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A New Set of Normalized Geometric Moments Based on Schlick’s Approximation

  • Ramakrishnan Mukundan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4842)

Abstract

Schlick’s approximation of the term x p is used primarily to reduce the complexity of specular lighting calculations in graphics applications. Since moment functions have a kernel defined using a monomial x p y p , the same approximation could be effectively used in the computation of normalized geometric moments and invariants. This paper outlines a framework for computing moments of various orders of an image using a simplified kernel, and shows the advantages provided by the approximating function through a series of experimental results.

Keywords

Image Classification Moment Function Central Moment Moment Computation Moment Invariant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ramakrishnan Mukundan
    • 1
  1. 1.Department of Computer Science and Software Engineering, University of Canterbury, ChristchurchNew Zealand

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