Paper
3 February 2014 Improving information perception from digital images for users with dichromatic color vision
Omid Shayeghpour, Daniel Nyström, Sasan Gooran
Author Affiliations +
Proceedings Volume 9015, Color Imaging XIX: Displaying, Processing, Hardcopy, and Applications; 901502 (2014) https://doi.org/10.1117/12.2039132
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
Color vision deficiency (CVD) is the inability, or limited ability, to recognize colors and discriminate between them. A person with this condition perceives a narrower range of colors compared to a person with normal color vision. In this study we concentrate on recoloring digital images in such a way that users with CVD, especially dichromats, perceive more details from the recolored images compared to the original ones. During this color transformation process, the goal is to keep the overall contrast of the image constant, while adjusting the colors that might cause confusion for the CVD user. In this method, RGB values at each pixel of the image are first converted into HSV values and, based on pre-defined rules, the problematic colors are adjusted into colors that are perceived better by the user. Comparing the simulation of the original image, as it would be perceived by a dichromat, with the same dichromatic simulation on the recolored image, clearly shows that our method can eliminate a lot of confusion for the user and convey more details. Moreover, an online questionnaire was created and a group of 39 CVD users confirmed that the transformed images allow them to perceive more information compared to the original images.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Omid Shayeghpour, Daniel Nyström, and Sasan Gooran "Improving information perception from digital images for users with dichromatic color vision", Proc. SPIE 9015, Color Imaging XIX: Displaying, Processing, Hardcopy, and Applications, 901502 (3 February 2014); https://doi.org/10.1117/12.2039132
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KEYWORDS
Chemical vapor deposition

Color vision

RGB color model

Image processing

Computer simulations

Cones

Eye

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