Abstract

Radial moments of circular-harmonic functions are used for image normalization. The moment orders are lower than those used in the classical method. The principal axes of image are replaced by a mean direction of image. The influence of random and correlated noise on moment-based image normalization is analyzed. The new method is more robust than the classical method against background noise. Experimental comparisons between the two methods are given. The complete series of the radial moments of circular-harmonic functions can be represented in the Cartesian coordinate system by modified complex moments whose orders are real valued. An application of the new method to gray-level noisy-image recognition is demonstrated that is invariant under changes of position, rotation, scale, and intensity.

© 1987 Optical Society of America

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