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http://dx.doi.org/10.7471/ikeee.2018.22.1.46

Machine Learning based Traffic Light Detection and Recognition Algorithm using Shape Information  

Kim, Jung-Hwan (Dept. of Electronic Engineering, Hanyang University)
Kim, Sun-Kyu (Dept. of Electronic Engineering, Hanyang University)
Lee, Tae-Min (Dept. of Electronic Engineering, Hanyang University)
Lim, Yong-Jin (Dept. of Electronic Engineering, Hanyang University)
Lim, Joonhong (Dept. of Electronic Engineering, Hanyang University)
Publication Information
Journal of IKEEE / v.22, no.1, 2018 , pp. 46-52 More about this Journal
Abstract
The problem of traffic light detection and recognition has recently become one of the most important topics in various researches on autonomous driving. Most algorithms are based on colors to detect and recognize traffic light signals. These methods have disadvantage in that the recognition rate is lowered due to the change of the color of the traffic light, the influence of the angle, distance, and surrounding illumination environment of the image. In this paper, we propose machine learning based detection and recognition algorithm using shape information to solve these problems. Unlike the existing algorithms, the proposed algorithm detects and recognizes the traffic signals based on the morphological characteristics of the traffic lights, which is advantageous in that it is robust against the influence from the surrounding environments. Experimental results show that the recognition rate of the signal is higher than those of other color-based algorithms.
Keywords
Haar-like feature; SVM; Machine Learning; Traffic Light; Autonomous Vehicle; Black-box;
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  • Reference
1 Yang Ji, Ming Yang, Zhengchen Lu, Chunxiang Wang, "Integrating Visual Selective Attention Model with HOG Features for Traffic Light Detection and Recognition," IEEE conf. on Intelligent Vehicles Symposium, 2015, pp. 280-285.
2 Gwang-Gook Lee, Byung Kwan Park, "Traffic light recognition using deep neural networks," IEEE International conf. on Consumer Electronics, 2017, pp. 277-278.
3 Sang-Hyuk Lee, "Traffic light detection and recognition algorithm using shape characteristics of traffic light," Master thesis, Hanyang Univ., 2018.
4 Nevrus Kaja, Adnan Shaout, Omid Dehzangi, "Two Stage Intelligent Automotive System to Detect and Classify a Traffic Light," IEEE conf. on New Trends in Computing Sciences, 2017, pp. 30-35.
5 P. Viola, M. Jones, "Rapid object using a boosted cascade of simple features," IEEE conf. on Computer Vision and Pattern Recognition, 2001, pp. 511-518.
6 Saturnino Maldonado-Bascon, Sergio Lafuente Arroyo, Pedro Gil-Jimenez, "Road-Sign Detection and Recognition Based on Support Vector Machines," IEEE Tras. on Intelligent Transportation System, vol.8, pp. 264-278, 2007.DOI: 10.1109/TITS.2007.895311   DOI