Using Patterns to Encode Color Information for Dichromats

Abstract

Color is one of the most common ways to convey information in visualization applications. Color vision deficiency (CVD) affects approximately 200 million individuals worldwide and considerably degrades their performance in understanding such contents by creating red-green or blue-yellow ambiguities. While several content-specific methods have been proposed to resolve these ambiguities, they cannot achieve this effectively in many situations for contents with a large variety of colors. More importantly, they cannot facilitate color identification. We propose a technique for using patterns to encode color information for individuals with CVD, in particular for dichromats. We present the first content-independent method to overlay patterns on colored visualization contents that not only minimizes ambiguities but also allows color identification. Further, since overlaying patterns does not compromise the underlying original colors, it does not hamper the perception of normal trichromats. We validated our method with two user studies: one including 11 subjects with CVD and 19 normal trichromats, and focused on images that use colors to represent multiple categories; and another one including 16 subjects with CVD and 22 normal trichromats, which considered a broader set of images. Our results show that overlaying patterns significantly improves the performance of dichromats in several color-based visualization tasks, making their performance almost similar to normal trichromats'. More interestingly, the patterns augment color information in a positive manner, allowing normal trichromats to perform with greater accuracy.

Processing images for red–green dichromats compensation via naturalness and information-preservation considered recoloring

“…Along with the widespread use of digital display devices, image processing techniques [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] for CVD assistance are attracting significant attention. Mainstream research has been conducted to enhance color contrast for users with CVD [9][10][11][12][13][14][15][16][17], and some researchers [22][23][24][25][26][27] have also taken the communication between normal color vision users and CVD users into consideration and proposed methods that enable the sharing of the same contents between normal and CVD users.…”

A Survey of Colormaps in Visualization

“…Patterns are also utilized to encode color information for people with CVD. The method of Sajadi et al [86] overlays a colormap with patterns, so that dichromats are able to better comprehend the values in the data, while original colors are preserved for normal trichromats. Two user studies are performed to validate the effectiveness of the method.…”

“…Care should be taken for people with color vision deficiencies, and several techniques [56], [65], [86] exist for enhancing colormaps for CVD.…”

ColourID

“…However, by painting all the pixels white, the underlying subtleties (lightness, intensity, and hue variations) of the colour are lost. Colour visualization techniques (similar to ColourMeters) have also been proposed [23,13,12], however each of these is designed specifically for people with inherited red-green CVD. Our techniques are designed to help with general ICV -even monochromatic vision -and do not require specific information about the user's type of ICV.…”