Jose Antonio Martin H. Machine Perception and Computer Vision page

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José Antonio Martín H.


Orthogonal Variant Moments:

José Antonio Martin H., Matilde Santos & Javier de Lope (2010), "Orthogonal Variant Moments Features in Image Analysis" , Information Sciences, March, 2010. Vol. 180(6), pp. 846 - 860. [DOI] [URL]

Invariant moments (e.g., the Hu invariant set) are statistical measures designed to remain constant after some transformations, such as object rotation, scaling, translation, or image illumination changes, in order to, e.g., improve the reliability of a pattern recognition system.

We propose the use of variant moments as an alternative to the classical approach.

Invariants are sensitive to any image change or perturbation for which they are not invariant, so any unexpected perturbation will affect the measurements. On the contrary, a variant moment is designed to be sensitive to a specific perturbation and thus any unexpected disturbance will not affect the objective of the measurement.