Implicit Moment Invariants

Jan Flusser, Jaroslav Kautsky, Filip Sroubek

    Research output: Contribution to journalArticlepeer-review

    22 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)72-86
    Number of pages15
    JournalInternational Journal of Computer Vision
    Volume86
    Issue number1
    DOIs
    Publication statusPublished - Jan 2010

    Keywords

    • Implicit invariants
    • Invariants
    • Moments
    • Orthogonal polynomials
    • Polynomial image deformation

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