Moment-Based Image Normalization With High Noise-Tolerance

In this paper the effects of noise with nonzero mean on existing moment-based image normalization methods are studied. Several modifications to reduce noise sensitivity are presented and tested. They involve nonlinear mapping and fractional- and negative-order moments.

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

[2]  M. Teague.  Image analysis via the general theory of moments , 1980 .

[3]  Roland T. Chin,et al.  On image analysis by the methods of moments , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  H. Arsenault,et al.  Noisy-image normalization using low-order radial moments of circular-harmonic functions , 1987 .

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

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