抄録
A novel algorithm for rotational registration of dot-cloud data based on Local Consistency of Point Dispersion considering defect types (color LCPD) is proposed. In this approach, a new measurement of the local consistency of the distribution of the dot clouds in both data sets is developed, which can then be combined into a weighted-metric based on the importance of the defect types. This method is expected to be effective and robust in the registration of randomly distributed, inconsistent observations. It has been shown to converge to the true solution in a variety of cases involving both real and simulated data.
