本文關(guān)鍵詞：結(jié)合路面深度影像梯度方向直方圖和分水嶺算法的裂縫檢測　出處：《華中師范大學學報(自然科學版)》2017年05期 　論文類型：期刊論文

  更多相關(guān)文章： 裂縫檢測 深度影像 梯度方向直方圖 分水嶺算法

【摘要】：裂縫檢測對于道路維護和管理具有重要作用.由于深度影像對路面油污、陰影等因素不敏感,近些年來基于深度影像的檢測方法已成為路面裂縫檢測新的研究方向之一.傳統(tǒng)的激光掃描線方法沒有顧及裂縫在整個空間分布的變異性、各向異性和全局性特征,無法有效檢測橫向、塊狀、網(wǎng)狀等裂縫.針對以往算法的不足,提出一種結(jié)合梯度方向直方圖和分水嶺算法的路面裂縫檢測方法.首先,通過梯度方向直方圖算法提取路面深度影像的裂縫邊緣強度和方向;然后,利用裂縫邊緣方向改進傳統(tǒng)分水嶺算法,最終提取裂縫目標.實驗結(jié)果表明,該方法不僅能夠準確檢測多種類型的裂縫目標,而且能識別裂縫破損程度.
[Abstract]:Crack detection plays an important role in road maintenance and management, because depth image is not sensitive to road oil, shadow and other factors. In recent years, the detection method based on depth image has become one of the new research directions of pavement crack detection. The traditional laser scanning line method does not take into account the variability of crack distribution in the whole space. Anisotropic and global characteristics, can not effectively detect transverse, block, mesh and other cracks. In view of the shortcomings of previous algorithms. A method of pavement crack detection based on gradient direction histogram and watershed algorithm is proposed. Firstly, the edge strength and direction of pavement depth image are extracted by gradient direction histogram algorithm. The experimental results show that the proposed method can not only accurately detect various types of crack targets, but also identify the degree of fracture damage.
【作者單位】： 湖北工業(yè)大學計算機學院;
【基金】：湖北省教育廳資助基金項目(2014277)
【分類號】：TP391.41;U418.66
【正文快照】： 裂縫是路面最常見的病害之一,自動檢測裂縫對于公路檢測與養(yǎng)護管理具有重要意義.目前,裂縫檢測算法主要以路面二維圖像的裂縫灰度特征及形態(tài)特征作為判別裂縫的準則;由于受到圖像采集系統(tǒng)硬件條件的限制及外界光照影響,伴隨路面油污、陰影、輪胎痕跡、隨機噪聲等因素帶來的干，

本文編號：1420294