Aiding Color Vision Deficiency with Image Recognition and Machine Learning

This research tackles the challenge of colorblindness, affecting millions, by developing a machine learning system that translates images for easier visualization by individuals with red-green color deficiency (Deuteranopia).The system first mimics Deuteranopic vision through machine learning training, then reverses this process to enhance red and green hues in images, making them more distinct and recognizable for colorblind individuals.Tests confirm the system's effectiveness in simulating normal color perception.Beyond science, this project emphasizes empathy and inclusion, aiming to create a more accessible world.It demonstrates the significant potential of machine learning in aiding colorblind vision, paving the way for future iterations addressing broader forms of colorblindness and further refinement with larger datasets.