model as a source and data points on the three-dimensional model of the part as a target. performing a registration of the three-dimensional model to the range data including utilizing data points on the three-dimensional model of the part defining model data as a source and the range data as a target, and determining a set of points in the range data having a high probability of corresponding to actual points on the three-dimensional model, and a transformation therebetween; and wherein the set of points in the range data having a high probability of corresponding to actual points in the three-dimensional model are a set of points in the range data that are closest to corresponding points in the three-dimensional model as calculated using an iterative closest point algorithm, and performing a registration of the determined set of points in the range data having a high correspondence probability to the three-dimensional model to include utilizing the range data having a high probability of corresponding to actual points on the three-dimensional model as a source and data points on the three-dimensional model of the part as a target.