【摘要】：隨著我國高等級公路建設(shè)的快速發(fā)展,公路的檢測和維護工作在國家經(jīng)濟建設(shè)以及民生建設(shè)中的作用受到越來越多的重視。目前,傳統(tǒng)的人工檢測已不能滿足公路快節(jié)奏發(fā)展的要求,因此,路面破損自動檢測技術(shù)的研究變得尤為重要。近年來,隨著計算機技術(shù)的迅猛發(fā)展,基于計算機視覺的路面破損檢測系統(tǒng)已經(jīng)應(yīng)用于公路破損檢測和養(yǎng)護領(lǐng)域。本文針對路面破損檢測算法中存在的熱點、難點進行了重點研究。首先,針對檢測系統(tǒng)采集到的圖像存在光照不均勻、噪聲干擾嚴(yán)重等問題,本文提出對其進行預(yù)處理,圖像去噪采用中值濾波處理,并將結(jié)果與均值濾波、高斯濾波效果比較,實驗結(jié)果表明中值濾波在去除噪聲點時可以取得較好效果。其次,對預(yù)處理后的圖像進行邊緣檢測和區(qū)域填充。本文將雙樹復(fù)小波變換和直方圖方向梯度計算相結(jié)合,提出一種基于雙樹復(fù)小波變換的路面裂縫檢測算法。該算法用雙樹復(fù)小波變換對路面裂縫圖像進行子帶分解,對各子帶圖像進行直方圖方向梯度矩陣計算,閾值化后確定裂縫邊緣。實驗結(jié)果表明,與傳統(tǒng)邊緣檢測算法相比,該算法目標(biāo)識別度高、抗干擾能力強及準(zhǔn)確率高。確定裂縫邊緣后進行區(qū)域填充處理,完全分割出裂縫區(qū)域。最后,對特征提取和分類識別進行了研究。本文對閾值化后的路面裂縫圖像進行特征提取,根據(jù)提取出的特征設(shè)計了支持向量機分類器,對路面圖像進行識別分類。通過多幅路面裂縫圖像實驗證明,該分類器可以有效地對路面裂縫圖像進行分類處理。
[Abstract]:With the rapid development of high-grade highway construction in China, more and more attention has been paid to the role of highway detection and maintenance in the national economic construction and the construction of people's livelihood. At present, the traditional manual detection can no longer meet the requirements of the rapid development of highway. Therefore, the research on automatic detection technology of pavement damage becomes more and more important. In recent years, with the rapid development of computer technology, pavement damage detection system based on computer vision has been applied in the field of highway damage detection and maintenance. This paper focuses on the hot spot and difficult point of pavement damage detection algorithm. Firstly, aiming at the problems of uneven illumination and serious noise interference in the image collected by the detection system, this paper proposes to pre-process the image denoising using median filter, and compares the result with the mean filter and Gao Si filtering effect. The experimental results show that the median filter can achieve better results in removing noise points. Secondly, the edge detection and region filling of the pre-processed image are carried out. In this paper, a pavement crack detection algorithm based on double-tree complex wavelet transform is proposed by combining double-tree complex wavelet transform with histogram direction gradient calculation. The algorithm uses the double-tree complex wavelet transform to decompose the pavement crack image, calculates the histogram direction gradient matrix of each sub-band image, and determines the crack edge after thresholding. The experimental results show that compared with the traditional edge detection algorithm, the proposed algorithm has the advantages of high target recognition, strong anti-jamming ability and high accuracy. After determining the edge of the fracture, the region filling is carried out, and the crack area is completely divided out. Finally, feature extraction and classification recognition are studied. This paper carries on the feature extraction to the thresholding pavement crack image, designs the support vector machine classifier according to the extracted feature, carries on the recognition and classification to the road surface image. Experiments on several pavement crack images show that the classifier can classify pavement crack images effectively.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U418.6;TP391.41

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本文編號：2451167