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Taking all above three aspects into account, the convergence of 
LND is much better than that of ICP. 
4.2 Computational Efficiency 
The computational efficiency is measured by the time 
consumed. This experiment is performed on a computer with 
MS windows 2000, Intel II667Mhz, and 300M memory. All the 
three experiments, ICP consumes about 10 times time more 
than LND used. With high computational efficiency, LND can 
be applied to large data sets. 
The reason for LND’s so high computational efficiency is 
related on the following two aspects: 1) LND constructs the 
point’s correspondence without exhaustive search process that 
used by ICP. According the statistical result from amount 
simulated experimental results; NDCC adopted by LND can 
determine one corresponding points within 6 iterations (for 
detail, See Section 2.2). 2) Surface moves close to each other 
alone the surface normal vector, which is closest route between 
two surfaces. 
5 CONCLUSION 
The correspondence criterion is the most importance step for a 
surface matching algorithm. In this paper, An efficient 
correspondence criterion, called NDCC, for 3D surface 
matching is proposed in this paper. Then a complete surface 
matching algorithm, called LND, using NDCC is also given. 
Focusing on the convergence rate and computational efficiency, 
a serials of experiments based on simulated data sets are 
performed to make an in-depth analyses of proposed method. 
Compared with ICP, the efficiency of LND is higher than ICP. 
Moreover, LND converges faster than ICP. 
ACKNOWLEDGMENT 
This work is supported by the Doctoral Innovation Foundation 
of Southwest Jiaotong University. 
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