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Pattern Analysis and Applications
Published in: Pattern Analysis and Applications 2/2014

01-05-2014 | Theoretical Advances

Legendre moment invariants to blur and affine transformation and their use in image recognition

Authors: Xiubin Dai, Hui Zhang, Tianliang Liu, Huazhong Shu, Limin Luo

Published in: Pattern Analysis and Applications | Issue 2/2014

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Abstract

The processing of the images simultaneously degraded by blur and affine transformation has become a key task in many applications and many novel methods are designed specifically for it in which the moment-based methods play an important role. However, the existing moment-based methods all resort to non-orthogonal moments invariants which have problem of information redundancy and are sensitive to noise. In this paper, we construct a new set of combined invariants of orthogonal Legendre moments which hold for blur and affine transformation together. The experimental results show that the proposed invariants have better discriminative power and robustness to noise with the comparison to other invariants.
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Appendix
Available only for authorised users
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Metadata
Title
Legendre moment invariants to blur and affine transformation and their use in image recognition
Authors
Xiubin Dai
Hui Zhang
Tianliang Liu
Huazhong Shu
Limin Luo
Publication date
01-05-2014
Publisher
Springer London
Published in
Pattern Analysis and Applications / Issue 2/2014
Print ISSN: 1433-7541
Electronic ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-012-0273-y

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