IRIS-BASED BIOMETRIC IDENTIFICATION SYSTEM USING PYTHON

Abstract

This paper presents the design and implementation of an iris-based biometric identification system using Python. Iris recognition is known for its high accuracy and uniqueness, making it one of the most reliable biometric modalities. The study explores key steps of the process, including image acquisition, segmentation, normalization, feature extraction, and classification. Various algorithms such as histogram analysis, Gabor filters, and convolutional neural networks (CNNs) were evaluated using open-source Python libraries like OpenCV and NumPy. Experimental results based on standard datasets (CASIA, IIT Delhi) demonstrated that CNN-based models achieved up to 96.5% accuracy, outperforming traditional methods. The proposed system offers a practical and efficient solution for secure biometric authentication. Future work includes integrating liveness detection and expanding testing in real-world conditions.