@inproceedings{18f9549757a7427db23f4df1efc2f590,
title = "Evaluation of algorithms for traffic sign detection",
abstract = "Traffic sign detection is a crucial task in autonomous driving systems. Due to its importance, several techniques have been used to solve this problem. In this work, the three more common approaches are evaluated. The first approach uses a model of the traffic sign which is based in color and shape. The second one enhances the image model of the first approach using K-means for color clustering. The last approach uses convolutional neural networks designed for image detection. The LISA Traffic Sign Dataset was used which it was divided into three superclasses: prohibition, mandatory, and warning signs. The evaluation was done using objective metrics used in the state-of-the-art.",
keywords = "autonomous vehicles, computer vision, deep learning, detection, machine learning, trac sign",
author = "Miguel Lopez-Montiel and Yoshio Rubio and Mois{\'e}s S{\'a}nchez-Adame and Ulises Orozco-Rosas",
note = "Publisher Copyright: {\textcopyright} 2019 SPIE. Downloading of the abstract is permitted for personal use only.; Optics and Photonics for Information Processing XIII 2019 ; Conference date: 13-08-2019 Through 14-08-2019",
year = "2019",
doi = "10.1117/12.2529709",
language = "Ingl{\'e}s",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Iftekharuddin, {Khan M.} and Awwal, {Abdul A. S.} and Diaz-Ramirez, {Victor H.} and Andres Marquez",
booktitle = "Optics and Photonics for Information Processing XIII",
address = "Estados Unidos",
}