Because eggs are highly susceptible to quality deterioration during distribution and storage, maintaining their freshness and safety is a critical factor for the distribution process. Recently, a method for evaluating egg freshness based on measuring ultrasonic velocity has been studied for full inspections, and there is a growing need for rapid measurement technology to determine egg size for accurate ultrasonic velocity calculation. Therefore, this study developed a YOLO-based model capable of measuring the minor axis of eggs, suitable for application in rapid inspection systems. The developed model can recognize eggs in real time and convert the detected pixel information into the actual minor axis values. Additionally, user-friendly software was created to enable real-time visualization and minor axis values. The proposed system can accurately measure the minor axis in under 0.5 seconds, making it well-suited for rapid image acquisition. Ultimately, the developed system is expected to improve the accuracy and efficiency of egg grading, and contribute to the advancement of non-destructive food quality evaluation technologies.