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Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2017 / Cilt: 17 - Sayı: 2

A CNN BASED ROTATION INVARIANT FINGERPRINT RECOGNITION SYSTEM

Ertuğrul SAATÇI
Rıfat EDİZKAN
Tuba Çelik MAYADAĞLI
Pages
3471–3479
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results are very encouraging for implementing a CNN based fully automatic rotation invariant fingerprint recognition system.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper presents a Cellular Neural Networks (CNN) based rotation invariant fingerprint recognition system by keeping the hardware implementability in mind.
📊
Key Findings & Data:False feature elimination increases the system performance by removing the false minutiae points.
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Conclusion & Impact:The results are very encouraging for implementing a CNN based fully automatic rotation invariant fingerprint recognition system.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This paper presents a Cellular Neural Networks (CNN) based rotation invariant fingerprint recognition system by keeping the hardware implementability in mind. Core point was used as a reference point and detection of the core point was implemented in the CNN framework. Proposed system consists of four stages: preprocessing, feature extraction, false feature elimination and matching. Preprocessing enhances the input fingerprint image. Feature extraction creates rotation invariant features by using core point as a reference point. False feature elimination increases the system performance by removing the false minutiae points. Matching stage compares extracted features and creates a matching score. Recognition performance of the proposed system has been tested by using high resolution PolyU HRF DBII database. The results are very encouraging for implementing a CNN based fully automatic rotation invariant fingerprint recognition system.

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Cite This Article

SAATÇI, E., EDİZKAN, R., MAYADAĞLI, T. Ç. (2022). A CNN BASED ROTATION INVARIANT FINGERPRINT RECOGNITION SYSTEM. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 17 - Sayı: 2, 3471–3479. https://ajindex.com/articles/543571

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