Detection and correction of the flashing parts that trigger photosensitive epilepsy in videos

Photosensitive epilepsy (PSE) is a neurological disorder that can be triggered by flashing patterns in video sequences, affecting individuals across all age groups. As digital content continues to accumulate, the risk of inadvertently exposing viewers to PSE triggers has increased, necessitating robust detection and correction mechanisms. This study presents a comprehensive approach to identifying and mitigating video content that could potentially trigger PSE. By leveraging image processing techniques, we develop a system that automatically detects segments of video content likely to provoke PSE episodes. The system adheres to established guidelines from organizations such as Ofcom, ITU, and W3C, with a particular emphasis on W3C's standards for Internet content. Upon detection, corrective measures are applied to modify the offending video segments, thus reducing or eliminating the risk of triggering PSE. This approach not only enhances viewer safety but also supports content creators in adhering to best practices for accessibility. The proposed method is evaluated on a range of video sequences, demonstrating its effectiveness in both detection accuracy and the successful application of corrections.