Creating an Automatic Road Sign Inventory System using a Fully Deep Learning-based Approach

: Some road sections are a veritable forest of road signs: just think how many indications you can come across on an urban or extra-urban route, near a construction site or a road diversion. The automatic recognition of vertical traffic signs is an extremely useful task in the automotive industry for many practical applications, such as supporting the driver while driving with an in-car advisory system or the creation of a register of signals for a particular road section to speed up maintenance and replacement of installations. Recent developments in deep learning have brought huge progress in the image processing area, which triggered successful applications like traffic sign recognition (TSR). The TSR is a specific image processing task in which real traffic scenes (images or frames from videos taken from vehicle cameras in uncontrolled lighting and occlusion conditions) are processed in order to detect and recognize traffic signs within it. Traffic Sign Recognition is a very recent technology facilitated by the Vienna Convention on Road Signs and Signals of 1968: during that international meeting, it was decided to standardize traffic signs so that they could be recognised more easily abroad. Finally, this work summarizes our proposal of a practical pipeline for the development of an automatic traffic sign recognition software.