Nick LaVassar

Introduction

Color vision deficiency (often called "colorblindness") affects hundreds of millions of people around the world. The deficiency is sex linked: approximately 8% of men have a CVD versus only 0.5% of females. This project aims to simulate the most common types of CVDs for people with normal color perception. The simulation will be run in realtime on an iOS device.

Background

Color vision deficiencies are characterized by reduced sensitivity to color as a result of anomalies in the eye's color receptors (called cones). In extremely rare cases, the cones in the eye are either completely absent or totally dysfunctional which results in monochromacy (no color perception). When only one cone is missing a person is said to be dichromatic. The most common CVDs are caused by a shift in the sensitivity of one of the types of cone in the eye and is known as anomalous trichromacy.

CVDs are classified according to which cone type is affected:

• Protanomaly - L cone sensitivity is defective.
• Deuteranomaly - M cone sensitivity is defective.
• Tritanomaly - S cone sensitivity is defective.

Likewise, someone with dichromatic vision is completely missing either their L, M or S cones, and is called either a protanope, deuteranope, or tritanope, respectively.

Protanopia and deuteranopia reduce senstivity to red-green colors, while tritanopia reduces sensitivity to blue-yellow colors.

Methods

Overview

Simulation steps are as follows:

• Precompute matrices mapping from RGB to opponent color space for range of CVD types and severities.
• Linearize RGB values from input camera in preparation for calculations in LMS space.
• Multiply linear RGB value with opponent CVD matrix to get opponent color space representation of what a color deficient person receives as input to their neural pathways.
• Multiply deficient opponent colorspace representation by the inverse opponent matrix conversion of a normal color perceiver to get trichromat representation.
• Reapply gamma and display on screen.

Computations

Anomalous trichromacy can be simulated by shifting the sensitivity of the L, M, and S cones in the following ways^1:

• Protanomaly - Shift L cone toward M cone $L(\lambda )_{a}=L(\lambda +\Delta \lambda _{L})$
• Deuteranomaly - Shift M cone toward L cone $M(\lambda )_{a}=M(\lambda +\Delta \lambda _{M})$
• Trianomaly - Shift S cone: $S(\lambda )_{a}=S(\lambda +\Delta \lambda _{S})$

We can convert from LMS to opponent color space using the following transform:

${\begin{bmatrix}WS(\lambda )\\YB(\lambda )\\RG(\lambda )\end{bmatrix}}={\begin{bmatrix}0.600&0.400&0.0000.240&0.105&0.7001.200&1.600&0.400\end{bmatrix}}*{\begin{bmatrix}L(\lambda )\\M(\lambda )\\S(\lambda )\end{bmatrix}}$

Failed to parse (syntax error): {\displaystyle \begin{bmatrix} 1 & 0 & 2 \\ -1 & 3 & 1 \\ \end{bmatrix} \times \begin{bmatrix} 3 & 1 \\ 2 & 1 \\ 1 & 0 \\ \end{bmatrix} &= \begin{bmatrix} 5 & 1 \\ 4 & 2 \\ \end{bmatrix}. }

Implementation

The method described was implemented on an iPhone to augment the device's camera feed in real time. As a result, the simulation is highly portable and easily distributed.

Conclusions

Applying the previously described color vision deficiency simulation to a realtime device yielded a very interesting and hopefully useful tool. The simulation can be used to entertain and educate people about CVDs. It can also assist trichromatic designers create content for dichromates.

References

[1]Gustavo M. Machado, Manuel M. Oliveira, and Leandro A. F. Fernandes "A Physiologically-based Model for Simulation of Color Vision Deficiency". IEEE Transactions on Visualization and Computer Graphics. Volume 15 (2009), Number 6, November/December 2009. pp. 1291-1298.

Appendix I - Code and Data

Will update with link to app store upon approval (any day now!).

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