【摘要】：高鐵鋼軌表面圖像具有光照變化、反射不均、特征少等特點,使得缺陷自動檢測極為困難。為了在高速運動過程中,從復雜的鋼軌表面圖像中分割出缺陷,根據(jù)鋼軌表面圖像具有沿鋼軌方向像素值基本不變的特征,建立鋼軌表面圖像背景模型,提出了基于背景差分的鋼軌表面缺陷檢測算法,主要包括鋼軌區(qū)域提取、背景建模差分、閾值分割和圖像濾波4個步驟,其主要特點是將視頻監(jiān)控中的背景差分法推廣到缺陷圖像分割領(lǐng)域,同時借助自適應(yīng)閾值分割和濾波技術(shù),在一定程度上,解決了鐵軌表面缺陷分割過程中圖像光照變化、反射不均、特征少等不利因素的影響。實驗仿真和現(xiàn)場測試結(jié)果均表明,該方法對塊狀缺陷能很好地識別,召回率和準確率分別達96%和80.1%。
[Abstract]:The surface image of high-speed rail is characterized by light variation, uneven reflection and less characteristics, which makes automatic defect detection very difficult. In order to segment defects from complex rail surface images during high-speed motion, a background model of rail surface images is established according to the fact that the rail surface images have the same pixel value along the rail direction. A rail surface defect detection algorithm based on background difference is proposed, which includes four steps: rail region extraction, background modeling difference, threshold segmentation and image filtering. The main feature of this method is that the background differential method in video surveillance is extended to the field of defect image segmentation. At the same time, with the help of adaptive threshold segmentation and filtering technology, the illumination variation of the image in the course of rail surface defect segmentation is solved to a certain extent. Uneven reflection, less characteristics and other adverse factors. The experimental results and field test results show that the proposed method can recognize the block defects well, and the recall rate and accuracy are 96% and 80.1%, respectively.
【作者單位】： 湖南大學電氣與信息工程學院;鄭州輕工業(yè)學院電氣信息工程學院;湘潭大學信息工程學院;
【基金】：國家自然科學基金(60835004;6107212;6117216;61175075) 河南省科技攻關(guān)計劃(42102210514;162102210060)項目資助
【分類號】：U216.3;TP391.41
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本文編號：2315980