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JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Aug 2020
Next issue: Nov 2020
Avg review time: 58 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


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Improved Wind Speed Prediction Using Empirical Mode Decomposition, ZHANG, Y., ZHANG, C., SUN, J., GUO, J.
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2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
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2019-Jun-20
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2018-May-31
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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
 
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: 349 | Views: 923

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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Full text preview
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  «-- Click to see who has cited this paper

[1] Y. Zhang, J. Xue, G. Zhang, Y. Zhang, and N. Zheng, "A multi-feature fusion based traffic light recognition algorithm for intelligent vehicles," 33rd Chinese Control Conference (CCC), pp. 4924-4929, 2014.
[CrossRef] [SCOPUS Times Cited 22]


[2] M. Diaz-Cabrera, P. Cerri, and P. Medici, "Robust real-time traffic light detection and distance estimation using a single camera," Expert Systems with Applications, pp. 3911-3923, 2014.
[CrossRef] [Web of Science Times Cited 40] [SCOPUS Times Cited 56]


[3] M. A. A. Sheikh, A. Kole, T. Maity, "Traffic sign detection and classification using colour feature and neural network," In Intelligent Control Power and Instrumentation (ICICPI), pp. 307-311, 2016.
[CrossRef] [SCOPUS Times Cited 12]


[4] E. H. Land and J. J. McCann, "Lightness and Retinex Theory," Josa, vol. 61, no. 1, pp.1-11, 1971.
[CrossRef] [SCOPUS Times Cited 2291]


[5] D. J. Jobson, Z. Rahman, and G. A. Woodell, "Properties and Performance of a Center/Surround Retinex," IEEE Transactions on Image Processing, vol. 6, no. 3, pp 451-462, 1997.
[CrossRef] [Web of Science Times Cited 831] [SCOPUS Times Cited 1195]


[6] Z. U. Rahman, D. J. Jobson, and G. A. Woodell, "Multiscale Retinex for Color Image Enhancement," Image Processing, vol. 3, pp. 1003-1006, 1996.
[CrossRef]


[7] D. J. Jobson, Z. U. Rahman, and G. A. Woodell, "A Multiscale Retinex for Bridging the gap between Color Images and the Human Observation of Scenes," IEEE Transactions on Image processing, vol. 6, No. 7, pp. 965-976, 1997.
[CrossRef] [Web of Science Times Cited 1064] [SCOPUS Times Cited 1475]


[8] C. Gatta, A. Rizzi, D. Marini, "Ace: An Automatic Color Equalization Algorithm", In Conference on Colour in Graphics, Imaging, and Vision, pp. 316-320, 2002.

[9] M. D. Fairchild, "Color Appearance Models", John Wiley & Sons, 2013.
[CrossRef]


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[CrossRef] [Web of Science Times Cited 803] [SCOPUS Times Cited 990]


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[CrossRef] [Web of Science Times Cited 807] [SCOPUS Times Cited 1083]


[12] J. Von Kries, "Die Gesichtsempfindungen", Handbuch der Physiologie der Menschen, 1905.

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[CrossRef] [Web of Science Times Cited 237] [SCOPUS Times Cited 263]


[14] S. Xue, M. Tan, A. Mcnamara, J. Dorsey, and H. Rushmeier, "Exploring the Use of Memory Colors for Image Enhancement," IS&T/SPIE Electronic Imaging. International Society for Optics and Photonics, vol. 9014, 2014.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]


[15] E. Rahtu, J. Nikkanen, J. Kannala, L. LepistLe, and J. Heikkilnd, "Applying Visual Object Categorization and Memory Colors for Automatic Color Constancy," In International Conference on Image Analysis and Processing, vol. 5716, pp. 873-882, 2009.
[CrossRef] [SCOPUS Times Cited 18]


[16] A. Moreno, B. Fernando, B. Kani, S. Saha, and S. Karaoglu, " Color Correction: a Novel Weighted Von Kries Model Based on Memory Colors," In International Workshop on Computational Color Imaging, vol. 6626, pp. 165-175, 2011.
[CrossRef] [SCOPUS Times Cited 11]


[17] H. Nachlieli, R. Bergman, D. Greig, C. Staelin, B. Oicherman, G. Ruckenstein, and D. Shaked, "Skin-sensitive Automatic Color Correction," SIGGRAPH, New Orleans, 2009. [Online] Available: Temporary on-line reference link removed - see the PDF document

[18] S. Bianco and Sc. Raimondo . "Adaptive Color Constancy Using Faces," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 8, pp 1505-1518, 2014.
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[CrossRef] [Web of Science Times Cited 208]




References Weight

Web of Science® Citations for all references: 4,045 TCR
SCOPUS® Citations for all references: 7,494 TCR

Web of Science® Average Citations per reference: 193 ACR
SCOPUS® Average Citations per reference: 357 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 2020-11-24 22:59 in 115 seconds.




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


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