Published Paper Details:

The diamond industry demands meticulous precision throughout its processes, particularly in planning and quality control stages. Manual verification, however, is time-consuming and prone to human error. This paper presents an automated smart imaging system designed to streamline the process of verifying line markings made during diamond planning. Using a custom-trained YOLO (You Only Look Once) object detection model, the system automates the task of checking whether the lines drawn by planning personnel match the autoplan suggested by software. By integrating machine learning and image processing techniques, our system aims to automate the manual inspection process, significantly reducing human error, enhancing efficiency, and ensuring consistent diamond quality. Our proposed solution demonstrates the potential for automation in precision industries, such as diamond processing, while still supporting human inspectors by reducing repetitive manual tasks