COLOR BLIND FILTERS By Stacey Osborn

OUTLINE

• INTRODUCTION

•PREVIOUS WORK

•DESCRIPTION

•EXPERIMENTS

•RESULTS

•DISCUSSION

INTRODUCTION

Color Blindness or Color Deficiency affects approximately 8% of men and 0.5% of women of European descent. It can be broken down in to three main categories: Monochromacy, Dichromacy and Anomalous Trichromacy. Dichromacy can be further broken down in to Protanopia, Deuteranopia, and Tritanopia.

In this project I focused primarily on the Deuteranopia form of Dichromacy.

INTRODUCTION – CONTINUED

The purpose of this project was to manipulate digital images using several different processing techniques including: a Daltonization Method, a Recoloring Method, A Contrast Adjustment Method, and a LAB Contrast Adjustment Method in order to make them viewable and distinguishable to those with color vision deficiency and determine which method produces the clearest result.

PREVIOUS WORK

• Daltonization – Daltonize.org

• Chrome Daltonize Plugin

• Colorblind Glasses / Contacts

• Smartphone Real Time Filter Applications

• Image Recoloring Techniques

• Contrast Adjustments

• Color Blind Simulators for Developers

• Color Blind Friendly Colormaps for Developers

DESCRIPTION - DALTONIZATION

• The Daltonization method is currently the

most accepted image manipulation

algorithm and has many variations and

improvements and is used in several browser plugins.For this project I used the very simple

version from daltonize.org

• The first step is to find the LMS values of the RGB image using a conversion matrix

• Then another conversion is made to delete the information associated

with the loss of any of the cone types

• Finally the activity is converted back to the RGB color space

DESCRIPTION - RECOLORING

• Recoloring builds on the Daltonization approach requiring more complex algorithms which have been the focus of several recent academic studies • Mass Spring Method

• Rasche Method • Generalized Histogram

Equalization

DESCRIPTION – RECOLORING CONTINUED

•All recoloring methods have the same main goals – Preserving Contrast and Maintaining Luminance

• The Mass Spring Method used in my survey uses three steps: • Image Quantization • Mass Spring Optimization • Reconstruction

DESCRIPTION – RECOLORING CONTINUED

• The Mass Spring Method represents the color gamut of each class of Dichromacy with two half- planes in the LMS color space approximated together to from a single plane passing through the luminance axis

• The luminance axis is determined by mapping the color gamut of each class of Dichromacy to the approximately perceptually-uniform LAB color space and taking the least-squares to obtain a plain that contains the luminance axis

DESCRIPTION – RECOLORING CONTINUED

• Quantization is completed by assigning each quantized color Pi with mass mi and the position of Pi is initialized with the value of the color as seen by a Dichromat after the rotation of the luminance plane

• Each pair of particles is connected with a spring S with an elasticity coefficient k and rest length (quantized length). At each optimization step the positions are updated and the Spring and length are recalculated with the goal that the perceptual distance between all pairs and the quantized color distance will be approximately the same

• The transformed colors are then determined by inversing the rotation of the luminance plane

DESCRIPTION – RECOLORING CONTINUED

• To adjust for the local minima problem, they switch the sign of the b* coordinate of all rotated quantized colors whose a* coordinates are positive with a perceptual distances between the color itself and the color as perceived by a dichromat is greater than a certain threshold in order to: • Avoid ambiguity

• Switching the b* coordinate for some colors compresses and stretches their associated spring adding additional potential energy

DESCRIPTION - CONTRAST

• First the algorithm adjusts an image’s RGB values to enhance contrast between red and green • The pixel values are then cut in half to make room for pixel values to be increased • Then for every pixel:

• Reds and Greens further from pure red or green are increased significantly while those closer are only marginally increased

• For pixels that are mostly red, the blue value is reduced

• For pixels mostly green, the blue value is increased

DESCRIPTION – LAB COLOR CORRECTION

• Similar to the RGB Contrast but performed in the LAB color space, first the image is converted from the RGB color space to the LAB color space

• The a* values are adjusted relative to their maxima making positive numbers more positive and negative numbers more negative

• The b* value is adjusted based on how red or green it is to bring out blue and yellow hues

• The l* value is then adjusted relative to the a* to adjust the brightness

• Finally the image is converted back to the RGB color space

EXPERIMENTS

I created an online survey using Survey Monkey to compare the Daltonization Method, a Recoloring Method, A Contrast Adjustment Method, and a LAB Contrast Adjustment Method. I used 6 image categories with 5 images each and ran the results through the Vischeck program to simulate a Deuteranope color deficiency.

https://www.surveymonkey.com/s/9FJJM8D

EXPERIMENTS – ART Daltonization

Recoloring

Contrast

LAB Contrast

EXPERIMENTS – TEST

Daltonization

Recoloring

Contrast

LAB Contrast

Contrast

EXPERIMENTS - FLOWERS

Daltonization

Recoloring

LAB Contrast

Contrast

EXPERIMENTS - LANDSCAPES Daltonization

Recoloring

LAB Contrast

Contrast

EXPERIMENTS – PEOPLE

Daltonization

Recoloring

LAB Contrast

Contrast

EXPERIMENTS – MAPS / CHARTS

Daltonization

Recoloring

LAB Contrast

Contrast

RESULTS

Daltonization MS Recoloring LAB Contrast Contrast

Art 69 98 51 47

Color Blind Test 29 90 31 115

Flowers 39 176 31 19

Landscapes 84 110 28 43

People 52 148 31 34

Maps and Charts 90 108 45 22

363 730 217 280

Survey was completed online using Survey Monkey with 53 respondents; the Mass Spring

Recoloring method was preferred by a large margin over the other approaches examined.

DISCUSSION

Why Does this Matter to Future Developers?

QUESTIONS ?