發(fā)布時間：2018-12-21 21:35

【摘要】：在一幅圖像當(dāng)中,圖像的線特征(包括直線、曲線)往往組成了物體的輪廓,如果能夠有效地將這些特征提取出來,則對于圖像處理在目標(biāo)匹配、目標(biāo)識別、機器人視覺、數(shù)據(jù)挖掘等領(lǐng)域的應(yīng)用具有重要意義。本文針對數(shù)字圖像中存在不同特點的線特征提取進行了算法研究,主要研究內(nèi)容包括:首先,針對圖像中存在具有非平滑邊緣的曲線特征(圓或橢圓)的情況進行了特征提取算法的研究,提出一種基于多尺度邊緣提取的圓及橢圓檢測算法,逐一檢測利用高斯金字塔所得到的不同尺度圖像,以此提高曲線特征的檢測率,并將該算法應(yīng)用于天體表面隕石坑圖像的檢測,并且檢測率可以達到85%以上,最后將該算法與Fornaciari等人提出的算法(Forn算法)進行檢測結(jié)果比較,結(jié)果表明,與Forn算法相比,檢測率提高40%,檢測時間提高50%以上。然后,針對圖像中存在多種線特征并存的情況,研究了一種基于ELSD的直線與橢圓提取算法。首先利用區(qū)域生長以及曲線生長的方法分別對直線段和橢圓弧段進行檢測,通過分析橢圓弧段的位置信息和切線方向信息進行最小二乘算法的橢圓擬合,并利用計算誤報率來剔除擬合出來的無效橢圓。應(yīng)用該算法對道路交通標(biāo)志圖像進行檢測,實驗結(jié)果表明,該算法不僅能夠?qū)Υ嬖诙喾N線特征的交通標(biāo)志圖像有較好的檢測結(jié)果,且檢測快速。最后,針對基于ARM平臺的圓(橢圓)檢測系統(tǒng)進行了設(shè)計和研究。通過對硬件部分和軟件部分的設(shè)計實現(xiàn)該系統(tǒng)的整體搭建。在硬件部分中,以i.MX6DL處理器為核心,并結(jié)合一系列外圍接口;軟件部分則利用OpenCV(跨平臺計算機視覺庫)以及QT等軟件資源來實現(xiàn)嵌入式系統(tǒng)下的圖像的處理及顯示。最后將交通標(biāo)志檢測程序移植到該系統(tǒng)中,實現(xiàn)了基于ARM平臺的交通標(biāo)志檢測。
[Abstract]:In an image, the line features (including lines, curves) of an image often form the contour of an object. If these features can be effectively extracted, then for image processing in object matching, target recognition, robot vision, The application of data mining and other fields is of great significance. In this paper, the algorithm of line feature extraction with different characteristics in digital image is studied. The main research contents are as follows: first of all, In this paper, the feature extraction algorithm is studied for the existence of curve features (circles or ellipses) with non-smooth edges, and a multi-scale edge detection algorithm based on circle and ellipse is proposed. In order to improve the detection rate of curve features, the algorithm is applied to the detection of crater images on the surface of celestial bodies one by using the different scale images obtained from Gao Si's pyramids, and the detection rate can reach more than 85%. Finally, the detection results of this algorithm are compared with the Forn algorithm proposed by Fornaciari et al. The results show that compared with the Forn algorithm, the detection rate is increased by 40% and the detection time is increased by more than 50%. Then, an algorithm of line and ellipse extraction based on ELSD is proposed. Firstly, the linear segment and the elliptical arc segment are detected by the method of region growth and curve growth, and the elliptical fitting of the elliptical arc segment and tangent direction information is carried out by analyzing the position information of the elliptic arc segment and the tangent direction information. The invalid ellipse is eliminated by calculating false alarm rate. The experimental results show that the algorithm can not only detect the traffic sign images with multiple line features, but also can detect the traffic signs quickly. Finally, the circle (ellipse) detection system based on ARM platform is designed and studied. The whole system is built by the design of hardware and software. In the hardware part, the i.MX6DL processor is used as the core and a series of peripheral interfaces are combined, while the software part uses the software resources such as OpenCV (cross-platform computer vision library) and QT to realize the image processing and display in the embedded system. Finally, the traffic sign detection program is transplanted into the system, and the traffic sign detection based on ARM platform is realized.
【學(xué)位授予單位】：青島科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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