Adding Chaos to Differential Evolution for Range Image Registration

This paper presents a method for automatically pair-wise registering range images. Registration is effected adding chaos to a Differential Evolution technique and by applying the Grid Closest Point algorithm to find the best possible transformation of the second image causing 3D reconstruction of the original object. Experimental results show the capability of the method in picking up efficient transformations of images with respect to the classical Differential Evolution. The proposed method offers a good solution to build complete 3D models of objects from 3D scan datasets.