Moment Invariants and Quantization Effects

Authors:
G. I. Salama;A. L. Abbott
Affiliations:
-;-
Venue:
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Year:
1998

Citing 5
Cited 1

On digital approximation of moment invariants

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Contour sequence moments for the classification of closed planar shapes

Pattern Recognition
A survey of moment-based techniques for unoccluded object representation and recognition

CVGIP: Graphical Models and Image Processing
Affine moment invariants: a new tool for character recognition

Pattern Recognition Letters
On Image Analysis by Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence

Improved Scheme for Object Searching Using Moment Invariants

PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing

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Abstract

This paper considers the effect of spatial quantization on several moment invariants. Of particular interest are the affine moment invariants, which have emerged in recent years as a useful tool for image reconstruction, image registration, and recognition of deformed objects. Traditional analysis assumes moments and moment invariants for images that are defined in the continuous domain. In practice, however, the digitization process introduces errors that violate the invariance assumption. This paper presents an analysis of quantization-induced error on (two-dimensional) Hu moment invariants and affine moment invariants, and on invariants derived from (one-dimensional) contour moments. Error bounds are given in several cases.