Universal Price Tag Reader for Retail Supermarket

Retail supermarkets are an essential part of today's economy, and managing them is a tedious task. One of the major problems faced by supermarkets today is to keep track of the items available on the racks. Currently, the track of the product on the shelf is kept by price tag readers, which work on a barcode detection methodology that has to be customized for each store. On the other hand, if barcodes are not present on the price tags, the data is manually fed by the staff of the store, which is really time-consuming. This paper presents a universal pipeline that is based on Optical Character recognition and can be used across all kinds of price tags, and is not dependent on barcodes or any particular type of price tag. This project uses various image-possessing techniques to determine and crop the Area of Interest. It detects the price of the product and the name of the product by filtering the OCR outputs based on the area and dimensions of the bounding boxes of the text detected. Additionally, the presented pipeline is also capable of capturing discounted prices, if any, for the products. It has been tested over price tags of five different types, and the accuracy ranges from 78% to 94.5%. 

Keywords: Artificial intelligence, Contour detection, Image processing, Optical character recognition, Retail supermarkets.