Simple and fast computation of moments

Abstract In this paper we address the problem of efficient computation of moments from the boundary of a digital area. Boundary-based computation is superior to usual region-based approaches as the data dimension of boundary representations is substantially smaller than that of region representations. We investigate the inter-order relationship of moments. One of our results is that moments of higher order can be computed from moments of lower order. Based on this relationship a simple iterative algorithm is proposed for the computation of moments from a polygonal approximation of the boundary. In comparison with a direct computation method, our algorithm is simpler to program. The memory requirement is minimum. Simulation results show that a speed-up of factor 8 can be achieved using our algorithm. A special version of the algorithm can be utilized to compute moments from the run-length chain code of the boundary. Our algorithm can be applied to compute the most popular geometric moments as well as other types of moments like Legendre, Zernike, rotational and complex moments.

[1]  Paul J. Zsombor-Murray,et al.  Fast algorithm for the computation of moment invariants , 1987, Pattern Recognit..

[2]  Mehdi Hatamian,et al.  A real-time two-dimensional moment generating algorithm and its single chip implementation , 1986, IEEE Trans. Acoust. Speech Signal Process..

[3]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[4]  Ernest L. Hall,et al.  Three-Dimensional Moment Invariants , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  F. W. Kellaway,et al.  Advanced Engineering Mathematics , 1969, The Mathematical Gazette.

[6]  Demetri Psaltis,et al.  Image Normalization by Complex Moments , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Rui J. P. de Figueiredo,et al.  A general moment-invariants/attributed-graph method for three-dimensional object recognition from a single image , 1986, IEEE J. Robotics Autom..

[8]  F.W. Smith,et al.  Automatic Ship Photo Interpretation by the Method of Moments , 1971, IEEE Transactions on Computers.

[9]  S. S. Reddi,et al.  Radial and Angular Moment Invariants for Image Identification , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  J. F. Boyce,et al.  Moment invariants for pattern recognition , 1983, Pattern Recognit. Lett..

[11]  Robert B. McGhee,et al.  Aircraft Identification by Moment Invariants , 1977, IEEE Transactions on Computers.

[12]  Alastair R. Allen,et al.  A method for working out the moments of a polygon using an integration technique , 1990, Pattern Recognit. Lett..

[13]  R. Wong,et al.  Scene matching with invariant moments , 1978 .

[14]  Keping Chen Efficient parallel algorithms for the computation of two-dimensional image moments , 1990, Pattern Recognit..

[15]  Roland T. Chin,et al.  On Image Analysis by the Methods of Moments , 1988, IEEE Trans. Pattern Anal. Mach. Intell..