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Real-Time Recoloring Ishihara Plates Using Artificial Neural Networks for Helping Colorblind People
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Author(s): Martín Montes Rivera (Universidad Politécnica de Aguascalientes, Mexico), Alejandro Padilla (Universidad Autónoma de Aguascalientes, Mexico), Juana Canul-Reich (Universidad Juárez Autónoma de Tabasco, Mexico)and Julio Ponce (Universidad Autónoma de Aguascalientes, Mexico)
Copyright: 2020
Pages: 19
Source title:
User-Centered Software Development for the Blind and Visually Impaired: Emerging Research and Opportunities
Source Author(s)/Editor(s): Teresita de Jesús Álvarez Robles (Universidad Veracruzana, Mexico), Francisco Javier Álvarez Rodríguez (Universidad Autónoma de Aguascalientes, Mexico)and Edgard Benítez-Guerrero (Universidad Veracruzana, Mexico)
DOI: 10.4018/978-1-5225-8539-8.ch009
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Abstract
Vision sense is achieved using cells called rods (luminosity) and cones (color). Color perception is required when interacting with educational materials, industrial environments, traffic signals, among others, but colorblind people have difficulties perceiving colors. There are different tests for colorblindness like Ishihara plates test, which have numbers with colors that are confused with colorblindness. Advances in computer sciences produced digital assistants for colorblindness, but there are possibilities to improve them using artificial intelligence because its techniques have exhibited great results when classifying parameters. This chapter proposes the use of artificial neural networks, an artificial intelligence technique, for learning the colors that colorblind people cannot distinguish well by using as input data the Ishihara plates and recoloring the image by increasing its brightness. Results are tested with a real colorblind people who successfully pass the Ishihara test.
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