A Robust Pupil Detection Algorithm based on a New Adaptive Thresholding Procedure
Petronela Bonteanu, Arcadie Cracan, Radu Gabriel Bozomitu, Gabriel Bonteanu · 2019
This paper presents a pupil detection algorithm based on a global adaptive thresholding procedure. The binarization threshold for each image is determined by analyzing the derivative of the percentile function. Additional morphological transformations are used to obtain the set of possible pupil contours. Afterwards, the algorithm selects the largest compact contour, fits an ellipse to it by using the least square method and delivers its center as the output. By using this method, the algorithm achieves good results even in non-uniform and variable lighting conditions. For two representative databases of eye images, the 5 pixels detection rate is higher than 92%.