An Application on Identification With The Face Recognition System
Özlem GÜVEN · DergiPark (Istanbul University) · 2021
Measures taken in areas such as tracking personnel, patients, students, and criminals, protecting mobile devices, and combating fraud have evolved with technological developments in artificial intelligence.Today, face recognition systems are used as one of the fast and precise solutions determined for this need since the identification of the person and identity in these problems requires instantaneous and high accuracy.These systems are generally created by comparing the features in the face images taken from the picture, historical or live video with the features in the real image of the person previously taken.Face recognition systems can be integrated into many applications, as a person and identity verification may be required in almost every sector.In this study, a face recognition system was developed in order to verify the driver using public transportation in the transportation sector.In order to prevent any accident and violation caused by unauthorized driving, it has become necessary to add a personnel recognition and identity verification module to the system.For this requirement, after the driver has verified his biometric data, it was decided that the verification should be repeated instantaneously throughout the ride and at certain intervals so that the driver does not give the ride to another driver.By avoiding the methods such as a fingerprint reader and an iris verification that will distract the driver and risk the driving, a facial recognition system has been created to provide control with video images taken while driving through cameras that are currently on the vehicles and see the driver.In order to check the accuracy of the relevant system, a separate database was created for each driver, which contains images taken from videos during driving at different times.Based on a pre-trained deep learning network with pictures represents the driver, the system was tested by using test images in a database using TensorFlow and OpenCV libraries.In summary, the developed face recognition module is designed to improve the driving safety of authorized and approved personnel on the intelligent transportation system, reduce accidents caused by unauthorized users and ensure driver control.