Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Nov 2016
Next issue: Feb 2017
Avg review time: 78 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

1,530,215 unique visits
477,954 downloads
Since November 1, 2009



Robots online now
Yahoo! Slurp
Baiduspider


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 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
 
 
 Volume 14 (2014)
 
     »   Issue 4 / 2014
 
     »   Issue 3 / 2014
 
     »   Issue 2 / 2014
 
     »   Issue 1 / 2014
 
 
 Volume 13 (2013)
 
     »   Issue 4 / 2013
 
     »   Issue 3 / 2013
 
     »   Issue 2 / 2013
 
     »   Issue 1 / 2013
 
 
  View all issues  


FEATURED ARTICLE

Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
Issue 4/2016

AbstractPlus






LATEST NEWS

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 "Big Data - " before the paper title in OpenConf.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

2016-Jun-14
Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

2015-Dec-04
Starting with Issue 2/2016, the article processing charge is 300 EUR for each article accepted for publication. The charge of 25 EUR per page for papers over 8 pages will not be changed. Details are available in the For authors section.

Read More »


    
 

  1/2014 - 11

Face Recognition using Similarity Pattern of Image Directional Edge Response

BASHAR, F. See more information about BASHAR, F. on SCOPUS See more information about BASHAR, F. on IEEExplore See more information about BASHAR, F. on Web of Science, KHAN, A. See more information about  KHAN, A. on SCOPUS See more information about  KHAN, A. on SCOPUS See more information about KHAN, A. on Web of Science, AHMED, F. See more information about  AHMED, F. on SCOPUS See more information about  AHMED, F. on SCOPUS See more information about AHMED, F. on Web of Science, KABIR, H. See more information about KABIR, H. on SCOPUS See more information about KABIR, H. on SCOPUS See more information about KABIR, H. on Web of Science
 
Click to see author's profile on 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 (907 KB) | Citation | Downloads: 533 | Views: 1,938

Author keywords
discrete cosine transform, face recognition, feature extraction, image texture analysis, pattern analysis

References keywords
recognition(31), face(25), pattern(17), local(11), analysis(10), image(8), binary(6), vision(5), machine(5), information(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 69 - 76
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01011
Web of Science Accession Number: 000332062300011
SCOPUS ID: 84894635007

Abstract
Quick view
Full text preview
An effective face descriptor is critical for a successful face recognition system and must overcome the challenges of changing environment. The face representation must have discriminatory information and be computationally feasible for any face recognition system. In this paper we propose a new face descriptor, Similarity Pattern of Image Directional Edge Response (SPIDER), for face recognition. An image is divided into smaller local regions and 8 directional edge responses are generated for each pixel position in the regions. The regional cumulative response of each direction is calculated and a histogram is generated consisting of 8 bins, one for each of the directions. The SPIDER code is generated by calculating the similarity between the histogram of the local region around each pixel against the histogram of neighbor regions. The feature vector is projected to a low-dimension vector space using a dimension reduction method to minimize the classification time. Experiments using the proposed method were carried out on the FERET database and results show improved recognition rates indicating the robustness to changing environment, and a low classification time compared to the existing methods.


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

[1] M. D. Kelly, "Visual Identification of people by computer", PhD Thesis, Stanford University, Stanford, CA, USA, 1971

[2] W. Zhao, R. Chellappa, P. J. Phillips and A. Rosenfeld, "Face Recognition: A Literature Survey", ACM Computing Surveys, vol. 35, no. 4, pp. 399-458, 2003.
[CrossRef] [Web of Science Times Cited 2319] [SCOPUS Times Cited 3479]


[3] D. S. Kim, I. J. Jeon, S. Y. Lee, P. K. Rhee and D. J. Chung, "Embedded face recognition based on fast genetic algorithm for intelligent digital photography," IEEE Transactions on Consumer Electronics, vol. 52, no. 3, pp.726-734, 2006.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 22]


[4] F. Zuo and P. H. N. de With, "Real-time embedded face recognition for smart home", IEEE Transaction on Consumer Electronics, vol. 51, no. 1, pp. 183-190, 2005.
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 59]


[5] T. Jabid, M. H. Kabir, and O. Chae, "Local Directional Pattern (LDP) for face recognition", International Journal of Innovative Computing, Information and Conrol, vol. 8, no. 4, pp. 2423-2437, 2012

[6] M. A. Turk and A. P. Pentland, "Face recognition using eigenfaces," International Conference on Computer Vision and Pattern Recognition, IEEE, 1991, pp. 586-591.

[7] J. R. Movellan, M.S. Bartlett and T. J. Senjnowski, "Face recognition by independent component analysis," IEEE Transactions on Neural Networks, vol. 13, pp.1450-1465, 2002.
[CrossRef] [Web of Science Times Cited 820] [SCOPUS Times Cited 1185]


[8] C. Zhou, X. Wei, Q. Zhang and B. Xiao, "Image reconstruction for face recognition based on fast ICA", International Journal of Innovative Computing, Information and Control, vol. 4, no. 7, pp. 1723-1732, 2008.

[9] K. Etemad and R. Chellappa, "Discriminant Analysis for recognition of human face images," Journal of the optical Society of America, vol.14, pp. 1724-1733, 1997.
[CrossRef] [Web of Science Times Cited 396] [SCOPUS Times Cited 533]


[10] A. F. Frangi, J. Yang, D. Zhang and J. Y. Yang, "Two-dimensional PCA: a new approach to appearance-based face representation and recognition," IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 26, pp. 131-137, 2004.
[CrossRef] [Web of Science Times Cited 1311] [SCOPUS Times Cited 2000]


[11] I. G. P. Wijaya, K. Uchimura and Z. Hu, "Face recognition based on dominant frequency features and multi-resolution metric," International Journal of Innovative Computing, Information and Control, vol.5, no.3, pp. 641-651, 2009.

[12] Y. Zana and R. M. C. Jr., "Face recognition based on polar frequency features," ACM Transactions on Applied Perception, vol.3, no.1, pp. 62-82, 2006.
[CrossRef]


[13] B. Moghaddam, T. Jebara and A. Pentland, "Bayesian Face Recognition," Pattern Recognition, vol. 33, no. 11, pp. 1771-1782, 2000.
[CrossRef] [Web of Science Times Cited 288] [SCOPUS Times Cited 391]


[14] J. Zhou, Q. Ji and G. Nagy, "A comparative study of local matching approach for face recognition," IEEE Transactions on Image Processing, vol. 16, no. 10, pp. 2617-2628, 2007.
[CrossRef] [Web of Science Times Cited 142] [SCOPUS Times Cited 205]


[15] L. Wiskott, J. M.Fellous, N. Kuiger and C. von der Malsburg, "Face recognition using elastic bunch graph matching," IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775-779, 1997.
[CrossRef] [Web of Science Times Cited 1438] [SCOPUS Times Cited 1949]


[16] P. S. Penev and J. Atick, "Local feature analysis: A general statistical theory for object representation", Network: Computation in Neural Systems, vol. 7, no. 3, pp. 477-500, 1996.
[CrossRef] [Web of Science Times Cited 305]


[17] J. Kim, J. Choi and J. Yi, "Face recognition based on locally salient ICA information", Biometric Authentication Workshop, pp. 1-9, 2004.
[CrossRef]


[18] V. V. Starovoitov, D. I. Samal and D. V. Biriliuk, "Three approaches for face recognition," International Conference on Pattern Recognition and Image Analysis, 2002, pp. 707-7011.

[19] R. Jafri and H. R. Arabnia, "A survey of face recognition techniques," Journal of Information Processing Systems, vol. 5, no. 2, pp. 41-68, 2009.
[CrossRef]


[20] T. Ojala, M. Pietikainen and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp.971-987, 2002.
[CrossRef] [Web of Science Times Cited 4110] [SCOPUS Times Cited 5887]


[21] T. Ahonen, A. Hadid and M. Pietikainen, "Face description with local binary patterns: Application to face recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, no.12, pp.2037-2041, 2006.
[CrossRef] [Web of Science Times Cited 1637] [SCOPUS Times Cited 2366]


[22] R. Mattivi and L. Shao, "Human action recognition using LBP-TOP as sparse spatio-temporal feature descriptor", Proc. of International Conference of Computer Analysis of Image and Pattern, pp. 740-747,

[23] S. Zhao, Y. Gao and B. Zhang, "Sobel-LBP," IEEE International Conference on Image Processing, 2008, pp. 2144-2147.

[24] F. Ahmed, E. Hossain, A. S. M. H. Bari, M. S. Hossen, "Compound Local Binary Pattern (CLBP) for rotation invariant texture classification", International Journal of Computer Applications, vol. 33, no. 6, pp. 5-10, 2011.

[25] X. Tran and B. Triggs, "Enhanced local texture feature sets for face recognition under difficult lighting conditions," Analysis and Modeling of Faces and Gestures, pp. 168-182, 2007.

[26] O. Deniz, G. Bueno, J. Salido and F. de la Torre, "Face recognition using Histogram of Oriented Gradients," Pattern Recognition Letters, vol. 32, no. 12, pp. 1598-1603, 2011.
[CrossRef] [Web of Science Times Cited 84] [SCOPUS Times Cited 138]


[27] T. Jabid, M. H. Kabir and O. Chae, "Local Directional Pattern (LDP) for face recognition," International Conference on Consumer Electronics, pp. 329-330, 2010.

[28] J. Huang, P. J. Phillips, H. Wechsler and P. Rauss, "The FERET database and evaluation procedure for face recognition algorithms," Image and Vision Computing, vol.16, no.5, pp. 295-306, 1998.
[CrossRef] [Web of Science Times Cited 960]


[29] Y. Mu, S. Yan, Y. Liu, S. T.Huang and B. Zhou, "Discriminative local binary patterns for human detection in personal album," IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1-8.

[30] Z. Sun, T. Tan and X. Qiu, "Graph matching iris image blocks with local binary pattern," Advances in Biometrics, 2005, pp. 366-372.

[31] X. Wang, H. Gong, H. Zhang, B .Li and Z. Zhuang, "Palm print Identification using Boosting Local Binary Pattern," International Conference on Pattern Recognition, 2006, pp. 503-506.

[32] R. C. Gonzalez, Digital Image Processing, Pearson, 2007

[33] Z. P. Rod, R. Adams, and H. Bolouri Dimensionality Reduction of Face Images Using Discrete Cosine Transforms for Recognition, IEEE Conference of Computer Vision and Pattern Recognition,

[34] J. Beveridge, D. Bolme, B. Draper, and M. Teixeira, "The CSU face identification evaluation system: Its purpose, features, and structure", Machine Vision and Applications, vol. 16, no. 2, pp. 128-138, 2005.
[CrossRef] [Web of Science Times Cited 51] [SCOPUS Times Cited 76]




References Weight

Web of Science® Citations for all references: 13,921 TCR
SCOPUS® Citations for all references: 18,290 TCR

Web of Science® Average Citations per reference: 398 ACR
SCOPUS® Average Citations per reference: 523 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 2017-02-17 15:25 in 115 seconds.




Note1: Web of Science® is a registered trademark of Thomson Reuters.
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 ©2001-2017
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: