Implicit Moment Invariants

Authors:
Jan Flusser;Jaroslav Kautsky;Filip Šroubek
Affiliations:
Institute of Information Theory and Automation of the ASCR, Prague 8, Czech Republic 182 08;The Flinders University of South Australia, Adelaide, Australia;Institute of Information Theory and Automation of the ASCR, Prague 8, Czech Republic 182 08
Venue:
International Journal of Computer Vision
Year:
2010

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Abstract

The use of traditional moment invariants in object recognition is limited to simple geometric transforms, such as rotation, scaling and affine transformation of the image. This paper introduces so-called implicit moment invariants. Implicit invariants measure the similarity between two images factorized by admissible image deformations. For many types of image deformations traditional invariants do not exist but implicit invariants can be used as features for object recognition. In the paper we present implicit moment invariants with respect to polynomial transform of spatial coordinates, describe their stable and efficient implementation by means of orthogonal moments, and demonstrate their performance in artificial as well as real experiments.