Implementation of Illumination Invariant Face Recognition for Accessing User Record in Healthcare Kiosk

Abstract

The availability of health check facilities that are increasingly affordable in terms of cost and distance is very useful for the community. Therefore, the presence of a healthcare kiosk that is installed everywhere will certainly be very beneficial for the wider community. In this paper, we developed a user-login method in the healthcare kiosk without utilizing any additional tools so that it is quite efficient, using face recognition biometric technology. We added the invariant illumination feature to face recognition technology to ensure that the healthcare kiosk system will continue to work even in places with changing lighting. This feature uses the light intensity contrast adjustment in the image automatically by employing the Fuzzy Inference System (FIS) and Genetic Algorithm (GA). Based on the results of testing the user-login system, we get an accuracy of 85.57% with an ideal distance of 30-60 cm. The system works with maximum performance in some experimental conditions such as normal lighting, backlighting, direct-lighting, low-lighting, and dark. Users that use facial recognition as a login method, the facial recognition program will capture the user's face and match it to the database. If the user is registered in the database, the system will inform the user that the user is logged in successfully, otherwise, if the user is not logged in, the system will notify the user as unknown.