DOI:
https://doi.org/10.14483/23448393.21408Published:
2024-07-17Issue:
Vol. 29 No. 2 (2024): May-AugustSection:
Electrical, Electronic and Telecommunications EngineeringMobile Application for Recognizing Colombian Currency with Audio Feedback for Visually Impaired People
Aplicación móvil para el reconocimiento de moneda colombiana con retroalimentación de audio para personas con discapacidad visual
Keywords:
Mobile application, Convolutional Neural Networks, Visually Impaired People, Colombian Currency Recognition (en).Keywords:
aplicación móvil, red neuronal convolucional, personas con discapacidad visual, reconocimiento de moneda Colombiana (es).Downloads
Abstract (en)
Context: According to the census conducted by the National Department of Statistics (DANE) in 2018, 7.1% of the Colombian population has a visual disability. These people face conditions with limited autonomy, such as the handling of money. In this context, there is a need to create tools to enable the inclusion of visually impaired people in the financial sector, allowing them to make payments and withdrawals in a safe and reliable manner.
Method: This work describes the development of a mobile application called CopReader. This application enables the recognition of coins and banknotes of Colombian currency without an Internet connection, by means of convolutional neural network models. CopReader was developed to be used by visually impaired people. It takes a video or photographs, analyzes the input data, estimates the currency value, and uses audio feedback to communicate the result.
Results: To validate the functionality of CopReader, integration tests were performed. In addition, precision and recall tests were conducted, considering the YoloV5 and MobileNet architectures, obtaining 95 and 93% for the former model and 99% for the latter. Then, field tests were performed with visually impaired people, obtaining accuracy values of 96%. 90% of the users were satisfied with the application’s functionality.
Conclusions: CopReader is a useful tool for recognizing Colombian currency, helping visually impaired people gain to autonomy in handling money.
Abstract (es)
Contexto: Según el censo realizado por el Departamento Nacional de Estadística (DANE) en 2018, el 7.1 % de la población colombiana tiene una discapacidad visual. Estas personas enfrentan condiciones con autonomía limitada, como lo es el manejo de dinero. En este contexto, es necesario crear herramientas que permitan la inclusión de las personas con discapacidad visual en el sector financiero, permitiéndoles realizar pagos y retiros de manera segura y confiable.
Método: Este trabajo describe el desarrollo de una aplicación móvil llamada CopReader. Esta aplicación permite el reconocimiento de monedas y billetes de la moneda colombiana sin conexión a Internet, mediante modelos de redes neuronales convolucionales. CopReader fue desarrollada para ser utilizada por personas con discapacidad visual: toma un video o fotografías, analiza los datos de entrada, estima el valor de la moneda y utiliza retroalimentación auditiva para comunicar el resultado.
Resultados: Para validar la funcionalidad de CopReader, se realizaron pruebas de integración. Además, se llevaron a cabo pruebas de precisión y recall, considerando las arquitecturas YoloV5 y MobileNet, donde se obtuvo 95 y 93 % para el primer modelo y 99 % para el segundo. Luego, se realizaron pruebas de campo con personas visualmente discapacitadas, obteniendo valores de exactitud del 96 %. El 90 % de los usuarios quedaron satisfechos con la funcionalidad de la aplicación.
Conclusiones: CopReader es una herramienta útil para el reconocimiento de la moneda colombiana, ayudando a las personas con discapacidad visual a ganar autonomía en el manejo del dinero.
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