Volume 11 - Volume 11
Automated Checkout for Stores: A Computer Vision Approach
Abstract
One of the most common current advances made by companies that use cutting-edge technology to
remain competitive in the market is the automation of processes. Using Computer Vision techniques
is one way to get into the automation processes without spending a lot of money. This strategy hence
results in increased productivity in the short term as well as increased earnings in the long run. In
reality, it aimed to improve an algorithm that had already been developed, but working on it has been
more difficult than anticipated due to the emergency caused by the Covid-19 pandemic. In this study,
we proposed an automated checkout for stores based on the YOLOv4 algorithm to address the
challenge. The dataset taken consists of the object categories inside a large supermarket. The
proposed method includes features such as detection of the objects, count the similar objects,
generate the bill of the commodities identified and allows the user to make the payment online. The
Automated Checkout for Stores demonstrated fast checkout, a user-friendly interface, customer
satisfaction, and, in this pandemic period, it provides social distancing as well as a safe and
comfortable shopping experience for the customers.
Paper Details
PaperID: 2053
Author's Name: Namitha James, Nikhitha Theresa Antony, Sara Philo Shaji, Sherin Baby and Jyotsna Annakutty
Volume: Volume 11
Issues: Volume 11
Keywords: Camera, Detection, MS COCO, Stripe, YOLOv4.
Year: 2021
Month: May
Pages: 1830-1841