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Computer Optics, 2016, Volume 40, Issue 2, Pages 294–300 (Mi co144)  

IMAGE PROCESSING, PATTERN RECOGNITION

Russian traffic sign images dataset

V. I. Shakhuroa, A. S. Konushinba

a NRU Higher School of Economics, Moscow, Russia
b Lomonosov Moscow State University, Moscow, Russia

Abstract: A new public dataset of traffic sign images is presented. The dataset is intended for training and testing the algorithms of traffic sign recognition. We describe the dataset structure and guidelines for working with the dataset, comparing it with the previously published traffic sign datasets. The evaluation of modern detection and classification algorithms conducted using the proposed dataset has shown that existing methods of recognition of a wide class of traffic signs do not achieve the accuracy and completeness required for a number of applications.

Keywords: traffic sign dataset, traffic sign classification and detection, cascade of weak classifiers, convolutional neural network.

Funding Agency Grant Number
Skolkovo Institute of Science and Technology 081-R
This work was supported by the Skolkovo Institute of Science and Technology, the contract 081-R, Annex A1.


DOI: https://doi.org/10.18287/2412-6179-2016-40-2-294-300

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Full text: http://www.computeroptics.smr.ru/.../400221.html
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Received: 10.07.2015
Revised: 25.02.2015

Citation: V. I. Shakhuro, A. S. Konushin, “Russian traffic sign images dataset”, Computer Optics, 40:2 (2016), 294–300

Citation in format AMSBIB
\Bibitem{ShaKon16}
\by V.~I.~Shakhuro, A.~S.~Konushin
\paper Russian traffic sign images dataset
\jour Computer Optics
\yr 2016
\vol 40
\issue 2
\pages 294--300
\mathnet{http://mi.mathnet.ru/co144}
\crossref{https://doi.org/10.18287/2412-6179-2016-40-2-294-300}


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