The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Surat ini membentangkan pendekatan baru untuk pengesanan lampu isyarat dalam bingkai video yang ditangkap oleh kamera dalam kenderaan. Algoritma ini terdiri daripada analisis komponen utama yang diputar (RPCA), ambang amplitud yang diubah suai berkenaan dengan histogram satah PC dan penapisan akhir dengan rangkaian saraf. Algoritma yang dicadangkan mencapai kadar pengesanan purata 96% dan sangat teguh kepada variasi dalam kualiti imej.
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Salinan
Sung-Kwan JOO, Yongkwon KIM, Seong Ik CHO, Kyoungho CHOI, Kisung LEE, "Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 12, pp. 2884-2887, December 2008, doi: 10.1093/ietisy/e91-d.12.2884.
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.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.12.2884/_p
Salinan
@ARTICLE{e91-d_12_2884,
author={Sung-Kwan JOO, Yongkwon KIM, Seong Ik CHO, Kyoungho CHOI, Kisung LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System},
year={2008},
volume={E91-D},
number={12},
pages={2884-2887},
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.},
keywords={},
doi={10.1093/ietisy/e91-d.12.2884},
ISSN={1745-1361},
month={December},}
Salinan
TY - JOUR
TI - Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System
T2 - IEICE TRANSACTIONS on Information
SP - 2884
EP - 2887
AU - Sung-Kwan JOO
AU - Yongkwon KIM
AU - Seong Ik CHO
AU - Kyoungho CHOI
AU - Kisung LEE
PY - 2008
DO - 10.1093/ietisy/e91-d.12.2884
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2008
AB - 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.
ER -