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JCR Impact Factor: 0.700
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SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Aug 2024
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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


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Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

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SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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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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Download PDF pdficon (879 KB) | Citation | Downloads: 1,369 | Views: 3,291

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

Abstract
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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.


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


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