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Title: Real time detection and geolocalization of regulatory traffic signs
Authors: Jose de Jesus Salgado Patron, Oscar Roa Valbuena, Albeiro Cortes Cabezas
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2019
Volume: 14
Issue: 3
Language: English
In this paper, an application capable of detecting, recognizing and geolocating real-time traffic regulatory signs is developed. OpenCV library modules are used as the cascade classifier to detect objects and the kNN machine learning algorithm (k-Nearest Neighbors or nearest k-neighbors), for the recognition of the digits of the traffic signs. The location of the signs is done by GPS. In this way, an application performance of 92% is achieved.
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