International Journal of Advanced Research in Computer and Communication Engineering

Abstract: The increasing demand for automated retail solutions has led to the development of smart checkout systems that eliminate the need for manual billing. Traditional checkout processes are time-consuming and prone to human error, creating a need for automated and reliable systems. This paper presents an object detection-based auto checkout system using the YOLO (You Only Look Once) deep learning model to identify and classify items in real time. The system integrates image acquisition, preprocessing, and YOLO-based detection to provide accurate and fast billing. Experiments conducted on a dataset of over 10,000 images of grocery items demonstrated a detection accuracy above 95%, reducing checkout time and improving customer convenience.

Keywords: Auto Checkout System, YOLO, Object Detection, Computer Vision, Deep Learning, Automated Billing, Smart Retail, Real-Time Detection

Downloads: | DOI: 10.17148/IJARCCE.2026.15146