Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System

概要

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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.
（社）電子情報通信学会の論文
2008-12-01