Finger minutiae extraction based on the use of YOLO-V5
In this study, we propose a novel method for detecting minutiae in fingerprint images using YOLOv5, a state-of-the-art object detection algorithm. Our approach utilizes a convolutional neural network (CNN) to identify and locate minutiae points, such as ridge endings and bifurcations, within a finge...
- Autores:
-
Trusiak, Krzysztof
Saeed, Khalid
- Tipo de recurso:
- Conferencia (Ponencia)
- Fecha de publicación:
- 2023
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/14081
- Acceso en línea:
- https://hdl.handle.net/11323/14081
https://repositorio.cuc.edu.co/
- Palabra clave:
- YOLOv5
Fingerprint images
Convolutional neural network (CNN)
- Rights
- closedAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)