An automated system in ATM booth using face encoding and emotion recognition process

Nowadays, the banking transaction system is more flexible than the previous one. When the banking sector introduces the ATM booth to us, it was a step ahead to ease the human effort. Here, ATM booth is an automated teller machine that gives out money to the consumer by inserting a card in it. All ATM booths support both credit and debit cards for the transaction, and this has saved everyone's time. But still, there are some certain situations, i.e., forgetting the card authentication details for a transaction can ruin a consumer's day. For this reason, this paper has tried to propose a system that will help everyone regarding this situation. This proposed system is about face encoding process with an emotion recognition test for making transactions faster and accurate, based on Convolutional Neural Network (CNN). However, normal card transactions can still be possible besides using the proposed system. FER2013 dataset was used for training and then tested the model using our own sample images. The result shows that the proposed system can correctly separate ĝ 'Happy' faces from other emotional faces and allow the transaction to proceed.