Browse > Article
http://dx.doi.org/10.5573/ieie.2017.54.8.123

Traffic Light Detection Using Color Based Saliency Map and Morphological Information  

Hyun, Seunghwa (e-intelligence Inc.)
Han, Dong Seog (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.54, no.8, 2017 , pp. 123-132 More about this Journal
Abstract
Traffic lights contain very important information for safety driving. So, the delivery of the information to drivers in real-time is a very critical issue for advanced driver assistance systems. However, traffic light detection is quite difficult because of the small sized traffic lights and the occlusion in real world. In this paper, a traffic light detection method using modified color based saliency map and morphological information is proposed. It shows 98.14% of precisions and 83.52% of recalls on computer simulations.
Keywords
첨단운전자지원시스템;신호등 검출;시각적 주의집중;돌출맵;형태학정보;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Ministry of Land, Infrastructure and Transport, "National Indicator System - Automobile Registration Status," http://www.index.go.kr/potal/main/EachDtlPageDetail.do?idx_cd=1257.
2 Korean National Police Agency, "Traffic accident statistics," 2016.
3 C. Yu, C. Huang, and Y. Lang, "Traffic light detection during day and night conditions by a camera," in Prof. of IEEE Int. Conf. on Signal Processing, pp. 821-824, Beijing, China, Oct. 2010.
4 M. Diaz-Cabrera, P. Cerri, and J. Sanchez-Medina, "Suspended traffic lights detection and distance estimation using color features," in Prof. of Int. IEEE Con. on Intelligent Transportation Systems, pp. 1315-1320, Anchorage, USA, Sep. 2012.
5 M. Omachi and S. Omachi, "Traffic light detection with color and edge information," in Proc. of IEEE Int. Con. on Computer Science and Information Technology, pp. 284-287, Beijin, China, Sep. 2009.
6 M. C. Jung, "Traffic Signal Detection and Recognition in an RGB Color Space," Journal of the Semiconductor & Display Technology, vol. 10, no. 3, pp. 53-59, Sep. 2011.
7 J. Levinson, J. Askeland, J. Dolson, and S. Thrun, "Traffic light mapping, localization, and state detection for autonomous vehicles," in Prof. of IEEE Int. Conf. on Robotics and Automation, pp. 5784-5791, Shanghai, China, May 2011.
8 Z. Cai, M. Gu, and Y, Li, "Real-time arrow traffic light recognition system for intelligent vehicle," in Proc. of World Congress in Computer Science, Computer Engineering, and Applied Computing, Jul. 2012.
9 H.-K. Kim, J. H. Park, and H.-Y. Jung, "Effective traffic lights recognition method for real time driving assistance system in the daytime," Int. Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, Vol. 5, no. 11, pp. 1424-1427, 2011.
10 A. Gomez, F. Alencar, P. Prado, F. Osorio, and D. Wolf, "Traffic lights detection and state estimation using hidden markov models," in Prof. of IEEE Intelligent Vehicles Symposium, Dearborn, USA, pp. 750-755, July 2014.
11 R. Charette and F. Nashashibi, "Real time visual traffic light detection based on spot light detection and adaptive traffic lights templates," in Prof. of IEEE intelligent Vehicles symposium, Xian, China, pp.358-363, July 2009.
12 J. Illingworth and J. Kittler, "The adaptive hough transform", IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol. PAMI-9, no. 5, pp.690-698, Sep. 1987.   DOI
13 C. Chiang, M. Ho and H. Liao, "Detecting and recognizing traffic lights by genetic approximate ellipse detection and spatial texture layouts," Int. Journal of Innovative Computing, Information and Control, Vol. 7, no. 12, pp. 6919-6934, Dec. 2011.
14 R. Charette, and F. Nashashibi, "Traffic light recognition using image processing compared to learning processes", in Prof. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 333-338, St. Louis, USA, Oct. 2009.
15 M. Philipsen, M. Jensen, M. Trivedi, and A. Mogelmose, "Traffic light detection at night: Comparison of a learning-based detector and three model-based detectors," in Proc. of Int. Symposium on Visual Computing, pp. 774-783, Las Vegas, USA, Dec. 2015.
16 J. Kim, "Traffic Lights Detection Based on Visual Attention and Spot-Lights Regions Detection," Journal of The Institute of Electronics and Information Engineers, vol. 51, no. 6, pp. 1260-1270, Jun. 2014.
17 G. Siogkas, E. Skodras, and E. Dermatas, "Traffic lights detection in adverse conditions using color, symmetry and spatiotemporal information.", in Proc. of the Int. Conf, on Computer Vision Theory and Applications, Rome, Italy, pp. 620-627, Feb. 2012.
18 L. Itti, C. Koch, E. Niebur, "A model of saliency-based visual attention for rapid scene analysis," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 20, no. 11, pp. 1254-1259, Nov. 1998.   DOI
19 Robotics Centre of Mines ParisTech., Traffic light recognition public benchmarks, http://www.lara.prd.fr/benchmarks/trafficlightsrecognition, 2015.