Development of a Real-Time Color Blindness Correction Progressive Web App (PWA) Using Daltonization Methods and WebGL Hardware Acceleration

Color Vision Deficiency (CVD) is a visual sensory disorder that affects an individual’s ability to distinguish certain colors, particularly in the red green and blue yellow spectrum. This condition can limit accessibility to digital visual information such as user interfaces, graphics, and navigation systems. This study aims to develop a web-based real-time color correction application by integrating the Daltonization algorithm with WebGL technology in a Progressive Web App (PWA) architecture. The system utilizes GPU acceleration through fragment shaders to perform parallel image processing, resulting in improved computational efficiency, achieving processing speeds of 35-57 FPS—a 280% to 380% increase compared to conventional CPU-based approaches. The implementation of color transformation in the LMS color space enhances visual contrast, enabling users with CVD to better differentiate colors. The results indicate that the proposed system is capable of delivering responsive performance with stable real-time processing, while maintaining accessibility and cross-platform usability. This research contributes to the development of inclusive digital technologies by providing an efficient and practical solution for color vision accessibility in modern web applications. The main contribution of this research lies in the novel integration of the Daltonization algorithm entirely within the GPU fragment shaders of a PWA, enabling zero-latency, client-side color correction that eliminates server dependencies and safeguards user privacy.

Keywords: Color Vision Deficiency, Daltonization, WebGL, Real-Time Processing, Accessibility