Contactless Fingerprint Verification Using Neural Networks
Sanchit Rote, Pranjal Pimpale, Kaushik Reddy, G. T. Haldankar, Priya M. Chimurkar · 2021
Fingerprint recognition is one of the most used biometric system in these days. Different methods used for these are using touch sensors, optical sensors or capacitive sensors. Each one has their own advantages and disadvantages. But all these need to have a physical contact of the finger with the sensor leading to hygienic issues and inaccuracy. Some problems that people face in current fingerprint authentication systems are caused due to smudge marks and oily fingers. To overcome these problems, the concept of contactless fingerprint recognition system can be used. It uses image processing and deep learning model implemented in the form of an app. Usage of public property needs to be minimized for avoiding physical contact and sanitation. Instead of a common instrument, this can be simplified into an application for every user. Using Machine Learning and in-built camera, the instrument can be reciprocated into an application. Since everyone has a smartphone nowadays, the impact of this project would be immense. Hence instead of utilizing a common instrument, this application can be used to do the same, provided they are connected to the same server network.