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JCR Impact Factor: 0.459
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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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ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
Issue 3/2016



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.

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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.

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  4/2014 - 14

Fingerprint Ridge Frequency Estimation in the Fourier Domain

PATRICIU, V.-V. See more information about PATRICIU, V.-V. on SCOPUS See more information about PATRICIU, V.-V. on IEEExplore See more information about PATRICIU, V.-V. on Web of Science, SPINU, S. See more information about SPINU, S. on SCOPUS See more information about SPINU, S. on SCOPUS See more information about SPINU, S. on Web of Science
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Author keywords
biometrics, feature extraction, fingerprint recognition, identification of persons, spectral analysis

References keywords
fingerprint(20), recognition(15), pattern(12), image(12), enhancement(9), jain(7), ridge(6), filtering(6), gabor(5), filter(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 95 - 98
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04014
Web of Science Accession Number: 000348772500014
SCOPUS ID: 84921634128

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Ridge frequency is an important parameter in fingerprint image processing and feature extraction. However, ridge frequency estimation is a difficult task in noisy fingerprint images. A simple and accurate method for the computation of fingerprint ridge frequency using the Fourier spectrum is proposed. The results of the experiments conducted on a collection of fingerprints as well as a quantitative method for performance evaluation based on a Gabor filter-bank are presented. The proposed method is robust with respect to noise and reliable frequency images are obtained.

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

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[2] L. O'Gorman, "Fingerprint verification," in A.K. Jain, R. Bolle, and S. Pankanti (Eds.), Biometrics: Personal Identification in Networked Society, pp. 43-64, Boston, MA: Kluwer Academic Publishers, 1999.

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[9] J. Yang, L. Liu, T. Jiang, Y. Fan, "A modified Gabor filter design method for fingerprint image enhancement," Pattern Recognition Letters, vol. 24, no. 12, pp. 1805-1817, Aug. 2003.
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[11] E. Zhu, J. Yin, G. Zhang, "Fingerprint enhancement using circular Gabor filter," in A. Campilho and M. Kamel (Eds.), Image Analysis and Recognition: International Conference, ICIAR 2004, Porto, Portugal, September 29 - October 1, 2004, Proceedings, Part II, pp. 750-758, Berlin: Springer-Verlag, 2004.

[12] C. Wu, V. Govindaraju, "Singularity preserving fingerprint image adaptive filtering," in Proc. of the IEEE International Conference on Image Processing, Atlanta, GA, Oct. 8-11, 2006, pp. 313-316.
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[13] S. Chikkerur, A. N. Cartwright, V. Govindaraju, "Fingerprint enhancement using STFT analysis," Pattern Recognition, vol. 40, no. 1, pp. 198-211, Jan. 2007.
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[17] A. Farina, Z. M. Kovacs-Vajna, A. Leone, "Fingerprint minutiae extraction from skeletonized binary images," Pattern Recognition, vol. 32, no. 5, pp. 877-889, May 1999.
[CrossRef] [Web of Science Times Cited 58]

[18] D.-H. Kim, "Minutiae quality scoring and filtering using a neighboring ridge structural analysis on a thinned fingerprint image," in T. Kanade, A.K. Jain, and N.K. Ratha (Eds.), Audio- and Video-Based Biometric Person Authentication: 5th International Conference, AVBPA 2005, Hilton Rye Town, NY, USA, July 20-22, 2005, Proceedings, pp. 674-682, Berlin: Springer-Verlag, 2005.

[19] D. Maio, D. Maltoni, "Ridge-line density estimation in digital images," in Proc. of the 14th International Conference on Pattern Recognition, Brisbane, Australia, Aug 16-20, 1998, vol. 1, pp. 534-538.

[20] Z. M. Kovacs-Vajna, R. Rovatti, M. Frazzoni, "Fingerprint ridge distance computation methodologies," Pattern Recognition, vol. 33, no. 1, pp. 69-80, Jan. 2000.
[CrossRef] [Web of Science Times Cited 30]

[21] Y. Yin, J. Tian, X. Yang, "Ridge distance estimation in fingerprint images: algorithm and performance evaluation," EURASIP Journal on Applied Signal Processing, vol. 2004, no. 4, pp. 495-502, 2004.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 24]

[22] D. Maio, D. Maltoni, R. Cappelli, J. L. Wayman, A. K. Jain, "FVC2002: Second Fingerprint Verification Competition," in Proc. of the 16th International Conference on Pattern Recognition, Quebec, Canada, Aug. 11-15, 2002, vol. 3, pp. 811-814.

[23] J. G. Daugman, "Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters," Journal of the Optical Society of America A, vol. 2, no. 7, pp. 1160-1169, Jul. 1985.
[CrossRef] [Web of Science Times Cited 1503] [SCOPUS Times Cited 1854]

[24] A. K. Jain, F. Farrokhnia, "Unsupervised texture segmentation using Gabor filters," Pattern Recognition, vol. 24, no. 12, pp. 1167-1186, Dec. 1991.
[CrossRef] [Web of Science Times Cited 1015] [SCOPUS Times Cited 1260]

References Weight

Web of Science® Citations for all references: 4,042 TCR
SCOPUS® Citations for all references: 5,205 TCR

Web of Science® Average Citations per reference: 162 ACR
SCOPUS® Average Citations per reference: 208 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 background updated on 2017-02-17 23:32 in 108 seconds.

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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.

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

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