Image level color classification for colorblind assistance
Thomas L. Fuller, Amir Sadovnik · 2017
The advancement and proliferation of augmented reality lends itself to the development of novel techniques for assistive technologies, especially in the realm of computer vision. By enhancing a certain part of the view of a person with visual impairment we can assist them in different tasks. In this work we develop an algorithm to assist people who suffer from color blindness. We first examine different methods for pixel level color classification to select the one that works the best. We then improve the color classification rate by optimizing the labeling over the whole image using graph cuts. Finally, we develop an implementation of the algorithm which can run in real time on Google Glass and show how it can assist those suffering from color blindness.