铁道科学与工程学报Issue(3)：509-514,6.
基于视觉注意力和 PLSA 模型的钢轨表面缺陷检测
Rail surface defect detection based on visual attention and PLSA model
摘要
Abstract
Aimed at the status quo fact that speed,accuracy and classification of rail surface defects are relative-ly low,this paper proposed a rail surface defect detection method based on visual attention and PLSA model method which is a combination of brightness and texture of the visual attention model to detect surface defects of rail,extraction of defects region of the original image,and uses the PLSA model to classify the defects.The ex-perimental results show that the proposed method,improves the speed,precision and classification of rail surface defects detection and can meet the requirements of the rail surface defects detection.关键词
钢轨表面缺陷/视觉注意力/PLSA/缺陷分类Key words
surface defects/visual attention/PLSA/defect classification分类
交通工程引用本文复制引用
王军..基于视觉注意力和 PLSA 模型的钢轨表面缺陷检测[J].铁道科学与工程学报,2015,(3):509-514,6.基金项目
国家自然科学基金资助项目（50808025）；中山市科技局工业攻关计划项目 （）
