OCR 81mm 기반 박격포탄 표기 상태판별

Abstract

This study introduces an automated system using optical character recognition (OCR) technology to identifymarkings on 81-mm mortars, aiming to overcome the inefficiencies and inconsistencies of expensive andtime-consuming manual inspection processes. We created a measurement environment to identify the markingsof 81-mm mortar shells and trained and evaluated their performance using the representative model ofperformance and EasyOCR framework using multilingual text detection (MLT). The model was trained usingthe AI-HUB dataset and self-generated data as training data, with its performance evaluated using precision,recall, and F-measures. The experimental results indicated that the EasyOCR model performed similarly torepresentative models. Therefore, the automated system proposed in this study can effectively identify themarkings of 81-mm mortars and is expected to contribute toward improving the efficiency and reliability ofthe inspection and discrimination process, thus enabling efficient management and maintenance of mortars—essential for military operations.