Desarrollo de una tiflo-aplicación Android para el reconocimiento de códigos QR
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2022
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Abstract
Este trabajo de fin de grado tiene como objetivo el desarrollo de una aplicación Android accesible para la lectura de códigos QR, que sea capaz de reconocer partes del QR o QRs no legibles e indicar al usuario como mover su dispositivo con el fin de detectar todo el QR y decodificarlo. Actualmente no se ha desarrollado ninguna aplicación con esta funcionalidad y, por lo tanto, el uso de códigos QR queda muy limitado en personas con discapacidad visual.
Con la pandemia global, causada por la COVID-19 vivida en los últimos años, ha sido necesaria la aplicación de medidas excepcionales en todo tipo de establecimientos y servicios centradas en evitar el contacto, siendo una de ellas la sustitución de numerosos textos físicos por equivalentes digitales. Estos textos son accedidos normalmente mediante códigos QR, que al de pender principalmente de las referencias visuales que identifique la persona, aquellas con discapacidad visual tendrán dificultades para su uso.
El desarrollo exponencial de la tecnología en los últimos años, adquiriendo cada vez más importancia en nuestras vidas, conlleva la necesidad de seguir unas pautas de accesibilidad para que pueda estar disponible a la mayor cantidad de gente posible.
El desarrollo de esta aplicación se hace a través de Android Studio, con el lenguaje de programación Java y con el uso de la inteligencia artificial, más específicamente visión por computador y aprendizaje automático.
This project’s objective is the development of an accessible Android application for QR code reading, which will be able to recognize parts of the QR code or a not readable QR code and guide the user on how to move their device in order to detect the entire QR code and decode it. Currently no application has been developed with this functionality and therefore the use of QR codes is very limited for the visually impaired. With the global pandemic caused by COVID-19 in recent years, it has been necessary to implement exceptional measures in all types of establishments and services focused on avoiding contact, one of them being the replacement of numerous physical texts by digital equivalents. These texts are normally accessed through QR codes, which, depending mainly on the visual references identified by the person, are difficult to use for the visually impaired. The exponential development of technology in recent years, acquiring more and more importance in our lives, brings with it the need to follow accessibility guidelines so that it can be available to as many people as possible. The development of this application is done through Android Studio, with the Java programming language and with the use of artificial intelligence, more specifically computer vision and machine learning.
This project’s objective is the development of an accessible Android application for QR code reading, which will be able to recognize parts of the QR code or a not readable QR code and guide the user on how to move their device in order to detect the entire QR code and decode it. Currently no application has been developed with this functionality and therefore the use of QR codes is very limited for the visually impaired. With the global pandemic caused by COVID-19 in recent years, it has been necessary to implement exceptional measures in all types of establishments and services focused on avoiding contact, one of them being the replacement of numerous physical texts by digital equivalents. These texts are normally accessed through QR codes, which, depending mainly on the visual references identified by the person, are difficult to use for the visually impaired. The exponential development of technology in recent years, acquiring more and more importance in our lives, brings with it the need to follow accessibility guidelines so that it can be available to as many people as possible. The development of this application is done through Android Studio, with the Java programming language and with the use of artificial intelligence, more specifically computer vision and machine learning.
Description
Trabajo de Fin de Grado en Ingeniería del Sotfware y en Ingeniería de Computadores, Facultad de Informática UCM, Departamento de Arquitectura de Computadores y Automática, Curso 2021/2022.