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A new separable moments based on Tchebichef-Krawtchouk polynomials

Orthogonal moments are beneficial tools for analyzing and representing images and objects. Different hybrid forms, which are first and second levels of combination, have been created from the Tchebichef and Krawtchouk polynomials. In this study, all the hybrid forms, including the first and second l...

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Main Authors: Idan, Zinah N., Abdulhussain, Sadiq H., Al-Haddad, Syed Abdul Rahman
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers 2020
Online Access:http://psasir.upm.edu.my/id/eprint/87616/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/87616/
https://ieeexplore.ieee.org/abstract/document/9018036
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spelling my.upm.eprints.876162022-07-06T08:21:16Z http://psasir.upm.edu.my/id/eprint/87616/ A new separable moments based on Tchebichef-Krawtchouk polynomials Idan, Zinah N. Abdulhussain, Sadiq H. Al-Haddad, Syed Abdul Rahman Orthogonal moments are beneficial tools for analyzing and representing images and objects. Different hybrid forms, which are first and second levels of combination, have been created from the Tchebichef and Krawtchouk polynomials. In this study, all the hybrid forms, including the first and second levels of combination that satisfy the localization and energy compaction (EC) properties, are investigated. A new hybrid polynomial termed as squared Tchebichef-Krawtchouk polynomial (STKP) is also proposed. The mathematical and theoretical expressions of STKP are introduced, and the performance of the STKP is evaluated and compared with other hybrid forms. Results show that the STKP outperforms the existing hybrid polynomials in terms of EC and localization properties. Image reconstruction analysis is performed to demonstrate the ability of STKP in actual images; a comparative evaluation is also applied with Charlier and Meixner polynomials in terms of normalized mean square error. Moreover, an object recognition task is performed to verify the promising abilities of STKP as a feature extraction tool. A correct recognition percentage shows the robustness of the proposed polynomial in object recognition by providing a reliable feature vector for the classification process. Institute of Electrical and Electronics Engineers 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87616/1/ABSTRACT.pdf Idan, Zinah N. and Abdulhussain, Sadiq H. and Al-Haddad, Syed Abdul Rahman (2020) A new separable moments based on Tchebichef-Krawtchouk polynomials. IEEE Access, 8. 41013 - 41025. ISSN 2169-3536 https://ieeexplore.ieee.org/abstract/document/9018036 10.1109/ACCESS.2020.2977305
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Orthogonal moments are beneficial tools for analyzing and representing images and objects. Different hybrid forms, which are first and second levels of combination, have been created from the Tchebichef and Krawtchouk polynomials. In this study, all the hybrid forms, including the first and second levels of combination that satisfy the localization and energy compaction (EC) properties, are investigated. A new hybrid polynomial termed as squared Tchebichef-Krawtchouk polynomial (STKP) is also proposed. The mathematical and theoretical expressions of STKP are introduced, and the performance of the STKP is evaluated and compared with other hybrid forms. Results show that the STKP outperforms the existing hybrid polynomials in terms of EC and localization properties. Image reconstruction analysis is performed to demonstrate the ability of STKP in actual images; a comparative evaluation is also applied with Charlier and Meixner polynomials in terms of normalized mean square error. Moreover, an object recognition task is performed to verify the promising abilities of STKP as a feature extraction tool. A correct recognition percentage shows the robustness of the proposed polynomial in object recognition by providing a reliable feature vector for the classification process.
format Article
author Idan, Zinah N.
Abdulhussain, Sadiq H.
Al-Haddad, Syed Abdul Rahman
spellingShingle Idan, Zinah N.
Abdulhussain, Sadiq H.
Al-Haddad, Syed Abdul Rahman
A new separable moments based on Tchebichef-Krawtchouk polynomials
author_facet Idan, Zinah N.
Abdulhussain, Sadiq H.
Al-Haddad, Syed Abdul Rahman
author_sort Idan, Zinah N.
title A new separable moments based on Tchebichef-Krawtchouk polynomials
title_short A new separable moments based on Tchebichef-Krawtchouk polynomials
title_full A new separable moments based on Tchebichef-Krawtchouk polynomials
title_fullStr A new separable moments based on Tchebichef-Krawtchouk polynomials
title_full_unstemmed A new separable moments based on Tchebichef-Krawtchouk polynomials
title_sort new separable moments based on tchebichef-krawtchouk polynomials
publisher Institute of Electrical and Electronics Engineers
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/87616/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/87616/
https://ieeexplore.ieee.org/abstract/document/9018036
_version_ 1738511961139707904
score 13.211869

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