I. F. Farkas, S. Szénási: Pallet Detection using Image Processing. In IEEE 29th International Conference on Intelligent Engineering Systems (INES 2025) Proceedings. pp. 329–334, 2025. ISBN 979-8-3315-9771-9 link

Abstract: This paper presents a software capable of realtime pallet detection and positioning based on live camera feeds. Automated pallet handling plays an increasingly vital role in logistics and industrial processes, significantly enhancing efficiency and reducing workplace risks. To develop the software, computer vision and deep learning techniques were utilized, specifically the YOLOv8 model. The training was conducted using approximately 4,000 images, resulting in high detection accuracy. The system can determine the location and type of pallets and can be integrated into various industrial applications, such as automated material handling systems. Pallet identification is performed using QR codes, and the software employs a MongoDB database to store data associated with the identified pallets. Based on the results, the software can serve as an effective tool for optimizing warehouse and logistics systems, particularly in environments where automation is critical.