Traffic-sign recognition

Traffic-sign recognition (TSR) is a technology by which a vehicle is able to recognize the traffic signs put on the road e.g. "speed limit" or "children" or "turn ahead".

The convention has broadly classified the road signs into seven categories designated with letters A to H. This standardization has been the main drive for helping the development of traffic-sign recognition systems that can be used globally.

Modern traffic-sign recognition systems are being developed using convolutional neural networks, mainly driven by the requirements of autonomous vehicles and self-driving cars.

A convolutional neural network can be trained to take in these predefined traffic signs and 'learn' using Deep Learning techniques.

The neural net in turn uses Image Processing and Computer Vision to train the network with its potential outcomes.

[9] Advanced computer vision and neural network techniques make this goal highly efficient and achievable in real time.

Other major algorithms for character recognition includes Haar-like features, Freeman Chain code, AdaBoost detection and deep learning neural networks methods.

Citroën, Ford, Honda, Infiniti, Jaguar, Jeep, Land Rover, Lexus, Mercedes, Nissan, Opel, Peugeot, Porsche, Renault, Toyota, Volkswagen, Tesla and Volvo.