Sistema de Reconocimiento de Señalamientos en Entornos Abiertos para la Orientación de Personas con Discapacidad Visual

Yesenia González; Alejandro Millán; Yuli Sánchez; Claudia Ortiz; Miguel Alemán; Carlos Hernández

doi:10.36561/NG.19.4

Authors

Yesenia González UPIITA - Instituto Politécnico Nacional, México https://orcid.org/0000-0003-2370-4660
Alejandro Millán UPIITA - Instituto Politécnico Nacional, México https://orcid.org/0000-0002-0789-1112
Yuli Sánchez UPIITA - Instituto Politécnico Nacional, México https://orcid.org/0000-0002-9744-4614
Claudia Ortiz UPIITA - Instituto Politécnico Nacional, México https://orcid.org/0000-0002-5314-9488
Miguel Alemán CNMN - Instituto Politécnico Nacional, México https://orcid.org/0000-0001-6234-8406
Carlos Hernández https://orcid.org/0000-0002-2417-9020

DOI:

https://doi.org/10.36561/NG.19.4

Keywords:

Signs, SLIC algorithm, Convolutional neural networks, Simple-board computer, GPS, People with visual disabilities

Abstract

This work presents the development of a prototype that allows identifying specific signs through artificial vision techniques. It uses an image segmentation stage based on the SLIC superpixel algorithm, followed by a sign recognition and classification stage based on convolutional neural networks and has been implemented in a simple-board computer (SBC). The prototype informs the user of the identification of these signs through an audio message sent to headphones, it has a GPS module that obtains the location where the sign was recognized and is stored to offer the user notifications about nearby signs. The tests were performed with 1: 2 scale signs in open spaces, with natural light. The prototype is intended as a support for visually impaired people to move in open urban environments. Processing times and prototype performance are reported. Although the implementation in the selected simple-board computer makes its use unfeasible due to operating times, the functionality of the system is demonstrated.

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