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A Fast Center of Pupil Detection Algorithm for VOG-Based Eye Movement Tracking.
1Department of Biomedical Engineering, Inje University, Kimhae, 621-749, Korea.
Summary
This study presents a new algorithm for the video-oculograph method to accurately detect the pupil center in eye images. The algorithm enhances image quality and removes noise, even with obstructions like eyelashes.
Area of Science:
- Biomedical Engineering
- Computer Vision
- Ophthalmology
Background:
- Accurate eye tracking is crucial for various applications, including clinical diagnostics and human-computer interaction.
- Existing pupil detection methods can be sensitive to image quality issues and occlusions.
Purpose of the Study:
- To develop and validate a robust algorithm for pupil center detection using the video-oculograph method.
- To improve the accuracy and reliability of eye tracking systems.
Main Methods:
- An algorithm was developed for pupil center detection from eye images captured by a CCD camera.
- Image processing techniques including thresholding, enhancement, and noise reduction were applied.
- The algorithm was tested on 640x480 pixel, 8-bit grayscale images.
Main Results:
- The proposed algorithm successfully detected the pupil center.
- Effective noise removal and image enhancement were achieved.
- Robust performance was demonstrated even when the pupil area was partially obscured by eyelashes or eyelids.
Conclusions:
- The developed algorithm provides a reliable method for pupil center detection in video-oculography.
- This technique offers improved accuracy for eye tracking, even under challenging imaging conditions.
