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

نویسندگان

  • Sung-Kwan Joo
  • Yongkwon Kim
  • Seong Ik Cho
  • Kyungho Choi
  • Kisung Lee
چکیده

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. key words: car navigation system, traffic light, crossroad detection, principal component analysis

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عنوان ژورنال:
  • IEICE Transactions

دوره 91-D  شماره 

صفحات  -

تاریخ انتشار 2008