Least median of squares matching for automated detection of surface deformations

Detecting the difference between two surfaces without the aid of control points is desirable for many industrial applications. We tackle this problem by means of robust surface matching. In presence of local deformation, conventional surface matching algorithm with least square condition would fail. Efforts have been made by some researches to robustify the surface matching algorithm using M-estimators. We use least median of squares estimator and data snooping technique to robustify the surface matching algorithm and use a M-estimator to improve the efficiency of least median of squares estimator. Evaluation and comparison of these methods are carried out using simulative data. The result shows robust matching using least median of squares estimator can detect a local deformation that covers up to 50 percents of the surface and very small deformation can detected and it is not sensitive to position of deformation, which is much superior to other methods of robustifying surface matching.