Accepted Papers
Electronic System for Signage Detection

Cristian Molina1 and Morelva Saeteros2, 1Salesian Polytechnic University, Quito, Ecuador, 2University of Deusto, Bizkaia, Spain


The present work focuses on the need of giving independence, safety and generating a better lifestyle for people with visual impairment. The work seeks to be an aid so that people with visual impairment can mobilize in a better manner, recognizing signage useful for their performance, such as pedestrian traffic lights, bus stops, pedestrian crossings, also, evaluate the model haar-cascade image detection methods to provide a better response to the user. The input to the system is a continuous video sequence, which analyses and gives the user and audible output of the different traffic signs. This process is based on an embedded system, which consists of a Raspberry Pi 3 B+ single board computer, a v2.1 Raspberry camera and headphones, the system was designed to be a low cost tool that can be adapted to the white cane for the support and autonomy of people with visual impairment.


Artificial Vision, Signage, OpenCV, Match Template, Haar-Classifier.

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