This chapter aims to measure the size distribution of metal particles of varying dimensions using image processing techniques applied to images obtained from a scanning electron microscope (SEM). Both traditional manual measurement techniques and advanced image-processing-based methods were employed during the analysis. In particular, the You Only Look Once (YOLO) algorithm was utilized as a deep learningbased approach for the detection and classification of metal particles. YOLO performs object detection and localization rapidly and with high accuracy, providing significant advantages in particle size measurement. The accuracy, sensitivity, and processing time of the algorithms used in this study were compared, and their performance was evaluated against conventional methods such as ImageJ. The obtained data were examined through statistical analyses, and the most suitable method was identified. The results demonstrate the advantages of the YOLO algorithm in determining particle size distribution in SEM images and indicate that image-processing-based algorithms can serve as efficient and effective tools for particle size analysis.