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research-article

Quaternion Harmonic moments and extreme learning machine for color object recognition

Authors:

Noureddine En-nahnahi,

Said El Alaoui OuatikAuthors Info & Claims

Volume 78, Issue 15

Pages 20935 - 20959

https://doi.org/10.1007/s11042-019-7381-2

Published: 01 August 2019 Publication History

Abstract

The quaternary orthogonal moments have been widely used as color image descriptors owe to their remarkable color and shape information encapsulation capability. Their computation, however, depends on finding the optimal value of a unit pure quaternion parameter, which is done empirically and with no warranty of optimality. We propose a 2D color object recognition method that relies on the quaternion-valued parameter-free disc-harmonic moment invariants (QHMs) fed into the quaternion extreme learning machine (QELM). The role of this latter is to maintain the correlation between the four parts, real and imaginary, of the quaternary descriptor coefficients. Several datasets are used for recognition experiments. We draw the conclusion that: (1) our quaternion-valued QHMs invariants outperform other quaternary moments, (2) the quaternion-valued moment invariants give results better than the modulus-based moment invariants and (3) the QELM yields results better than the state-of-the-art classifiers.

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Cited By

El Alami AMesbah ABerrahou NLakhili ZBerrahou AQjidaa H(2023)Quaternion discrete orthogonal Hahn moments convolutional neural network for color image classification and face recognitionMultimedia Tools and Applications10.1007/s11042-023-14866-482:21(32827-32853)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14866-4
Liu JZhang J(2022)Target Recognition Technology of Multimedia Platform Based on a Convolutional Neural NetworkAdvances in Multimedia10.1155/2022/81889362022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/8188936
Hosny KDarwish MSalah ALi KAbdelatif A(2021)CUDAQuat: new parallel framework for fast computation of quaternion moments for color images applicationsCluster Computing10.1007/s10586-021-03271-x24:3(2385-2406)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10586-021-03271-x

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Quaternion Harmonic moments and extreme learning machine for color object recognition
1. Computing methodologies

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Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 78, Issue 15

Aug 2019

1603 pages

ISSN:1380-7501

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Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 August 2019

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Cited By

El Alami AMesbah ABerrahou NLakhili ZBerrahou AQjidaa H(2023)Quaternion discrete orthogonal Hahn moments convolutional neural network for color image classification and face recognitionMultimedia Tools and Applications10.1007/s11042-023-14866-482:21(32827-32853)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14866-4
Liu JZhang J(2022)Target Recognition Technology of Multimedia Platform Based on a Convolutional Neural NetworkAdvances in Multimedia10.1155/2022/81889362022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/8188936
Hosny KDarwish MSalah ALi KAbdelatif A(2021)CUDAQuat: new parallel framework for fast computation of quaternion moments for color images applicationsCluster Computing10.1007/s10586-021-03271-x24:3(2385-2406)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10586-021-03271-x

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