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Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System
- Issue Date
- Dec-2008
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- car navigation system; traffic light; crossroad detection; principal component analysis
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E91D, no.12, pp.2884 - 2887
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E91D
- Number
- 12
- Start Page
- 2884
- End Page
- 2887
- ISSN
- 1745-1361
- 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 ill the image quality.
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Related Researcher
- Joo, Sung Kwan
- College of Engineering (School of Electrical Engineering)