Matching for Shape Defect Detection
CAIP '99 Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns
Iterative closest SIFT formulation for robust feature matching
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
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A simple and practical method is proposed that facilitates fast spatial neighborhood operations in a non-ordered point list containing coordinates of a planar point set. Given a rectangular neighborhood, O(Nq) operations are needed to scan the neighborhoods of N points in the list, where q is the average number of points in the neighborhood. The method uses a data structure that requires O(N) bytes of storage. The complexity of the algorithm that structures the data is O(N).