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A fast algorithm for the computation of axial moments and its application to the orthogonal fitting of curves

✍ Scribed by Roman M. Palenichka; Marek B. Zaremba

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
343 KB
Volume
36
Category
Article
ISSN
0031-3203

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✦ Synopsis

This paper describes a fast algorithm to compute local axial moments used in the detection of objects of interest in images. The basic idea is the elimination of redundant operations while computing axial moments for two neighboring angles of orientation. The main result is that the complexity of the recursive computation of axial moments becomes independent of the total number of computed moments at a given point, i.e., it is of the order O(N ) where N is the size of the data set. This result is of great importance in computer vision since many feature extraction methods rely on the computation of axial moments. The use of this algorithm for fast object skeletonization in images by orthogonal regression ΓΏtting is described in detail, with the experimental results conΓΏrming the theoretical computational complexity.

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