Blink detection for off-angle iris images using deep learning

Hasan Palta; Timi Omoteso; Mahmut Karakaya

doi:10.1117/12.2662248

13 June 2023 Blink detection for off-angle iris images using deep learning

Hasan Palta, Timi Omoteso, Mahmut Karakaya

Proceedings Volume 12527, Pattern Recognition and Tracking XXXIV; 1252707 (2023) https://doi.org/10.1117/12.2662248
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Iris recognition is one of the well-known areas of biometric research. However, in real-world scenarios, subjects may not always provide fully open eyes, which can negatively impact the performance of existing systems. Therefore, the detection of blinking eyes in iris images is crucial to ensure reliable biometric data. In this paper, we propose a deep learning-based method using a convolutional neural network to classify blinking eyes in off-angle iris images into four different categories: fully-blinked, half-blinked, half-opened, and fully-opened. The dataset used in our experiments includes 6500 images of 113 subjects and contains images of a mixture of both frontal and off-angle views of the eyes from -50o to 50o in gaze angle. We train and test our approach using both frontal and off-angle images and achieve high classification performance for both types of images. Compared to training the network with only frontal images, our approach shows significantly better performance when tested on off-angle images. These findings suggest that training the model with a more diverse set of off-angle images can improve its performance for off-angle blink detection, which is crucial for real-world applications where the iris images are often captured at different angles. Overall, the deep learning-based blink detection method can be used as a standalone algorithm or integrated into existing standoff biometrics frameworks to improve their accuracy and reliability, particularly in scenarios where subjects may blink.

Conference Presentation

Citation Download Citation

Hasan Palta, Timi Omoteso, and Mahmut Karakaya "Blink detection for off-angle iris images using deep learning", Proc. SPIE 12527, Pattern Recognition and Tracking XXXIV, 1252707 (13 June 2023); https://doi.org/10.1117/12.2662248

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available