华侨大学学报（自然科学版）2025，Vol.46Issue(5)：569-580,12.DOI:10.11830/ISSN.1000-5013.202508037
基于改进YOLOv5n模型的靶面弹孔识别技术方案
Bullet Hole Recognition Technology Scheme Based on Improved YOLOv5n Model
摘要
Abstract
To address the issues of insufficient accuracy,weak anti-interference capability,and high mainte-nance cost in existing automatic recognition and calibration technologies for bullet hole rings on target surfaces,a bullet hole recognition scheme based on improved YOLOv5n model is proposed.In the image preprocessing stage,multi-scale template matching is employed to locate the target surface region,the Laplacian operator is used to filter images,and morphological processing is applied to extract the effective area of the chest target.Several improvements are further implemented,including Mosaic data augmentation optimization,backbone network optimization,Neck structure and detection head refinement,attention mechanism integration,and loss function optimization.As a result,the improved YOLOv5n model achieves an mAP@0.5 of 97.43％with only 2.2× 1012 s-1 floating point operations.Perspective correction matrices are applied for bullet hole localiza-tion,and ring values are calibrated using semi-arcradius calculations.A dataset containing 312 images is con-structed,and the model is deployed and tested on the RK3588 platform.The results show that the proposed method achieves a recognition speed of 21 frames per second,effectively balances the requirements of accuracy and real-time performance,and providing reliable technical support for the automatic bullet hole ring recogni-tion and calibration on target surface.关键词
透视校正/YOLOv5n/靶面标定/边缘计算/目标检测Key words
perspective correction/YOLOv5n/target surface calibration/edge computing/target detection分类
计算机与自动化引用本文复制引用
黄诚惕,曾智浩,王飞鹏,朱建清..基于改进YOLOv5n模型的靶面弹孔识别技术方案[J].华侨大学学报（自然科学版）,2025,46(5):569-580,12.基金项目
福建省自然科学基金杰出青年基金资助项目(2022J06023) （2022J06023）
福建省科技兴警研究计划项目(2024Y0064) （2024Y0064）
福建省泉州市高层次人才创新创业项目(2023C013) （2023C013）
