Dynamic Fingerprint Identification via Interval Image Subtraction
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Solution Overview
Problem
Fingerprint identification systems face security risks due to the ease of obtaining and replicating fingerprint information, and they struggle with high false acceptance and rejection rates, which compromise their reliability and convenience.
Innovation Solution
An identification method utilizing an image sensor to generate dynamic images over a time range with varying exposure intervals, determining whether the image is biological by analyzing sharpness values and subtracting interval images to enhance ridge valley values, thereby improving security and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional fingerprint identification is used, then the identification process is fast and easy to use, but the security is compromised because fingerprints can be obtained and replicated from publicly visited places
Solution Approach 1:
The patent transitions from static fingerprint capture to dynamic fingerprint imaging by capturing multiple images at different time points during the fingerprint placement process. This dynamic approach captures the temporal evolution of ridge patterns, making replication attacks difficult while maintaining user convenience
Solution Approach 2:
The system performs preliminary actions by capturing a sequence of images before final identification occurs. Multiple interval images are captured during the fingerprint placement process, and processing is performed in advance to extract temporal features, enabling security verification before authentication
2Reliability
If more fingerprints are registered to increase reliability, then the identification capability improves, but the system complexity increases
Solution Approach 1:
The patent changes the temporal parameter of fingerprint capture by introducing time-based interval imaging. Instead of capturing a single static image, the system captures multiple images at different time intervals, extracting temporal evolution characteristics that enhance identification capability without requiring additional fingerprint sensors or complex multi-modal biometric systems
3Reliability
If the false acceptance rate is reduced to improve security, then the false rejection rate increases, affecting convenience
Solution Approach 1:
The system implements feedback by analyzing the temporal evolution of ridge patterns across multiple interval images. The processing module compares the dynamic characteristics of captured fingerprints against stored templates, providing feedback on matching quality and confidence levels, enabling accurate differentiation between genuine and spoofed fingerprints while maintaining low false rejection rates
Data Source
AI summary
Provided is an identification method for an identification system, which includes a sensing area and an image sensor. First, a test object is close to the sensing area, so that the image sensor generates a dynamic image. Next, the test object gradually pressurizes the sensing area. Then, the test object completely covers the sensing area, and the image sensor further produces a perspective image. Finally, an identification module is used to determine whether the dynamic image is a biological image according to the perspective image, and to perform a subtraction operation on the dynamic image as a basis to determine whether to unlock the identification system. Therefore, the identification system and the identification method can achieve a real-time determination on whether the dynamic image is a biological image. Also, the identification method greatly improves the false acceptance rate (FAR) and the false rejection rate (FRR) of the identification system.