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SURVEY ON AUTOMATED CHECKOUT SYSTEM


EOI: 10.11242/viva-tech.01.08.023

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Citation

Darshan Dhamode , Danish Shaikh , Ranjit Narlya , Prof. Kirtida Naik " SURVEY ON AUTOMATED CHECKOUT SYSTEM ", VIVA-IJRI Volume 1, Issue 8, Article 1, pp. 1-8, 2025. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

" This research focuses on an advanced automated checkout system using the YOLOv8 model for real-time object detection. By capturing product images at checkout, the system identifies items without traditional barcode scanning. Trained on a custom dataset, YOLOv8 detects and classifies products, distinguishing between similar packaging variants. It retrieves product details from a database, updates the cart, and calculates the total for a seamless checkout experience. This solution improves speed, reduces errors, and eliminates the need for costly scanning hardware, making it adaptable for various retail setups. By leveraging image-based detection, the system of ers flexibility and high accuracy, even during peak store traf ic. Additionally, it streamlines inventory tracking, enhances operational ef iciency, and improves overall customer satisfaction. Integrating machine learning, computer vision, and object detection, this research focuses on revolutionizing the retail experience."

Keywords

YOLOv8 Model, Image-Based Product Detection, Vision-Based Automation.

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