학술논문

Detection of Fingerprint Authenticity Based on Deep Learning Using Image Pixel Value
Document Type
Conference
Source
2020 Fifth International Conference on Informatics and Computing (ICIC) Informatics and Computing (ICIC), 2020 Fifth International Conference on. :1-6 Nov, 2020
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Image recognition
Image matching
Fingerprint recognition
Tools
Object recognition
Informatics
fingerprint
authenticity
deep learning
CNN
image
Language
Abstract
Research on fingerprints has been done a lot, this is because of so many uses of fingerprints as an access tool to enter a system. This method is used to ensure the authenticity of authorized users. Fingerprints are used as biometric identification because fingerprints have a unique pattern that is different from every human fingerprint. The many uses of fingerprint biometric systems also cause many threats to the system, fingerprint forgery occurs so that it can be used to access the system illegally. Therefore this study proposes a system to be able to recognize the authenticity of a fingerprint. CNN is generally designed for object recognition of an image, making it suitable for recognizing fingerprint images to determine if a fingerprint is genuine or fake. The results of the evaluation of several experiments conducted obtained the highest accuracy value of 95.32% for determining the authenticity of fingerprints.