Refined translation and scale Legendre moment invariants

Authors:
Khalid M. Hosny
Affiliations:
Department of Information Technology, Faculty of Computers and Informatics, Zagazig University, Zagazig, Egypt
Venue:
Pattern Recognition Letters
Year:
2010

Citing 6
Cited 2

On Image Analysis by the Methods of Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
On Image Analysis by Moments

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Robust Line Fitting in a Noisy Image by the Method of Moments

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An Efficient Method for the Computation of Legendre Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Legendre moment computation for grey level images

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Exact Legendre moment computation for gray level images

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Fast and low-complexity method for exact computation of 3D Legendre moments

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Image analysis by Gaussian-Hermite moments

Signal Processing

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Abstract

Orthogonal Legendre moments are used in several pattern recognition and image processing applications. Translation and scale Legendre moment invariants were expressed as a combination of the approximate original Legendre moments. The shifted and scaled Legendre polynomials were expressed in terms of the original Legendre polynomials according to complicated and time-consuming algebraic relations. In this paper, refined translation-scale Legendre moment invariants are obtained through the exact computation of original Legendre moments which completely remove approximation. Fast straightforward computation of central Legendre moments significantly reduces the computational time. According to the tremendous reduction of the computational complexity, the refined set of Legendre invariants is suitable for large size images. The performance of descriptors is evaluated by using a set of standard images.