發(fā)布時間：2018-06-29 21:58

  本文選題：移動測量系統(tǒng) + 特征提取��； 參考：《北京建筑大學(xué)》2013年碩士論文

【摘要】：近些年來，移動測量系統(tǒng)在各個行業(yè)中得到了廣泛應(yīng)用，獲得了很好的實踐成果，促進了社會的進步發(fā)展。由于移動測量系統(tǒng)可以采集大量的可量測實景影像數(shù)據(jù)，廣泛應(yīng)用到影像瀏覽，以及后期提取影像中地物的空間位置信息及屬性信息中，因此影像數(shù)據(jù)顯得越來越重要，受到人們的重視。 本文研究所使用的移動測量系統(tǒng)外業(yè)采集的影像數(shù)據(jù)，由于相機的視場角較小，拍攝的影像不能滿足項目的需要（寬幅影像）。從這個問題出發(fā)，本文研究適合移動測量系統(tǒng)的影像拼接算法。在移動測量系統(tǒng)中，相機拍攝的影像之間都有一定的重疊度，而且這個重疊度基本上是固定的，因此，本文將移動測量系統(tǒng)的影像特點作為限制條件，改進SIFT匹配算法，制作寬幅影像。另外，移動測量系統(tǒng)拍攝影像數(shù)量巨大，而且影像有固定的命名及存儲格式，因此，本文給出了開發(fā)適合移動測量系統(tǒng)的影像自動拼接的系統(tǒng)構(gòu)思。 本文對移動測量系統(tǒng)拍攝影像的特點進行了全面的分析，提取移動測量系統(tǒng)的獨特特征數(shù)據(jù)，比如相機的固定位置及角度關(guān)系，影像間的位置及旋轉(zhuǎn)關(guān)系,影像的重疊度等等，改進SIFT的特征提取算法以及特征匹配算法，研究適合移動測量系統(tǒng)影像數(shù)據(jù)的拼接算法。 本文選用在不同級別的道路上拍攝的影像做統(tǒng)計實驗。首先，本文通過對影像進行模型分析以及統(tǒng)計實驗，獲取兩個相機拍攝影像的重疊度數(shù)據(jù)，根據(jù)獲取的重疊度數(shù)據(jù)制定相應(yīng)的閾值，踢除不符合要求的特征點數(shù)據(jù)。其次，通過影像統(tǒng)計實驗，確定特征點匹配的搜索區(qū)域H。以正前相機拍攝的影像為標(biāo)準(zhǔn)影像，左前跟右前相機拍攝的影像為待拼接影像，通過人工判讀的方法，提取影像的同名特征點，分析同名特征點數(shù)據(jù)，獲取與標(biāo)準(zhǔn)影像特征點匹配的待配準(zhǔn)影像特征點的大致區(qū)域，制定特征點匹配的搜索區(qū)域H。在待配準(zhǔn)影像中，以H的矩形搜索區(qū)域為搜索范圍，運用歐式距離匹配影像特征點。這樣不僅提高算法的運算速度，而且還有效減少偽匹配特征點的數(shù)量。最后，通過最小二乘原理，隨機選取一定數(shù)量的特征點建立轉(zhuǎn)換模型，剩余的特征點作為檢核點，檢驗轉(zhuǎn)換模型的可靠性，獲取可靠性最高的轉(zhuǎn)換模型。 通過本文的研究，提高了算法的運算速度，成功降低特征點偽匹配概率，獲取了可信度最高的同名特征點，建立了影像拼接模型。本論文改進的匹配算法，適合移動測量系統(tǒng)，而且在此算法基礎(chǔ)上開發(fā)的影像自動拼接系統(tǒng)，，為街景影像的后期發(fā)布提供便利，對整個移動測量系統(tǒng)功能的完善和改進起到了積極的推動作用。
[Abstract]:In recent years, mobile measurement system has been widely used in various industries, obtained good practical results, and promoted the development of society. Because the mobile measurement system can collect a large number of measurable real scene image data, it is widely used in image browsing, as well as the spatial position information and attribute information of the object in the image, so the image data becomes more and more important. Be valued by people. In this paper, the image data collected from the field of view of the mobile measurement system are studied. Because of the small field of view angle of the camera, the image can not meet the needs of the project (wide range image). From this point of view, this paper studies the image stitching algorithm suitable for mobile measurement system. In the mobile measurement system, there is a certain degree of overlap between the images taken by the camera, and the overlap degree is basically fixed. Therefore, this paper takes the image characteristics of the mobile measurement system as the limiting condition, and improves the sift matching algorithm. Make wide images. In addition, the number of images taken by the mobile measurement system is huge, and the images have a fixed naming and storage format. This paper makes a comprehensive analysis of the characteristics of the image taken by the mobile measurement system, extracts the unique characteristic data of the mobile measurement system, such as the fixed position and angle relation of the camera, the position and rotation relationship between the images, the overlap degree of the image, etc. Improved sift feature extraction algorithm and feature matching algorithm, research suitable for mobile measurement system image data splicing algorithm. In this paper, we choose the images taken on different levels of roads to do statistical experiments. Firstly, through the model analysis and statistical experiment of the image, the overlap degree data of the two cameras are obtained, the corresponding threshold is set according to the overlap degree data obtained, and the feature point data that does not meet the requirements is kicked out. Secondly, the search region of feature point matching is determined by image statistical experiment. Taking the image taken by the front camera as the standard image and the image taken by the left front camera and the right front camera as the image to be stitched together, the feature points of the same name of the image are extracted by manual interpretation, and the data of the same name feature point are analyzed. The approximate region of the feature points to be matched with the standard image feature points is obtained, and the search region of the feature points matching is established. In the image registration, the rectangular search area of H is used as the search range and the Euclidean distance is used to match the feature points of the image. This not only improves the speed of the algorithm, but also effectively reduces the number of pseudo-matching feature points. Finally, through the least square principle, a certain number of feature points are randomly selected to establish the transformation model, and the remaining feature points are used as check points to test the reliability of the transformation model and obtain the most reliable transformation model. Through the research in this paper, the algorithm speed is improved, the probability of pseudo-matching of feature points is reduced successfully, the feature points of the same name with the highest credibility are obtained, and the image mosaic model is established. The improved matching algorithm in this paper is suitable for the mobile measurement system, and the automatic image mosaic system based on this algorithm provides convenience for the later release of the street view image. It plays a positive role in improving the function of the whole mobile measurement system.
【學(xué)位授予單位】：北京建筑大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P235.2

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本文編號：2083504