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| Traffic Lights Recognition Based on Concatenated Filtering Method |
| JIN Tao-a, WANG Chun-Xiang-a, WANG Bing-b, YANG Ming-b |
| (a. Research Institute of Robotics; b. Department of Automation, Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiaotong University, Shanghai 200240, China) |
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Abstract A method for detection and recognition of traffic lights based on intelligent vehiclemounted camera was proposed. Applying the threshold acquired by image training, the candidate regions of traffic lights are extracted using the color segmentation method. Next the concatenated filters are proposed as a way to classify the extracted candidate regions. And then template matching using normalized cross correlation techniques is adopted to validate the classified traffic lights candidates. The experimental results show that the proposed algorithm works effectively and robustly for traffic lights recognition for intelligent vehicles in complex urban environments.
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Received: 10 November 2011
Published: 28 September 2012
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