High-speed pupil dynamic tracking algorithm for RAPD measurement equipment utilizing gray-level features

Abstract

Relative pupillary afferent disorder (RAPD) plays a crucial role in diagnosing optic nerve dysfunction. This paper introduces an innovative equipment design with a high-speed pupil detection algorithm and a binocular independent stimulation optical path. The proposed algorithm utilizes the grayscale characteristics of the pupil region to achieve rapid and accurate pupil detection and tracking. Initially, a pupil threshold is estimated using eigenvalues, enabling the calculation of the pupil centroid. Subsequently, leveraging the unique characteristics of the pupil region, a dynamic tracking algorithm, a second-order partial derivative threshold algorithm, and a pupil diameter extraction algorithm are employed to precisely locate the centroid. By incorporating a binocular independent stimulus light path design, the algorithm overcomes limitations associated with the current measurement equipment. The experimental results demonstrate the algorithm’s high robustness and fast detection speed, meeting the tracking speed requirement of 1250 frames per second for a single eye. These advancements have the potential to significantly enhance the diagnosis and assessment of optic nerve dysfunction.