Automated Baggage Size Check: Real-Time Object Measurement Using Aruco Markers in OpenCV

Personal bag inspections are crucial for maintaining security, as they help to identify and prevent the entry of prohibited items, such as weapons, explosives, and other dangerous materials, into secure areas. However, this kind of operation is typically done manually by personnel, and it is a rigorous process. To address this concern, this study aims to develop a real-time automated personal bags size checker. To develop the algorithm, the study made use of Python and the OpenCV library. Moreover, Aruco marker was utilized to calibrate the camera for measuring the object dimensions. In this study, the algorithm achieved an average accuracy of 80.1%. It was determined that factors such as the bag shape, bag attachments, lighting environment, background, number of cameras and its resolution can affect the accuracy of the algorithm. Thus, it was recommended to address the said factors and to utilize artificial intelligence (AI) or machine learning (ML) to further improve the accuracy.