ChatGPT Meets Iris Biometrics

TL;DR

This paper explores the application of GPT-4 multimodal LLMs in iris recognition, demonstrating high adaptability and accuracy in complex biometric analysis tasks, including under challenging conditions and against presentation attacks.

Contribution

It is the first to evaluate GPT-4's capabilities in iris biometrics, showing its effectiveness and advantages over existing AI models like Gemini Advanced.

Findings

GPT-4 accurately identifies iris features under diverse conditions

GPT-4 outperforms Gemini Advanced in complex iris analysis

Nuanced query framing enhances biometric data insights

Abstract

This study utilizes the advanced capabilities of the GPT-4 multimodal Large Language Model (LLM) to explore its potential in iris recognition - a field less common and more specialized than face recognition. By focusing on this niche yet crucial area, we investigate how well AI tools like ChatGPT can understand and analyze iris images. Through a series of meticulously designed experiments employing a zero-shot learning approach, the capabilities of ChatGPT-4 was assessed across various challenging conditions including diverse datasets, presentation attacks, occlusions such as glasses, and other real-world variations. The findings convey ChatGPT-4's remarkable adaptability and precision, revealing its proficiency in identifying distinctive iris features, while also detecting subtle effects like makeup on iris recognition. A comparative analysis with Gemini Advanced - Google's AI model - highlighted ChatGPT-4's better performance and user experience in complex iris analysis tasks. This research not only validates the use of LLMs for specialized biometric applications but also emphasizes the importance of nuanced query framing and interaction design in extracting significant insights from biometric data. Our findings suggest a promising path for future research and the development of more adaptable, efficient, robust and interactive biometric security solutions.