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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  1/2019 - 6

Efficient Shape Classification using Zernike Moments and Geometrical Features on MPEG-7 Dataset

ABBAS, S. See more information about ABBAS, S. on SCOPUS See more information about ABBAS, S. on IEEExplore See more information about ABBAS, S. on Web of Science, FARHAN, S. See more information about  FARHAN, S. on SCOPUS See more information about  FARHAN, S. on SCOPUS See more information about FARHAN, S. on Web of Science, FAHIEM, M. A. See more information about  FAHIEM, M. A. on SCOPUS See more information about  FAHIEM, M. A. on SCOPUS See more information about FAHIEM, M. A. on Web of Science, TAUSEEF, H. See more information about TAUSEEF, H. on SCOPUS See more information about TAUSEEF, H. on SCOPUS See more information about TAUSEEF, H. on Web of Science
 
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Download PDF pdficon (1,361 KB) | Citation | Downloads: 554 | Views: 1,308

Author keywords
classification algorithms, feature extraction, image classification, shape

References keywords
shape(23), recognition(12), pattern(11), machine(9), image(9), classification(8), learning(7), descriptors(7), retrieval(6), content(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-02-28
Volume 19, Issue 1, Year 2019, On page(s): 45 - 50
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.01006
Web of Science Accession Number: 000459986900006
SCOPUS ID: 85064223642

Abstract
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There is an urgent need and demand for manipulating images to extract useful information from them. In every field, whether it is biotechnology, botany, medical, robotics or machinery, the demand for extracting useful aspects of a specific targeted image is growing. Effective systems and applications have been introduced for this purpose: CBIR and MPEG-7 are most common applications. Shape extraction and recognition is used in image retrieval and matching. Complex objects can be identified and classified by extracting their shape. This paper proposes an efficient algorithm for shape classification. Analyses are made on MPEG-7 dataset using 1400 images belonging to 70 classes. Zernike Moments descriptor and geometrical features are used for classification purposes. Cross validation and percentage split are used to evaluate the proposed scheme. Experimental results proved the efficiency of the proposed approach with an accuracy of 92.45 percent on the challenging dataset.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 1 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 3
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Cited-By CrossRef

[1] Dental Impression Tray Selection From Maxillary Arch Images Using Multi-Feature Fusion and Ensemble Classifier, Hasan, Muhammad Asif, Abdullah, Norli Anida, Rahman, Mohammad Mustaneer, Idris, Mohd Yamani Idna Bin, Tawfiq, Omar F., IEEE Access, ISSN 2169-3536, Issue , 2021.
Digital Object Identifier: 10.1109/ACCESS.2021.3059785
[CrossRef]

[2] InShaDe: Invariant Shape Descriptors for visual 2D and 3D cellular and nuclear shape analysis and classification, Al-Thelaya, Khaled, Agus, Marco, Gilal, Nauman Ullah, Yang, Yin, Pintore, Giovanni, Gobbetti, Enrico, Calí, Corrado, Magistretti, Pierre J., Mifsud, William, Schneider, Jens, Computers & Graphics, ISSN 0097-8493, 2021.
Digital Object Identifier: 10.1016/j.cag.2021.04.037
[CrossRef]

[3] Comparative Study of Moments Shape Descriptors and propose a new hybrid Descriptor technique, Hamandi, Shaymaa M., Rahma, Abdul Monem S., Hassan, Rehab F., 2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS), ISBN 978-1-7281-3995-1, 2019.
Digital Object Identifier: 10.1109/ICICIS46948.2019.9014844
[CrossRef]

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