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All-digital ring-wedge detector applied to fingerprint recognition.

D M Berfanger¹, N George

¹Institute of Optics, Center for Electronic Imaging Systems, University of Rochester, Rochester, New York 14627, USA. berfang@optics.rochester.edu

|February 29, 2008

Summary

A novel all-digital ring-wedge detector system accurately recognizes fingerprints using neural networks. This system analyzes spatial-frequency content and edge-angle correlations for robust fingerprint sorting and quality assessment.

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Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor (IRIS)

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Area of Science:

Digital image processing
Biometrics
Artificial intelligence

Background:

Traditional coherent optoelectronic processors often utilize analog multielement arrays.
Digital systems offer advantages in flexibility and processing capabilities for image analysis.

Purpose of the Study:

To introduce an all-digital ring-wedge detector system that simulates analog systems.
To demonstrate the system's efficacy in fingerprint recognition, sorting, and quality assessment.

Main Methods:

Development of an all-digital ring-wedge detector system.
Application of neural-network software for image analysis.
Utilizing ring-only and wedge-only input neurons for specific feature extraction.

Main Results:

High accuracy achieved in fingerprint recognition, including orientation and scale-independent sorting.
Successful application on windowed subregions for localized spatial-frequency and edge-angle correlation analysis.
Generation of local ridge-orientation maps and detection of poor print quality regions.

Conclusions:

The all-digital ring-wedge detector system effectively processes both hard-copy and digital imagery.
Both direct-image data and spatial-transform data are crucial for comprehensive fingerprint analysis.
The system provides a versatile tool for advanced biometric identification and image quality evaluation.