|3/2018 - 10|
All-Weather Road Image Enhancement using Multicolor Content-Aware Color ConstancyLEE, D. , KIM, T. , BYUN, H. , CHOI, Y.
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (7,208 KB) | Citation | Downloads: 381 | Views: 1,073|
image enhancement, color, image color analysis, object recognition, road vehicles
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
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|
| 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]
 M. Diaz-Cabrera, P. Cerri, and P. Medici, "Robust real-time trafï¬c light detection and distance estimation using a single camera," Expert Systems with Applications, pp. 3911-3923, 2014.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 63]
 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]
 E. H. Land and J. J. McCann, "Lightness and Retinex Theory," Josa, vol. 61, no. 1, pp.1-11, 1971.
[CrossRef] [SCOPUS Times Cited 2369]
 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 890] [SCOPUS Times Cited 1273]
 Z. U. Rahman, D. J. Jobson, and G. A. Woodell, "Multiscale Retinex for Color Image Enhancement," Image Processing, vol. 3, pp. 1003-1006, 1996.
 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 1136] [SCOPUS Times Cited 1571]
 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.
 M. D. Fairchild, "Color Appearance Models", John Wiley & Sons, 2013.
 G. Buchsbaum, "A Spatial Processor Model for Object Colour Perception," Journal of the Franklin institute, vol. 310, no. 1, pp 1-26, 1980.
[CrossRef] [Web of Science Times Cited 839] [SCOPUS Times Cited 1025]
 E. H. Land, "The Retinex Theory of Color Vision", pp. 2-17, Scientific America, 1977.
[CrossRef] [Web of Science Times Cited 864] [SCOPUS Times Cited 1164]
 J. Von Kries, "Die Gesichtsempfindungen", Handbuch der Physiologie der Menschen, 1905.
 T. Hansen, M. Olkkonen, S. Walter, and K. R. Gegenfurtner, " Memory Modulates Color Appearance," Nature Neuroscience, vol. 9, no. 11, pp1367-1368, 2006.
[CrossRef] [Web of Science Times Cited 246] [SCOPUS Times Cited 270]
 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]
 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 21]
 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]
 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
 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.
[CrossRef] [Web of Science Times Cited 37] [SCOPUS Times Cited 40]
 K. Lim, Y. Hong, Y. Choi, H. Byun, "Real-time Traffic Sign Recognition Based on a General Purpose GPU and Deep-learning," PLoS one, vol. 12, no. 3, 2017.
[CrossRef] [Web of Science Times Cited 12] [SCOPUS Times Cited 31]
 B. Froba and A. Ernst, "Face Detection with the Modified Census Transform," Proc. of the sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 91-96. 2003.
[CrossRef] [Web of Science Times Cited 210]
Web of Science® Citations for all references: 4,290 TCR
SCOPUS® Citations for all references: 7,883 TCR
Web of Science® Average Citations per reference: 204 ACR
SCOPUS® Average Citations per reference: 375 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 2021-04-17 02:02 in 107 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
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.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.