Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Feb 2021
Next issue: May 2021
Avg review time: 56 days


PUBLISHER

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


TRAFFIC STATS

1,601,842 unique visits
491,126 downloads
Since November 1, 2009



Robots online now
Googlebot
PetalBot


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 21 (2021)
 
     »   Issue 1 / 2021
 
 
 Volume 20 (2020)
 
     »   Issue 4 / 2020
 
     »   Issue 3 / 2020
 
     »   Issue 2 / 2020
 
     »   Issue 1 / 2020
 
 
 Volume 19 (2019)
 
     »   Issue 4 / 2019
 
     »   Issue 3 / 2019
 
     »   Issue 2 / 2019
 
     »   Issue 1 / 2019
 
 
 Volume 18 (2018)
 
     »   Issue 4 / 2018
 
     »   Issue 3 / 2018
 
     »   Issue 2 / 2018
 
     »   Issue 1 / 2018
 
 
 Volume 17 (2017)
 
     »   Issue 4 / 2017
 
     »   Issue 3 / 2017
 
     »   Issue 2 / 2017
 
     »   Issue 1 / 2017
 
 
  View all issues  


FEATURED ARTICLE

Improved Wind Speed Prediction Using Empirical Mode Decomposition, ZHANG, Y., ZHANG, C., SUN, J., GUO, J.
Issue 2/2018

AbstractPlus


SAMPLE ARTICLES

Indoor Localization using Voronoi Tessellation, ARIF, M., WYNE, S., JUNAID NAWAZ, A.
Issue 4/2018

AbstractPlus

Differential Evolution Implementation for Power Quality Disturbances Monitoring using OpenCL, SOLIS-MUNOZ, F. J., OSORNIO-RIOS, R. A., ROMERO-TRONCOSO, R. J., JAEN-CUELLAR, A. Y.
Issue 2/2019

AbstractPlus

Two Types of Fuzzy Logic Controllers for the Speed Control of the Doubly-Fed Induction Machine, SAIDI, A., NACERI, F., YOUB, L., CERNAT, M., GUASCH PESQUER, L.
Issue 3/2020

AbstractPlus

A Digital Signal Amplification Device for Microelectrode Arrays based on Stochastic Resonance, FAMBRINI, F., DESTRO-FILHO, J. B., Del Val CURA, L. M., SAQUI, D., SAITO, J. H.
Issue 3/2020

AbstractPlus

Improvements on the Incremental Conductance MPPT Method Applied to a PV String with Single-Phase to Three-Phase Converter for Rural Grid Applications, MONTEIRO, L. F. C., FREITAS, C. M., BELLAR, M. D.
Issue 1/2019

AbstractPlus

Analysis and Control of a New Dual-input Impedance-based DC–DC Converter for Hybrid PV-FC Systems, BAYAT, P., BAGHRAMIAN, A.
Issue 4/2019

AbstractPlus




LATEST NEWS

2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
Starting on the 15th of June 2020 we wiil introduce a new policy for reviewers. Reviewers who provide timely and substantial comments will receive a discount voucher entitling them to an APC reduction. Vouchers (worth of 25 EUR or 50 EUR, depending on the review quality) will be assigned to reviewers after the final decision of the reviewed paper is given. Vouchers issued to specific individuals are not transferable.

2019-Dec-16
Starting on the 15th of December 2019 all paper authors are required to enter their SCOPUS IDs. You may use the free SCOPUS ID lookup form to find yours in case you don't remember it.

2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

Read More »


    
 

  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
 
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

Download PDF pdficon (1,361 KB) | Citation | Downloads: 503 | Views: 1,255

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
Quick view
Full text preview
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

[1] T. Dharani and I. L. Aroquiaraj, "A survey on content based image retrieval," in Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 IEEE Conference on, 2013, pp. 485-490.
[CrossRef] [SCOPUS Times Cited 50]


[2] C. Iakovidou, N. Anagnostopoulos, A. C. Kapoutsis, Y. Boutalis and S. A. Chatzichristofis , "Searching images with MPEG-7 (& MPEG-7-like) powered localized descriptors: the SIMPLE answer to effective content based image retrieval," in Content-Based Multimedia Indexing, 2014 IEEE 12th International Workshop on, 2014, pp. 1-6.
[CrossRef]


[3] M. Anvaripour and H. Ebrahimnezhad, "Accurate object detection using local shape descriptors," Pattern Analysis and Applications, vol. 18, no. 2, pp. 277-295, 2015.
[CrossRef]


[4] S. Seth, P. UpaRedhyay, R. Shroff and R. Komatwar, "Review of content based image retrieval systems," International Journal of Engineering Trends and Technology, vol. 19, no. 4, pp. 178-181, 2015.

[5] L. Zhao, Q. Peng and B. Huang, "Shape matching algorithm based on shape contexts," IET Computer Vision, vol. 9, no. 5, pp. 681-690, 2015.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 13]


[6] A. Barman and P. Dutta, "Facial expression recognition using shape signature feature," in Research in Computational Intelligence and Communication Networks, 2017 IEEE Third International Conference on, 2017, pp. 174-179.
[CrossRef] [SCOPUS Times Cited 5]


[7] G. Zhang and D. Lu, "Review of shape representation and description techniques," Pattern Recognition, vol. 37, no. 1, pp. 1-19, 2004.
[CrossRef] [Web of Science Times Cited 1032] [SCOPUS Times Cited 1350]


[8] S. Piérard, A. Lejeune and M. V. Droogenbroeck, "Boosting shape classifiers accuracy by considering the inverse shape," Journal of Pattern Recognition Research, vol. 11, no. 1, pp. 41-54, 2016.
[CrossRef] [Web of Science Times Cited 1]


[9] S. Sharma and P. Khanna, "Computer-aided diagnosis of malignant mammograms using zernike moments" Journal of Digital Imaging, vol. 28, no. 1, pp. 77-90, 2015.
[CrossRef] [Web of Science Times Cited 49] [SCOPUS Times Cited 63]


[10] C. Lin, C. M. Pun, C. M. Vong and D. Adjeroh, "Efficient shape classification using region descriptors," Multimedia Tools and Applications, vol. 76, no. 1, pp. 83-102, 2017.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 4]


[11] M. Bicego and P. Lovato, "A bioinformatics approach to 2D shape classification," Computer Vision and Image Understanding, vol. 145, pp. 59-69, 2016.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 15]


[12] S. Battiato, G. M. Farinella, O. Giudice and G. Puglisi, "Aligning shapes for symbol classification and retrieval," Multimedia Tools and Applications, vol. 75, no. 10, pp. 5513-5531, 2016.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 7]


[13] S. Escalera, A. Fornés, O. Pujol, P. Radeva, G. Sánchez, et al., "Blurred shape model for binary and grey-level symbol recognition," Pattern Recognition Letters, vol. 30, no. 15, pp. 1424-1433, 2009.
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 67]


[14] S. Belongie, J. Malik and J. Puzicha, "Shape matching and object recognition using shape contexts," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 4, pp. 509-522, 2002.
[CrossRef] [Web of Science Times Cited 3663] [SCOPUS Times Cited 4849]


[15] D. Sharvit, J. Chan, H. Tek and B. B. Kimia, "Symmetry-based indexing of image databases," in Content-Based Access of Image and Video Libraries, 1998 IEEE Workshop on, pp. 56-62, 1998.
[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 54]


[16] H. Ling and D. W. Jacobs, "Shape classification using the inner-distance," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 2, pp. 286-299, 2007.
[CrossRef] [Web of Science Times Cited 705] [SCOPUS Times Cited 888]


[17] X. Bai, B. Wang, C. Yao, W. Liu and Z. Tu, "Co-transduction for shape retrieval," IEEE Transactions on Image Processing, vol. 21, no 5, pp. 2747-2757, 2012.
[CrossRef] [Web of Science Times Cited 68] [SCOPUS Times Cited 83]


[18] L. J. Latecki, R. Lakamper and T. Eckhardt, "Shape descriptors for non-rigid shapes with a single closed contour," in Computer Vision and Pattern Recognition, 2000 IEEE Conference on, 2000, pp. 424-429.
[CrossRef]


[19] C. Lin and C. M. Pun, "Robust region descriptors for shape classification," in Computer Graphics, Imaging and Visualization, 2016 International Conference on, 2016, pp. 269-272.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 1]


[20] C. Pillai, "A survey of shape descriptors for digital image processing," International Journal of Computer Science and Information Technology and Security, vol. 3, no. 1, pp. 44-50, 2013.

[21] I. K. Kazmi, L. You and J. J. Zhang, "A survey of 2D and 3D shape descriptors," in Computer Graphics Imaging and Visualization, 2013 Tenth International Conference on, 2013, pp. 1-10.
[CrossRef] [SCOPUS Times Cited 36]


[22] W. Y. Kim and Y. S. Kim, "A region-based shape descriptor using zernike moments," Signal Processing: Image Communication, vol. 16, no. 1, pp. 95-102, 2000.
[CrossRef] [Web of Science Times Cited 237] [SCOPUS Times Cited 303]


[23] M. Murat, S.W. Chang, A. Abu, H. J. Yap and K. T. Yong, "Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach," PeerJ, vol. 5, no. e3792, pp. 1-23, 2017.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 9]


[24] M. Yang, K. Kpalma and J. Ronsin, "A survey of shape feature extraction techniques," Pattern Recognition Techniques, Technology and Applications, Austria, pp. 43-90, 2008.

[25] S. G. Wu, F. S. Bao, E. Y. Xu, Y. X. Wang, Y. F. Chang, et al., "A leaf recognition algorithm for plant classification using probabilistic neural network," in Signal Processing and Information Technology, 2007 IEEE International Symposium on, 2007, pp. 11-16.
[CrossRef] [SCOPUS Times Cited 449]


[26] J. G. Cleary and L. E. Trigg, "K*: an instance-based learner using an entropic distance measure," in Machine Learning, 1995 12th International Conference on, 1995, pp. 108-114.
[CrossRef]


[27] D. W. Aha, D. Kibler and M. K. Albert, "Instance-based learning algorithms," Machine Learning, vol. 6, no. 1, pp. 37-66, 1991.
[CrossRef]


[28] E. Bauer and R. Kohavi, "An empirical comparison of voting classification algorithms: bagging, boosting, and variants," Machine Learning, vol. 36, no. 1, pp. 105-139, 1999.
[CrossRef] [Web of Science Times Cited 1293] [SCOPUS Times Cited 1572]


[29] T. K. Ho, "The random subspace method for constructing decision forests," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 8, pp. 832-844, 1998.
[CrossRef] [SCOPUS Times Cited 3682]


[30] C. E. Rasmussen, "Gaussian processes in machine learning," Advanced Lectures on Machine Learning, Germany, pp. 63-71, 2004.
[CrossRef] [Web of Science Times Cited 865] [SCOPUS Times Cited 844]


[31] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, et al., "The WEKA data mining software: an update," ACM SIGKDD Explorations Newsletter, vol. 11, no. 1, pp. 10-18, 2009.
[CrossRef]


[32] S. Escalera, A. Fornes, O. Pujol, J. Llados and P. Radeva, "Circular blurred shape model for multiclass symbol recognition," IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 41, no. 2, pp. 497-506, 2011.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 34]


[33] X. Yang, S. Koknar-Tezel and L. J. Latecki, "Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval," in Computer Vision and Pattern Recognition, 2009 IEEE Conference on, 2009, pp. 357-364.
[CrossRef]




References Weight

Web of Science® Citations for all references: 8,049 TCR
SCOPUS® Citations for all references: 14,378 TCR

Web of Science® Average Citations per reference: 237 ACR
SCOPUS® Average Citations per reference: 423 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 2021-03-30 08:57 in 186 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2021
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.




Website loading speed and performance optimization powered by: