Assistive Learning Technologies using Image Processing Exploration for Special needs Education: Color Blind

This research focuses on the advanced image processing techniques tailored for individuals with color vision deficiencies (CVD). Transforming and manipulating images for both modification purposes using matrix transformation to make them easily identifiable by people with CVD is the most important reason for creating visual instruction material accessible. An easily adaptable and scalable solution integrated into various educational settings is through the development of a web application. Both teachers and students can easily access the benefits of this friendly and easy-to-use application, which can be utilized without any sophisticated equipment. This research gives a detailed evaluation of how effective the tool was for users with CVD in understanding visual materials. The initial results state that people with CVD engaged more frequently and successfully with the modified text, thereby underlining the promise of machine learning in particular, visual technologies for assistive aids. This shows how advanced algorithms can render a free path toward accessibility for all users across different dimensions in visual learning. This work introduces a novel real-time assistive system combining matrixbased color transformation and Vision Transformer (ViT) refinement for color vision deficiency (CVD) correction, without relying on external datasets. Unlike traditional methods, our solution operates entirely through synthetic pixel manipulation and hierarchical feature extraction, enabling fast, adaptive enhancement of educational images.