铁道科学与工程学报2018，Vol.15Issue(4)：871-879,9.
复杂环境下基于视觉显著性特征的铁轨识别方法
Track detection approach in complex environment based on saliency features
摘要
Abstract
A new track edge detection method based on the saliency features was proposed to overcome the detection problem in complex environment. In order to extract the edge of track features, the muti-scale Gabor filter was introduced and the suppressing operator was used to realize inhibition of environmental interference information, which together established the fusion detection model like the Human Visual System. The evaluation model for track salient features was built to further filter out false edges, while enhancing the right edges by angle statistics method. Experimental examples were made including under the condition of varying illumination or noise. The results show that the proposed method is more suitable for track edge detection in complex environment and similar detection scenes, compared with other detection methods.关键词
边缘检测/复杂环境/显著性评价/多尺度Gabor算子Key words
edge detection/complex environment/saliency evaluation/muti-scale Gabor filter分类
交通工程引用本文复制引用
宋亚帆,潘迪夫,韩锟..复杂环境下基于视觉显著性特征的铁轨识别方法[J].铁道科学与工程学报,2018,15(4):871-879,9.基金项目
湖南省自然科学基金资助项目(2016JJ4117) （2016JJ4117）
