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JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: May 2024
Next issue: Aug 2024
Avg review time: 57 days
Avg accept to publ: 60 days
APC: 300 EUR


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


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Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
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LATEST NEWS

2024-Jun-20
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.

2023-Jun-05
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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  3/2018 - 10

All-Weather Road Image Enhancement using Multicolor Content-Aware Color Constancy

LEE, D. See more information about LEE, D. on SCOPUS See more information about LEE, D. on IEEExplore See more information about LEE, D. on Web of Science, KIM, T. See more information about  KIM, T. on SCOPUS See more information about  KIM, T. on SCOPUS See more information about KIM, T. on Web of Science, BYUN, H. See more information about  BYUN, H. on SCOPUS See more information about  BYUN, H. on SCOPUS See more information about BYUN, H. on Web of Science, CHOI, Y. See more information about CHOI, Y. on SCOPUS See more information about CHOI, Y. on SCOPUS See more information about CHOI, Y. on Web of Science
 
View the paper record and citations in View the paper record and citations in Google Scholar
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 (7,208 KB) | Citation | Downloads: 131 | Views: 2,383

Author keywords
image enhancement, color, image color analysis, object recognition, road vehicles

References keywords
image(6), retinex(5), processing(4), memory(4), automatic(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-08-31
Volume 18, Issue 3, Year 2018, On page(s): 67 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.03010
Web of Science Accession Number: 000442420900010
SCOPUS ID: 85052053137

Abstract
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This paper proposes a method that enhances the road images in real-time, which is an essential part of advanced driver assistance systems. The proposed method restores distorted colors in road images due to illumination by harnessing the relationship between known traffic signs and detected traffic signs via a traffic sign recognition system. The relationship is represented with Von Kries color constancy model which we aim to estimate and apply to the entire image. The proposed method uses a road traffic sign recognition system that is robust against illumination changes. It uses the difference between the detected color values of the traffic sign and an existing reference color values to obtain the coefficients of the Von Kries color constancy method, which is then applied to correct the road images in real time. Our method runs in real time and we tested the proposed method on various road driving images to show superior image enhancement performance regardless of the weather or time of day, compared to methods based on existing image processing techniques and color constancy method such as white balance.


References | Cited By

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Cited-By SCOPUS

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Cited-By CrossRef

[1] Quantitative Study on Road Traffic Environment Complexity under Car-Following Condition, Liu, Wenlong, Chen, Yixin, Li, Hongtao, Zhang, Hui, Sustainability, ISSN 2071-1050, Issue 10, Volume 14, 2022.
Digital Object Identifier: 10.3390/su14106251
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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