Abstract
This letter presents a novel approach for traffic light detection in a video frame captured by an in-vehicle camera. The algorithm consists of rotated principal component analysis (RPCA), modified amplitude thresholding with respect to the histograms of the PC planes and final filtering with a neural network. The proposed algorithm achieves an average detection rate of 96% and is very robust to variations in the image quality.
Original language | English |
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Pages (from-to) | 2884-2887 |
Number of pages | 4 |
Journal | IEICE Transactions on Information and Systems |
Volume | E91-D |
Issue number | 12 |
DOIs | |
Publication status | Published - 2008 |
Keywords
- Car navigation system
- Crossroad detection
- Principal component analysis
- Traffic light
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence