自动化与信息工程2025，Vol.46Issue(2)：1-8,8.DOI:10.12475/aie.20250201
基于高分辨率特征图的工业产品表面缺陷检测算法
Surface Defect Detection Algorithm for Industrial Products Based on High-resolution Feature Maps
摘要
Abstract
In the field of industrial manufacturing,surface defect detection of processed products can effectively improve the quality of finished products.Industrial product surface defects often exhibit characteristics such as low contrast,irregular shapes,small and slender sizes,and significant noise,making the detection task highly challenging.To address this issue,a surface defect detection algorithm for industrial products based on high-resolution feature maps is proposed.First,a real-time high-resolution network(RHNet)is introduced,which maintains the input and output feature maps of each stage at 1/4 of the original image resolution,effectively preserving more detailed information.Then,a short-term dual-branch module(SDBM)is proposed to process high-resolution feature maps in real time.Finally,a fast parallel aggregation pyramid pooling module(FPAPPM)is designed to rapidly extract deep level information and perform multi-scale context fusion.Experimental results demonstrate that the RHNet model performs well in both surface defect modeling capability and detection performance,meeting the real-time requirements and deployment needs of industrial scenarios.关键词
表面缺陷检测/高分辨率特征图实时网络/多尺度融合Key words
surface defect detection/real-time network based on high-resolution feature maps/multi-scale fusion分类
计算机与自动化引用本文复制引用
王伊杰,蔡建扑,任志刚..基于高分辨率特征图的工业产品表面缺陷检测算法[J].自动化与信息工程,2025,46(2):1-8,8.基金项目
国家自然科学基金资助项目(62073088,U1911401) （62073088,U1911401）
广东省重点领域研发计划资助项目(2021B0101200005) （2021B0101200005）
广东省基础与应用基础研究基金资助项目(2019A1515011606). （2019A1515011606）
