Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints
Accurate pupil localization is crucial for the eye-tracking technology used in monitoring driver fatigue. However, factors such as poor road conditions may result in blurred eye images being captured by eye-tracking devices, affecting the accuracy of pupil localization. To address the above problems...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/6/1749 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850087956937703424 |
|---|---|
| author | Shufang Qiu Yi Wang Zeyuan Liu Huaiyu Cai Xiaodong Chen |
| author_facet | Shufang Qiu Yi Wang Zeyuan Liu Huaiyu Cai Xiaodong Chen |
| author_sort | Shufang Qiu |
| collection | DOAJ |
| description | Accurate pupil localization is crucial for the eye-tracking technology used in monitoring driver fatigue. However, factors such as poor road conditions may result in blurred eye images being captured by eye-tracking devices, affecting the accuracy of pupil localization. To address the above problems, we propose a real-time pupil localization algorithm for blurred images based on double constraints. The algorithm is divided into three stages: extracting the rough pupil area based on grayscale constraints, refining the pupil region based on geometric constraints, and determining the pupil center according to geometric moments. First, the rough pupil area is adaptively extracted from the input image based on grayscale constraints. Then, the designed pupil shape index is used to refine the pupil area based on geometric constraints. Finally, the geometric moments are calculated to quickly locate the pupil center. The experimental results demonstrate that the algorithm exhibits superior localization performance in both blurred and clear images, with a localization error within 6 pixels, an accuracy exceeding 97%, and real-time performance of up to 85 fps. The proposed algorithm provides an efficient and precise solution for pupil localization, demonstrating practical applicability in the monitoring of real-world driver fatigue. |
| format | Article |
| id | doaj-art-fbcaebd4b32e4b78976371e16d5233d3 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-fbcaebd4b32e4b78976371e16d5233d32025-08-20T02:43:07ZengMDPI AGSensors1424-82202025-03-01256174910.3390/s25061749Real-Time Pupil Localization Algorithm for Blurred Images Based on Double ConstraintsShufang Qiu0Yi Wang1Zeyuan Liu2Huaiyu Cai3Xiaodong Chen4Key Laboratory of Opto-Electronics Information Technology of Ministry of Education, School of Precision Instruments and Optoelectronic Engineering, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Opto-Electronics Information Technology of Ministry of Education, School of Precision Instruments and Optoelectronic Engineering, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Opto-Electronics Information Technology of Ministry of Education, School of Precision Instruments and Optoelectronic Engineering, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Opto-Electronics Information Technology of Ministry of Education, School of Precision Instruments and Optoelectronic Engineering, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Opto-Electronics Information Technology of Ministry of Education, School of Precision Instruments and Optoelectronic Engineering, Tianjin University, Tianjin 300072, ChinaAccurate pupil localization is crucial for the eye-tracking technology used in monitoring driver fatigue. However, factors such as poor road conditions may result in blurred eye images being captured by eye-tracking devices, affecting the accuracy of pupil localization. To address the above problems, we propose a real-time pupil localization algorithm for blurred images based on double constraints. The algorithm is divided into three stages: extracting the rough pupil area based on grayscale constraints, refining the pupil region based on geometric constraints, and determining the pupil center according to geometric moments. First, the rough pupil area is adaptively extracted from the input image based on grayscale constraints. Then, the designed pupil shape index is used to refine the pupil area based on geometric constraints. Finally, the geometric moments are calculated to quickly locate the pupil center. The experimental results demonstrate that the algorithm exhibits superior localization performance in both blurred and clear images, with a localization error within 6 pixels, an accuracy exceeding 97%, and real-time performance of up to 85 fps. The proposed algorithm provides an efficient and precise solution for pupil localization, demonstrating practical applicability in the monitoring of real-world driver fatigue.https://www.mdpi.com/1424-8220/25/6/1749eye trackerblurred imagespupil center localizationgrayscale constraintsgeometric constraintspupil shape index |
| spellingShingle | Shufang Qiu Yi Wang Zeyuan Liu Huaiyu Cai Xiaodong Chen Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints Sensors eye tracker blurred images pupil center localization grayscale constraints geometric constraints pupil shape index |
| title | Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints |
| title_full | Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints |
| title_fullStr | Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints |
| title_full_unstemmed | Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints |
| title_short | Real-Time Pupil Localization Algorithm for Blurred Images Based on Double Constraints |
| title_sort | real time pupil localization algorithm for blurred images based on double constraints |
| topic | eye tracker blurred images pupil center localization grayscale constraints geometric constraints pupil shape index |
| url | https://www.mdpi.com/1424-8220/25/6/1749 |
| work_keys_str_mv | AT shufangqiu realtimepupillocalizationalgorithmforblurredimagesbasedondoubleconstraints AT yiwang realtimepupillocalizationalgorithmforblurredimagesbasedondoubleconstraints AT zeyuanliu realtimepupillocalizationalgorithmforblurredimagesbasedondoubleconstraints AT huaiyucai realtimepupillocalizationalgorithmforblurredimagesbasedondoubleconstraints AT xiaodongchen realtimepupillocalizationalgorithmforblurredimagesbasedondoubleconstraints |