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Updated: May 26, 2026
13:19
Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Pseudo-outer product based fuzzy neural network fingerprint verification system.
1Intelligent Systems Laboratory, School of Computer Engineering, Nanyang Technological University, Singapore, Singapore. ashcquek@ntu.edu.sg
Summary
This study introduces a novel fuzzy neural network for robust fingerprint verification. The pseudo outer product fuzzy neural network (POPFNN) effectively identifies individuals even with altered fingerprints due to adverse conditions.
Area of Science:
- Biometrics
- Artificial Intelligence
- Pattern Recognition
Background:
- Fingerprint identification is a century-old law enforcement standard, now automated.
- Fuzzy neural networks are underexplored for fingerprint verification.
- Automated systems have simplified fingerprint analysis.
Purpose of the Study:
- To develop and evaluate a fingerprint verification system using a fuzzy neural network.
- To assess the robustness of the system against fingerprints subjected to adverse conditions.
- To demonstrate the efficacy of the pseudo outer product fuzzy neural network (POPFNN) for biometric identification.
Main Methods:
- Constructed a database of fingerprint images.
- Trained a pseudo outer product fuzzy neural network (POPFNN) for fingerprint similarity detection.
- Tested the system with fingerprint samples subjected to various adverse conditions (wetness, chemical treatments, etc.).
Main Results:
- The POPFNN demonstrated robustness in distinguishing between authentic and spurious fingerprints.
- The system effectively verified fingerprints even after exposure to adverse conditions.
- Experimental results indicate the potential of POPFNN in fingerprint verification systems (FVS).
Conclusions:
- The POPFNN is a powerful tool for fingerprint verification, offering learning, generalization, and computational advantages.
- The developed system can reliably identify individuals despite variations in fingerprint conditions.
- This research highlights the potential of fuzzy neural networks in enhancing biometric security.
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