This thesis addresses the problem of registering one point set with respect to another. This problem arises in the context of the use of CMM/Scanners to inspect objects especially with freeform surfaces. The tolerance verification process now requires the comparison of measured points with the nominal geometry. This entails placement of the measured point set in the same reference frame as the nominal model. This problem is referred to as the registration or localization problem. In the most general form the tolerance verification task involves registering multiple point sets corresponding to multi-step scan of an object with respect to the nominal CAD model. This problem is addressed in three phases. This thesis presents a novel approach to automated inspection by matching point sets based on the Iterative Closest Point (ICP) algorithm. The Modified ICP (MICP) algorithm presented in the thesis improves upon the existing methods through the use of a localized region based triangulation technique to obtain correspondences for all the inspection points and achieves dramatic reduction in computational effort. The use of point sets to represent the nominal surface and shapes enables handling different systems and formats. Next, the thesis addresses the important problem of establishing registration between point sets in different reference frames when the initial relative pose between them is significantly large. A novel initial pose invariant methodology has been developed. Finally, the above approach is extended to registration of multiview inspection data sets based on acquisition of transformation information of each inspection view using the virtual gauging concept. This thesis describes implementation to address each of these problems in the area of automated registration and verification leading towards automatic inspection.