Abstract
This paper proposes a kind of feature extraction based efficient registration algorithm including coarse to fine registrations. During coarse registration, a very fast feature extraction method is present. Then an initial estimate for relative rigid-body transform can be brought to realization, through matching these regions with eigenvectors of covariance matrix of feature-closed point clouds, During coarse registration, a new fine registration method will be present in this paper based Iterative Closest Point (ICP) algorithm which had been used in fine registration to align view pairs after the coarse registration. Experimental results of 3D images taken by laser scanner are carried out to compare the convergence and registration result. The proposed registration approach can realize automatic registration without any assumptions about their initial positions, and can overcome the problems of traditional ICP in low overlapping and bad initial estimate. The proposed feature extraction based ICP algorithm and measure procedure management provides an efficient 3D modeling for computer-aided engineering and computer-aided design.
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