Automated Detection and Recognition of Engraved Serial Numbers on Metallic Surfaces
Objective
The objective of this project is to develop an automated system for detecting and recognizing engraved serial numbers on metallic surfaces using deep learning techniques, specifically YOLOv8-CBAM and RT-DETR-Swin. The project aims to enhance industrial quality control by accurately identifying engraved Meter no and kWh-rating markings from metallic components captured through industrial inspection cameras. By leveraging YOLOv8-CBAM for attention-guided detection and RT-DETR-Swin for multi-scale feature extraction, the system automatically localizes and classifies engraved serial number regions. The integration of YOLOwill provide visual interpretability by highlighting regions in the image that influence the model's decisions. The goal is to create an efficient, automated solution for engraved serial number recognition on metallic surfaces, enabling rapid and accurate verification of Meter no and kWh-rating markings and enhancing industrial quality control management systems
Paper Publishing
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