@inproceedings{64e440c8b09f4005bf594256c7e7c79a,
title = "Triangular road signs detection and recognition algorithm and its embedded system implementation",
abstract = "This paper proposes a low-complex triangular road signs detection and recognition algorithm that can be implemented on an embedded system for real-time applications and maintains decent detection and recognition accuracy under inclement weather conditions. The proposed method is composed of the shape detection to locate triangular road signs followed by the two feature extraction methods to focus on their different contents, and the descriptor construction method to eliminate the noise and make the system robust. This work is implemented on a desktop computer as well on an automotive-grade Freescale i.MX 6 embedded platform. Under a video resolution of 1280x720, the proposed system achieves 161 fps on the desktop computer and 17 fps on the Freescale i.MX6 embedded platform with an overall accuracy of 93.33%.",
keywords = "Advanced Driver Assistance System (ADAS), Feature Matching, Shape detection, Triangular road signs",
author = "Ting Chou and Chang, {Ssu Yuan} and Vinay, {M. S.} and Jiun-In Guo",
year = "2017",
month = jul,
language = "English",
series = "Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017",
publisher = "CSREA Press",
pages = "71--76",
editor = "Arabnia, {Hamid R.} and Leonidas Deligiannidis and Tinetti, {Fernando G.}",
booktitle = "Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017",
note = "2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 ; Conference date: 17-07-2017 Through 20-07-2017",
}