Fingerprint Detection using CNN | Zendy

K. Abhijith Saralaya | Zendy; T Prasanna Lakshmi | Zendy; Sudeepthi Devasari | Zendy; Ramesh Rajini | Zendy; Srigiri Shree Puruhoothi | Zendy

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Fingerprint Detection using CNN

Author(s) -

K. Abhijith Saralaya,

T Prasanna Lakshmi,

Sudeepthi Devasari,

Ramesh Rajini,

Srigiri Shree Puruhoothi

Publication year - 2022

Publication title -

interantional journal of scientific research in engineering and management

Language(s) - English

Resource type - Journals

ISSN - 2582-3930

DOI - 10.55041/ijsrem11836

Subject(s) - artificial intelligence , computer science , biometrics , fingerprint (computing) , pattern recognition (psychology) , convolutional neural network , image (mathematics) , spoofing attack , fingerprint recognition , computer vision , computer security

For biometric recognition, fingerprints are often used. Spoofing attacks based on a synthetic fingerprint, on the other hand, are frequent. We present in this research a method for detecting fingerprints that employ guided filtering and hybrid image analysis. When examining a denoised image, the problem of neglecting the contribution of sharp features is addressed in this study. The method described in this project uses the increased sharp features as well as the denoised features from the hybrid images to get better outcomes. Keywords: Hybrid image analysis, Guided filtering, Convolutional Neural Networks.

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