Abstract A 3D matching method based on genetic algorithm (GA) and model projection is presented, which is a process of searching for the best parameters of projective transform. Coarse to fine strategy is adopted. Firstly, based on the outermost boundary of model all the edges are matched. Then the correct initial values of parameters are obtained quickly to improve the efficiency of the algorithm. The fitness function of GA is based on 34 chamfer distance transform. Finally, label mapping is proposed to deal with the noise in distance map. Meanwhile, features of edge pixels, which are difficult to be applied directly to the distance map, are available to label map. Experimental results show that the proposed method is effective in 3D modelbased matching.
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2006, Vol. 19 
