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A Video based Traffic Light Recognition System for Intelligent Vehicles  

Chu, Yeon Ho (Korea University of Technology and Education, School of Computer Science and Engineering)
Lee, Bok Joo (Korea University of Technology and Education, School of Computer Science and Engineering)
Choi, Young Kyu (Korea University of Technology and Education, School of Computer Science and Engineering)
Publication Information
Journal of the Semiconductor & Display Technology / v.14, no.2, 2015 , pp. 29-34 More about this Journal
Abstract
Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, we propose a robust and efficient algorithm for recognizing traffic lights from video sequences captured by a low cost off-the-shelf camera. Instead of using color information for recognizing traffic lights, a shape based approach is adopted. In learning and detection phase, Histogram of Oriented Gradients (HOG) feature is used and a cascade classifier based on Adaboost algorithm is adopted as the main classifier for locating traffic lights. To decide the color of the traffic light, a technique based on histogram analysis in HSV color space is utilized. Experimental results on several video sequences from typical urban environment prove the effectiveness of the proposed algorithm.
Keywords
traffic light recognition; intelligent vehicle; shape analysis; HOG (Histogram of Oriented Gradient); AdaBoost algorithm; cascade classifier;
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