Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Aug 2018
Next issue: Nov 2018
Avg review time: 80 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

2,048,865 unique visits
545,904 downloads
Since November 1, 2009



Robots online now
Googlebot


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 18 (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
 
 
 Volume 16 (2016)
 
     »   Issue 4 / 2016
 
     »   Issue 3 / 2016
 
     »   Issue 2 / 2016
 
     »   Issue 1 / 2016
 
 
 Volume 15 (2015)
 
     »   Issue 4 / 2015
 
     »   Issue 3 / 2015
 
     »   Issue 2 / 2015
 
     »   Issue 1 / 2015
 
 
  View all issues  




SAMPLE ARTICLES

Spatiotemporal Data Mining for Distribution Load Expansion, ARANGO, H. G., LAMBERT-TORRES, G., de MORAES, C. H. V., BORGES DA SILVA, L. E.
Issue 3/2016

AbstractPlus

Correction Impulse Method for Turbo Decoding over Middleton Class-A Impulsive Noise, TRIFINA, L., TARNICERIU, D., ANDREI, M.
Issue 4/2016

AbstractPlus

An Analysis of a Hard Real-Time Execution Environment Extension for FreeRTOS, STANGACIU, C., MICEA, M., CRETU, V.
Issue 3/2015

AbstractPlus

A PEG Construction of LDPC Codes Based on the Betweenness Centrality Metric, BHURTAH-SEEWOOSUNGKUR, I., CATHERINE, P. C., SOYJAUDAH, K. M. S.
Issue 2/2016

AbstractPlus

Signal Integrity Applications of an EBG Surface, MATEKOVITS, L., DE SABATA, A.
Issue 2/2015

AbstractPlus

Design Options for Thermal Shutdown Circuitry with Hysteresis Width Independent on the Activation Temperature, PLESA, C.-S., NEAG, M., RADOIAS, L.
Issue 1/2017

AbstractPlus




LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


    
 

  3/2011 - 13

Application of Rosette Pattern for Clustering and Determining the Number of Cluster

SADR, A. See more information about SADR, A. on SCOPUS See more information about SADR, A. on IEEExplore See more information about SADR, A. on Web of Science, MOMTAZ, A. K. See more information about MOMTAZ, A. K. on SCOPUS See more information about MOMTAZ, A. K. on SCOPUS See more information about MOMTAZ, A. K. 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 (2,657 KB) | Citation | Downloads: 805 | Views: 2,864

Author keywords
clustering, Fuzzy C-means (FCM), pattern recognition, Rosette Pattern, validity index

References keywords
clustering(17), pattern(12), fuzzy(11), algorithms(8), recognition(7), data(7), analysis(7), rosette(5), hall(5), clusters(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 77 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03013
Web of Science Accession Number: 000296186700013
SCOPUS ID: 80055116504

Abstract
Quick view
Full text preview
Clustering is one of the most important research topics which has many practical applications such as medical imaging and Non-Destructive Testing (NDT). Most clustering algorithms like K-means, fuzzy C-Means (FCM) and their derivatives require the number of clusters as one of the initializing parameters. This paper proposes an algorithm for image clustering with no need to any initializing parameter. In this state-of-the-art, an image is sampled based on a rosette pattern and according to the pattern characteristics, the extracted samples are clustered and then the number of clusters is determined. The centroids of classes are computed by means of a method based on calculation of distribution function. Based on different data sets, the results show that the algorithm improves the capability of the clustering by a minimum of 62.26% and 87.62% in comparison with FCM and K-means algorithms, respectively. Moreover, in dealing with high resolution data sets, the efficiency of the algorithm in clusters detection and run time improvement increases considerably.


References | Cited By  «-- Click to see who has cited this paper

[1] A. K. Jain, R. C. Dubes, Algorithms for clustering data, Prentice-Hall, Englewood Cliffs, NJ, 1988.

[2] P. H. A. Sneath, R. R. Sokal, Numerical taxonomy, Freeman, San Francisco, London, 1973.

[3] B. King, Step-wise clustering procedures, J. Am. Statist. Assoc. vol. 69, pp. 86-101, 1967.
[CrossRef]


[4] J. MacQueen, "Some methods for classification and analysis of multivariate observations," Fifth Berkeley Symposium on Mathematics, Statistics and Probability, University of California Press, pp. 281-297, 1967.

[5] B. S. Everitt and D. J. Hand, Finite mixture distributions, London, U.K.: Chapman and Hall, 1981.

[6] G. H. Ball, D. I. Hall, "ISODATA- A novel method of data analysis and classification," Stanford Res. Inst., California, 1965.

[7] E. W. Forgy, "Cluster analysis of multivariate data: Efficiency vs. interpretability of classifications," Biometrics, vol 21, pp. 768-769, 1965.

[8] S. Eschrich, K. Jingwei, L. O. Hall, D. B. Goldgof, "Fast accurate fuzzy clustering through data reduction," IEEE Trans. Fuzzy Systems, vol. 11, no. 2, pp. 262-270, 2003.
[CrossRef] [Web of Science Times Cited 120] [SCOPUS Times Cited 142]


[9] M. Steinbach, G. Karypis, V. Kumar, "A comparison of document clustering techniques," KDD Workshop on Text Mining, 2000.

[10] D. Pelleg, A. Moore, "Accelerating exact k-means algorithms with geometric reasoning," Proc. Fifth Internat. Conf. on Knowledge Discovery in Databases, AAAI Press, pp. 277-281, 1999.

[11] P. S. Bradley, U. Fayyad, C. Reina, "Scaling clustering algorithms to large databases," Proc. 4th KDD.1998.

[12] D. Pelleg, A. Moore, "X-means: Extending k-means with efficient estimation of the number of clusters," 17th Int. Conf. on Machine Learning. pp. 727-734, 2000.

[13] L. Kaufman, P. J. Rousseeuw, "Finding groups in data: An introduction to cluster analysis," Wiley series in Probability and Statistics, 2005.

[14] A. K. Jain, "Data clustering: 50 years beyond K-means," Pattern Recognition Letters, vol. 31, pp. 651-666, 2010.
[CrossRef] [Web of Science Times Cited 2048] [SCOPUS Times Cited 2706]


[15] J. C. Dunn, "A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters," J. Cyberne, vol. 3, pp. 32-57, 1973.
[CrossRef] [SCOPUS Times Cited 3108]


[16] J. C. Bezdek, Pattern recognition with fuzzy objective function algorithms, Plenum Press, New York, 1981.

[17] H. Sun, S. Wang, Q. Jiang, "FCM-based model selection algorithms for determining the number of clusters," Pattern Recognition Society, vol. 37, no. 10, pp. 2027-2037, 2004.

[18] A. Baraldi, P. Blonda, "A survey of fuzzy clustering algorithms for pattern recognition- part I," IEEE Trans. Syst. Man, Cybern. B, vol. 29, no. 6, pp. 778-785, 1999.
[CrossRef] [PubMed] [Web of Science Times Cited 217] [SCOPUS Times Cited 258]


[19] E. R. Hruschka, R. J. G. B. Campello, A. A. Freitas, and A. de Carvalho, "A survey of evolutionary algorithms for clustering," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 39, no. 2, pp. 133-155, March 2009.
[CrossRef] [Web of Science Times Cited 279] [SCOPUS Times Cited 382]


[20] U. Maulik, S. Bandyopadhyay, "Performance evaluation of some clustering algorithms and validity indices," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 12, pp. 1650-1654, 2002.
[CrossRef] [Web of Science Times Cited 510] [SCOPUS Times Cited 643]


[21] M. K. Pakhira, U. Maulik, and S. Bandyopadhyay, "Validity index for crisp and fuzzy clusters," Pattern Recognition, vol. 37, no. 3, pp. 487-501, 2004.
[CrossRef] [Web of Science Times Cited 291] [SCOPUS Times Cited 392]


[22] S. M. Pan and K. S. Cheng, "Evolution-based tabu search approach to automatic clustering," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 37, no. 5, pp. 827-838, Sep. 2007.
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 40]


[23] Y. Wang, C. Li, and Y. Zuo, "A Selection model for optimal fuzzy clustering algorithm and number of clusters based on competitive comprehensive fuzzy evaluation," IEEE Tran. on Fuzzy Systems, vol. 17, (3), pp. 568-577, 2009.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 37]


[24] S. Saha and S. Bandyopadhyay, "Performance evaluation of some symmetry-based cluster validity indexes," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 39, no. 4, pp. 420-425, Jul. 2009.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 22]


[25] C. Fowlkes, S. Belongie, F. Chung, and J. Malik, "Spectral grouping using the nystrom method," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 2, pp. 214-225, Feb. 2004.
[CrossRef] [PubMed] [Web of Science Times Cited 523] [SCOPUS Times Cited 818]


[26] J. Shi and J. Malik, "Normalized cuts and image segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888-905, Aug. 2000.
[CrossRef] [Web of Science Times Cited 5778] [SCOPUS Times Cited 8348]


[27] S. X. Yu, J. Shi, "Multiclass spectral clustering," Proc. Int. Conf. on Computer Vision, pp. 313-319, 2003.
[CrossRef]


[28] M. Belkin, P. Niyogi, "Laplacian eigenmaps and spectral techniques for embedding and clustering," Advances in Neural Information Processing Systems, vol. 14, pp. 585-591, 2002.

[29] W. Y. Chen, Y. Song, H. Bai, C J. Lin, and E. Y. Chang, "Parallel spectral clustering in distributed systems", IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 33, no. xx, 2011, to be published.

[30] R. M. Gray, J. C. Young, and A. K. Aiyer, "Minimum discrimination information clustering: modeling and quantization with Gauss mixtures," Proc. Int. Conf. Image Processing, vol. 3, pp. 14-17, 2001.

[31] K. M. Ozonat and R. M. Gray, "Guass mixture image classification for the linear image transforms," IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, vol. 5, pp. v/337 - v/340, 2005.
[CrossRef] [SCOPUS Times Cited 2]


[32] R. P., Lippman, "An introduction to computing with neural nets," ASSP Magazine, IEEE, vol. 4, no.2, pp. 4-22, 1987.
[CrossRef] [SCOPUS Times Cited 4426]


[33] S. Liu, C. Ume, and A. Achari, "Defects pattern recognition for flip-chip solder joint quality inspection with laser ultrasound and interferometer," IEEE transactions on electronics packing manufacturing, vol. 27, no. 1, pp. 59-66, 2004.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 18]


[34] S. Haykin, Neural Networks- A comprehensive foundation, New Jersey: Prentice Hall, 1999.

[35] S. G., Jahng, H. K., Hong, and J. S. Choi, "Dynamic simulation of the rosette scanning infrared seeker and an IRCCM using the moment technique," Optical Engineering, vol. 38, no. 5, pp. 921-928, 1999.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 23]


[36] S. G. Jahng, H. K. Hong, and J. S. Choi, "Simulation of rosette infrared seeker and counter-countermeasure using K-means algorithm," IEICE Tran. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E82-A, no. 6, pp. 987-993, 1999.

[37] S. G. Jahng, H. K. Hong, D. S. Seo, and J. S. Choi, "New infrared counter-countermeasure technique using an iterative self-organizing data algorithm for the rosette scanning infrared seeker," Optical Engineering, vol. 39, no. 9, pp. 2397-2404, 2000.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 14]


[38] S. G. Jahng, H. K. Hong, J. S. Choi, "Clustering method for rosette scan images," US patent, number 6,807,307 B2, Oct. 19, 2004.

[39] S. B. Shokouhi, A. K. Momtaz, H. Soltanizadeh, "The new weighting and clustering methods for the rosette pattern," WSEAS Transactions on information science & applications, vol. 2, no. 9, pp. 1250-1257, 2005.

[40] H. J. Zimmermann, Fuzzy Set Theory and Its Applications, Norwell, USA: Kluwer Academic publishers, 1996.

[41] J. C. Bezdek, Pattern recognition in handbook of fuzzy computation, IOP Publishing Ltd., Boston, MA, 1998.

References Weight

Web of Science® Citations for all references: 9,873 TCR
SCOPUS® Citations for all references: 21,379 TCR

Web of Science® Average Citations per reference: 241 ACR
SCOPUS® Average Citations per reference: 521 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 2018-09-20 15:49 in 136 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 ©2001-2018
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: