An Adaptive Fuzzy-Based System to Simulate, Quantify and Compensate Color Blindness
This work addresses color vision disturbances affecting about 8% of males, offering an adaptive correction tool, but it is incremental as it builds on existing linear transform methods with fuzzy modifications.
The paper tackled the problem of color blindness by developing a fuzzy logic-based software tool to simulate, quantify, and correct it, with results showing that Method B with histogram equalization achieved the best performance for 47% of volunteers in a survey of 40 people.
About 8% of the male population of the world are affected by a determined type of color vision disturbance, which varies from the partial to complete reduction of the ability to distinguish certain colors. A considerable amount of color blind people are able to live all life long without knowing they have color vision disabilities and abnormalities. Nowadays the evolution of information technology and computer science, specifically image processing techniques and computer graphics, can be fundamental to aid at the development of adaptive color blindness correction tools. This paper presents a software tool based on Fuzzy Logic to evaluate the type and the degree of color blindness a person suffer from. In order to model several degrees of color blindness, herein this work we modified the classical linear transform-based simulation method by the use of fuzzy parameters. We also proposed four new methods to correct color blindness based on a fuzzy approach: Methods A and B, with and without histogram equalization. All the methods are based on combinations of linear transforms and histogram operations. In order to evaluate the results we implemented a web-based survey to get the best results according to optimize to distinguish different elements in an image. Results obtained from 40 volunteers proved that the Method B with histogram equalization got the best results for about 47% of volunteers.