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研究生:李友群
研究生(外文):You-Cyun Li
論文名稱:基於最小能量函數於空間域進行估算位移場
論文名稱(外文):Estimation Displacement Field in Spatial Domain Based on Minimizing Energy Function
指導教授:李吉群
口試委員:蔡東憲何昭慶
口試日期:2017-07-20
學位類別:碩士
校院名稱:國立中興大學
系所名稱:機械工程學系所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:66
中文關鍵詞:Morph仿射轉換重映射斑點檢測結構相似性
外文關鍵詞:MorphAffine TransformationRemapBlobs DetectionSSIM
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數位影像處理量測是一種非接觸、非破壞性的光學量測方法。
本文藉由擷取表面貼附網格之物體受力變形後的影像,並經由一系列的處理,將物體還原至未變形之型態。首先使用斑點檢測找出斑點響應最高之網格作為初始還原點,並使用Canny邊緣檢測來減少數據量。對於初始還原點來說,由仿射轉換求得的仿射轉換矩陣作為初始變形量。對於其他網格點,使用圖像變形(Image Morph)之概念,藉由隨機給每個區塊還原方向,計算此還原方向的圖像,並與標準圖像計算圖像結構相似性(SSIM),相似性最高的還原量作為圖像的還原方向梯度,沿著方向梯度逐步迭代出圖像相似性最高之變形量,每個區塊依此方式重複執行。
本文使用的圖像相似性應用上忽略了亮度相似性,只計算對比度相似性以及結構相似性,以排除擷取圖像時,圖像亮度影響結果的因素。每個變形量的嘗試皆會使用重映射來產生該區塊的圖像來比較相似性,取得相似性最高的變形量後,將此變形量產生的區塊貼至對應位置,當每個區塊皆計算完成後,將會得到一物體變形前的圖像。

關鍵字:Morph、仿射轉換、重映射、斑點檢測、結構相似性
Digital image processing measurement is a non-contact and non-destructive optical measuring method.
In this paper, capture the image of object attached to the grid after deformation, and then the object will be restored to the undeformed shape through a series of image processing .The first is to using the blobs detection to find the grid of highest response as the initial restoration point, and using the Canny edge detection to decrease the amount of data. For the initial restoration point, The affine transformation matrix obtained by affine transformation is used as the initial deformation amount. In other grid points, using the concept of image morph to calculate the image of the restoration direction by randomly giving each block a restoration direction, and compare with the standard image to calculate the image structure similarity (SSIM). The restoration amount of the highest similarity is regarded as the restoration direction of the image,and then gradually iterate along the gradient of direction to obtain the highest deformation of the image similarity.
The image similarity used in this paper ignores the similarity of illumination, and only calculates the contrast similarity and the structural similarity to eliminate the factors that image illumination affects the result when the image is captured. Each deformation choosing will use remapping to produce the image of the block to compare the similarity, After obtaining the highest deformation, the blocks generated by this deformation are attached to the corresponding positions.When each block is calculated, it will get an image before the object is deformed.
Keywords:Morph、Affine Transformation、Remap、Blobs Detection、SSIM
摘要 i
Abstract ii
目錄 iv
圖目錄 vi
一、緒論 1
1-1前言 1
1-2研究目的 2
1-3文獻回顧 3
1-4論文架構 6
二、理論基礎 7
2-1中值濾波 7
2-2 形態學處理 8
2-2-1侵蝕 9
2-2-2擴張 10
2-2-3斷開 11
2-2-4閉合 12
2-3斑點檢測 13
2-3-1 Blobs Detection 14
2-3-2尺度不變特徵轉換 17
2-4 Canny邊緣檢測 20
2-5 仿射轉換 24
2-6 影像變形(Image Morph) 25
2-6-1 Morph運作 26
2-6-2能量函數 28
2-7影像內插 31
2-7-1最鄰近點內插 32
2-7-2雙線性內插 33
2-7-3雙立方內插 34
三、實驗程序 37
3-1計算程序 37
3-2初始變形量預測 42
3-3計算相似性優化 45
3-4限制最大變形量 46
四、實驗結果及討論 48
4-1實驗架構 48
4-2實驗結果與討論 49
4-3誤差分析 60
4-4雜訊影響 62
五、結論及未來展望 64
六、參考文獻 65
[1]Peters, W. H., and W. F. Ranson. "Digital imaging techniques in experimental stress analysis."Optical engineering 21.3 (1982): 213427-213427.
[2]Lowe, David G. "Object recognition from local scale-invariant features."Computer vision, 1999. The proceedings of the seventh IEEE international conference on. Vol. 2. IEEE, 1999.
[3]Bay, Herbert, Tinne Tuytelaars, and Luc Van Gool. "Surf: Speeded up robust features." European conference on computer vision. Springer Berlin Heidelberg, 2006.
[4]Panchal, P. M., S. R. Panchal, and S. K. Shah. "A comparison of SIFT and SURF." International Journal of Innovative Research in Computer and Communication Engineering 1.2 (2013): 323-327.
[5]Hazewinkel, Michiel, ed, "Affine transformation", Encyclopedia of Mathematics, Springer, ISBN 978-1-55608-010-4, (2001)
[6]Canny, John. "A computational approach to edge detection." IEEE Transactions on pattern analysis and machine intelligence 6 (1986): 679-698.
[7]Mokhtarian, Farzin, and Riku Suomela. "Robust image corner detection through curvature scale space." IEEE Transactions on Pattern Analysis and Machine Intelligence 20.12 (1998): 1376-1381.
[8]Wang, Zhou, et al. "Image quality assessment: from error visibility to structural similarity." IEEE transactions on image processing 13.4 (2004): 600-612.
[9]Gao, Qingji, Ping Xu, and Wang Man. "Breakage detection for grid images based on improved Harris corner." Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on. IEEE, 2011.
[10]Ye Yongmao, et al. "On linear and nonlinear processing of underwater, ground, aerial and satellite images." 2005 IEEE International Conference on Systems, Man and Cybernetics. Vol. 4. IEEE, 2005.
[11]Li Wei, Zelin Shi, and Jian Yin. "A Fully Affine Invariant Feature Detector."Pattern Recognition (ICPR), 2012 21st International Conference on. IEEE, 2012.
[12]Chen-Hsuan Chiu. " Application of Fourier Transform Phase Retrieval and Geometric Image Transformations in Deformation Measurement " ,2016.
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