@inproceedings{264be1e62e0c4f58a733f12e5d40b837,
title = "Background pixels mutation detection and Hu invariant moments based traffic signs detection on autonomous vehicles",
abstract = "In this paper, background pixels mutation detection and Hu invariant moments based traffic signs segmentation are combined in traffic signs detection. Considering the gray histogram information in S space, it has good segmentation effects as a global threshold selection method, which can greatly reduce the processing time of the subsequent work. Then using moment invariant theory to extract standard images and seven Hu invariant moments of traffic signs, we contrast the eigenvalues with the suspected areas to establish a rapid and reliable traffic signs detection method.",
keywords = "Background pixels mutation detection, Eigenvalues extraction, Hu invariant moments, Traffic signs",
author = "Fu, \{Meng Yin\} and Liu, \{Fang Yu\} and Yi Yang and Wang, \{Mei Ling\}",
note = "Publisher Copyright: {\textcopyright} 2014 TCCT, CAA.; Proceedings of the 33rd Chinese Control Conference, CCC 2014 ; Conference date: 28-07-2014 Through 30-07-2014",
year = "2014",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2014.6896705",
language = "English",
series = "Proceedings of the 33rd Chinese Control Conference, CCC 2014",
publisher = "IEEE Computer Society",
pages = "670--674",
editor = "Shengyuan Xu and Qianchuan Zhao",
booktitle = "Proceedings of the 33rd Chinese Control Conference, CCC 2014",
address = "United States",
}