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JCR Impact Factor: 0.595
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Issues per year: 4
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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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Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
Issue 4/2016

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LATEST NEWS

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-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

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.

2017-Jan-30
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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.

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  4/2016 - 6

A New Autofocusing Method Based on Brightness and Contrast for Color Cameras

SELEK, M. See more information about SELEK, M. on SCOPUS See more information about SELEK, M. on IEEExplore See more information about SELEK, M. 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 (1,516 KB) | Citation | Downloads: 179 | Views: 411

Author keywords
CCD image sensors, digital images, focusing, image color analysis, image processing

References keywords
focus(25), image(14), measure(10), auto(8), pattern(7), autofocus(7), algorithm(7), zhang(6), systems(6), recognition(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 39 - 44
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04006
Web of Science Accession Number: 000390675900006
SCOPUS ID: 85007578320

Abstract
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The autofocusing is one of the most important features of imaging devices. This feature directly affects the quality of the image taken by the imaging device. Currently, many studies are being performed to improve the feature of autofocusing. In this study, we propose a method for passive autofocusing of the color cameras. This method suggested is called as the Passive Autofocusing Based-Brightness and Contrast (PA Based-BC). According to this method, autofocusing is performed by identifying the brightness of the R, G and B color components of the RGB image and by focusing of the camera on the brightest color component. To this end, in this study, many experiments have been conducted. The analyses of these experiments show that the contrast-based focusing made depending on the brightness gives much better results. The use of this method upgrades the focusing accuracy of the color camera up to 95%.


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

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References Weight

Web of Science® Citations for all references: 1,947 TCR
SCOPUS® Citations for all references: 2,956 TCR

Web of Science® Average Citations per reference: 46 ACR
SCOPUS® Average Citations per reference: 70 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 2017-06-26 20:45 in 284 seconds.




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