%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/08.16.09.03
%2 sid.inpe.br/sibgrapi/2016/08.16.09.03.31
%T Vehicle Speed Estimation by License Plate Detection and Tracking
%D 2016
%A Luvizon, Diogo Carbonera,
%A Nassu, Bogdan Tomoyuki,
%A Minetto, Rodrigo,
%@affiliation Federal University of Technology - Paraná (UTFPR)
%@affiliation Federal University of Technology - Paraná (UTFPR)
%@affiliation Federal University of Technology - Paraná (UTFPR)
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I Sociedade Brasileira de Computação
%J Porto Alegre
%S Proceedings
%K vehicle speed, speed measurement, license plate detection, feature traking.
%X We propose a non-intrusive methodology, based on digital videos, for measuring vehicle speeds by detecting and tracking license plates a technology that does not exist in Brazil. We proposed novel algorithms for detecting regions containing moving vehicles, as well as their license plates. Each vehicles speed is then estimated by tracking the license plates and applying geometric transformations. Experiments were performed on videos containing 8,000 vehicles, associated to speeds measured by a precise inductive loop detector. The average speed measurement error was -0.5 km/h, staying inside the +2/-3 km/h margin determined by international regulatory agencies, in more than 96% of the cases.
%@language en
%3 sibgrapi_2016_luvizon.pdf