Affiliation:
1. Universidad Politécnica de Aguascalientes, Mexico
2. Universidad Autónoma de Aguascalientes, Mexico
3. Universidad Juárez Autónoma de Tabasco, Mexico
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.
Reference26 articles.
1. Colour blindness in everyday life and car driving
2. Comprehending Color Images for Color Barrier-Free via Factor Analysis Technique.;K.-s.Chieko Kato;International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing,2013
3. Colblindor. (2016). Obtenido de http://www.color-blindness.com/wp-content/documents/Color-Blind-Essentials.pdf
4. Molecular genetics of colour vision deficiencies