2018 4th International Conference on Science and Technology (ICST) 2018
DOI: 10.1109/icstc.2018.8528286
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Robust Pupil Localization Algorithm Based on Circular Hough Transform for Extreme Pupil Occlusion

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Cited by 14 publications
(7 citation statements)
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“…In a more complex model, not only is the iris fitted into a circle, but also the upper and lower eyelids are fitted into parabolas. For example, a shape-based method is adopted to fit the pupil into a circle, and then Hough circle transformation is used to achieve pupil position in [7]. Furthermore, two new features of Semi-Circular Edge Shape and Semi-Ellipse Edge Shape are reported in the literature, to make full use of the edge shape features of iris and eyelid [8].…”
Section: B Iris Center Localization Methodsmentioning
confidence: 99%
“…In a more complex model, not only is the iris fitted into a circle, but also the upper and lower eyelids are fitted into parabolas. For example, a shape-based method is adopted to fit the pupil into a circle, and then Hough circle transformation is used to achieve pupil position in [7]. Furthermore, two new features of Semi-Circular Edge Shape and Semi-Ellipse Edge Shape are reported in the literature, to make full use of the edge shape features of iris and eyelid [8].…”
Section: B Iris Center Localization Methodsmentioning
confidence: 99%
“…Feature extraction in real-time from a webcam is highly dependent on the unobtrusive pupil tracking approach. Earlier works found promising results in finding pupil area using Circular Hough Transform (CHT) [15], [30], [31], and therefore, we adapted this technique for pupil tracking. To further improve the performance of such approach, the input image (eye image) that has been fed into CHT plays a vital role.…”
Section: Related Workmentioning
confidence: 99%
“…However, for the eye image with no apparent difference between the target and background, the segmentation parameters cannot be calculated accurately, resulting in a large error in pupil location. In addition, Chen et al [10] and Setiawan et al [11] improved the traditional Hough transform circle detection method by introducing the Canny edge detection operator and proposed a pupil localization method based on the circular Hough transform. This method can achieve relatively accurate localization of artificially blocked pupils in high-quality images.…”
Section: Related Workmentioning
confidence: 99%