Optical Character Recognition In UMS EcoCampus Tourism Registration System

Abstract

The UMS EcoCampus tourist registration is done on paper. Visitors must register in person at the EcoCampus Visitor Information Centre (EVIC), with a maximum of 2 visitors per registration. So, completing registration for each visitor may take longer. The current system stores records on paper. There is a risk of losing records that cannot be recovered. Also, if visitors fill out a form digitally on their phone, the information is not authentic. To address these challenges, this project integrates OCR into the registration system. The OCR engine recognises characters in photos and converts them to digital. The suggested system uses Firebase ML kit to detect characters and Firestore to store data online. The proposed system will be turned into an Android app using Android Studio. So, visitors must download the mobile application and connect their smartphone to the internet. Visitors must use the mobile application to scan their ID cards to allow the system to recognise and register their personal information. This system will assist visitors register and EVIC employees manage records. The constraint of illumination influences the OCR results in this research. Each environment has its own lighting conditions. Outdoor OCR results have a higher accuracy rate than indoor OCR results, according to tests. The interior light source is limited, causing light reflection on the identity card surface.