New set of adapted Gegenbauer–Chebyshev invariant moments for image recognition and classification

Orthogonal moments and their invariants to geometric transformations for gray-scale images are widely used in many pattern recognition and image processing applications. In this paper, we propose a new set of orthogonal polynomials called adapted Gegenbauer–Chebyshev polynomials (AGC). This new set...

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Bibliographic Details
Published in:	The Journal of supercomputing Vol. 77; no. 6; pp. 5637 - 5667
Main Authors:	Hjouji, Amal, Bouikhalene, Belaid, EL-Mekkaoui, Jaouad, Qjidaa, Hassan
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2021 Springer Nature B.V
Subjects:	Chebyshev approximation Coils Compilers Computer Science Geometric transformation Image classification Image processing Interpreters Invariants Object recognition Pattern recognition Polynomials Processor Architectures Programming Languages means algorithm (FKM) Pattern recognition Fuzzy Adapted Gegenbauer–Chebyshev invariant moments Invariant moments Image classification
ISSN:	0920-8542, 1573-0484
Online Access:	Get full text
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