7 March 2016 Explicit Krawtchouk moment invariants for invariant image recognition
Bin Xiao, Yanhong Zhang, Linping Li, Weisheng Li, Guoyin Wang
Author Affiliations +
Abstract
The existing Krawtchouk moment invariants are derived by a linear combination of geometric moment invariants. This indirect method cannot achieve perfect performance in rotation, scale, and translation (RST) invariant image recognition since the derivation of these invariants are not built on Krawtchouk polynomials. A direct method to derive RST invariants from Krawtchouk moments, named explicit Krawtchouk moment invariants, is proposed. The proposed method drives Krawtchouk moment invariants by algebraically eliminating the distorted (i.e., rotated, scaled, and translated) factor contained in the Krawtchouk moments of distorted image. Experimental results show that, compared with the indirect methods, the proposed approach can significantly improve the performance in terms of recognition accuracy and noise robustness.
© 2016 SPIE and IS&T 1017-9909/2016/$25.00 © 2016 SPIE and IS&T
Bin Xiao, Yanhong Zhang, Linping Li, Weisheng Li, and Guoyin Wang "Explicit Krawtchouk moment invariants for invariant image recognition," Journal of Electronic Imaging 25(2), 023002 (7 March 2016). https://doi.org/10.1117/1.JEI.25.2.023002
Published: 7 March 2016
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CITATIONS
Cited by 33 scholarly publications.
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KEYWORDS
Signal to noise ratio

Databases

Lithium

Interference (communication)

Direct methods

Distortion

Image analysis

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