A Novel Method of Billing System Using Deep Learning

Abstract

In order to make the billing process of goods easier and quicker for the customers as well as the shopkeepers, the RFID tags and the bar-codes are used in most of the products. But for the edible products like fruits and vegetables, these tags cannot be used as each item has to be stuck with the tag and its weight must be measured individually. To overcome this, a system is designed in which the weighing and billing of the fruits and vegetables are automated. The proposed billing system consists of Raspberry pi, a microprocessor with a camera module and a load cell. Using Raspberry pi 3 camera module, images of fruits and vegetables are captured and are recognized by using the deep learning technique, ImageNet which is built on Convolutional Neural Network (CNN) architecture and a machine learning technique, K-means clustering is used for classifying the products into corresponding groups. The camera module captures the images of the fruits and vegetables placed on the tray under which the load cell is placed for the weighing purpose. The price of various items per kg is given as an input to the microprocessor. As a result, the Raspberry pi computes the total cost of the items and displays it on the monitor. The general-purpose high-level programming language, Python is used for developing the efficient deep learning algorithm.