Real-Time Iris recognition Biometric Attendance System Using Image Processing Techniques.

The article focuses on the development and evaluation of a real-time, contactless biometric attendance system based on iris recognition using image processing techniques. It addresses limitations of traditional attendance methods and contact-based biometrics by employing standard camera hardware to capture iris images, followed by segmentation, normalization, feature extraction via 2D Gabor filters, and template matching using Hamming Distance within a decision matrix framework to ensure accuracy and robustness. Experimental results with 40 participants demonstrate high segmentation accuracy (93.8%), genuine match accuracy (97.2%), low False Acceptance Rate (1.4%), and False Rejection Rate (2.1%), with an average recognition time of 1.8 seconds, indicating suitability for real-time deployment in educational and corporate environments. The system’s contactless nature enhances hygiene and security, while future improvements may include deep learning-based segmentation, liveness detection, and multimodal biometric integration to further increase reliability and applicability.