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

초록

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 ill the image quality.

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