BR-TRAFFIC SIGNS

BR-TRAFFIC SIGNS

Daniel Theisges dos Santos

Daniel Theisges dos Santos

Blumenau, Santa Catarina

Brazilian traffic signs detection

Artificial Intelligence, Robotics, Internet of Things

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Description

The security in road traffic has become a concern for the society, which motivating the development of Advanced Driver Assistance Systems (ADAS). An example of ADAS is the detection system for traffic signs, which aims to extract traffic information through computer vision te- chniques. In this work it was developed a system capable of detecting Brazilian traffic signs, using for this a new algorithm to filter objects. Firstly, the algorithm extracts objects based on color, applied through a threshold on the space Y’CbCr. After, the post-processing step, a neural network was used with the Fourier descriptors to isolate objects with typical shapes of the Brazilian traffic signs.

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Daniel T. added photos to project BR-TRAFFIC SIGNS

Medium 1e98d8f2 625b 473d abdc ce9b1a732d8e

BR-TRAFFIC SIGNS

The security in road traffic has become a concern for the society, which motivating the development of Advanced Driver Assistance Systems (ADAS). An example of ADAS is the detection system for traffic signs, which aims to extract traffic information through computer vision te- chniques. In this work it was developed a system capable of detecting Brazilian traffic signs, using for this a new algorithm to filter objects. Firstly, the algorithm extracts objects based on color, applied through a threshold on the space Y’CbCr. After, the post-processing step, a neural network was used with the Fourier descriptors to isolate objects with typical shapes of the Brazilian traffic signs.

Medium 1618498 813216372038108 986849409 n

Daniel T. created project BR-TRAFFIC SIGNS

Medium 1e98d8f2 625b 473d abdc ce9b1a732d8e

BR-TRAFFIC SIGNS

The security in road traffic has become a concern for the society, which motivating the development of Advanced Driver Assistance Systems (ADAS). An example of ADAS is the detection system for traffic signs, which aims to extract traffic information through computer vision te- chniques. In this work it was developed a system capable of detecting Brazilian traffic signs, using for this a new algorithm to filter objects. Firstly, the algorithm extracts objects based on color, applied through a threshold on the space Y’CbCr. After, the post-processing step, a neural network was used with the Fourier descriptors to isolate objects with typical shapes of the Brazilian traffic signs.

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