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Efficient Shape Classification using Zernike Moments and Geometrical Features on MPEG-7 DatasetABBAS, S.   , FARHAN, S. , FAHIEM, M. A. , TAUSEEF, H. |
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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
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. |
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[1] Interior Distance Ratio to a Regular Shape for Fast Shape Recognition, Li, Zekun, Guo, Baolong, Li, Cheng, Symmetry, ISSN 2073-8994, Issue 10, Volume 14, 2022.
Digital Object Identifier: 10.3390/sym14102040 [CrossRef]
[2] 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]
[3] 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, Issue , 2021.
Digital Object Identifier: 10.1016/j.cag.2021.04.037 [CrossRef]
[4] 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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Faculty of Electrical Engineering and Computer Science
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
