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

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


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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
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

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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

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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  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 10,906 TCR
SCOPUS® Citations for all references: 14,650 TCR

Web of Science® Average Citations per reference: 321 ACR
SCOPUS® Average Citations per reference: 431 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-06-14 00:48 in 185 seconds.

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