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標題: 失焦演算法於形貌量測之研究
Profilometry Using Depth from Defocus
作者: 蔡政育
Tsai, Cheng-Yu
關鍵字: Fourier transform
Wavelet coefficient
Wavelet function
power spectrum
border effect
point spread function
出版社: 機械工程學系所
引用: [1] Yangjie Wei, Zaili Dong, Lei Miao, and Wen J. Li, ''Analysis of Depth from Defocus Measurements for Micro-Imaging and 3D Micro-Visual Reconstruction'', IEEE International Conference on Information Acquisition, pp.326-331, 2005. [2] Ren Guoquan, Li Wenzhao, Chen Liang, Xiang Shuo, ''Application of Shape from Shading Algorithm in Wear Debris 3D Surface Shape Recovery'', International Conference on Measuring Technology and Mechatronics Automation, Vol.01, pp.586-589, 2010. [3] Chen Xiang-cheng, Yang Sheng and Wang Ya-jun, ''Research on 3D shape Reconstruction using Uneven Defocusing Model'', IEEE International Conference on Mechatronics and Automation, pp.2326-2331, 2007. [4] Subbarao M., ''Parallel Depth Recovery By Changing Camera Parameters'', Second International Conference on Computer Vision, pp.149-155, 1988. [5] Xiong Y., Shafer S.A, "depth from focusing and defocusing", Computer Society Conference on Computer Vision and Pattern Recognition, pp.68-73, 1993. [6] Ens J., Lawrence P., " An Investigation of Methods for Determining Depth from Focus", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.15, pp.97-108, 1993. [7] Pentland A., "A New Sense for Depth of Field", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.9, No.4, pp.523-531, 1987. [8] Subbarao M., Wei T. C., "Depth from Defocus and Rapid Autofocusing: a Practical Approach", IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.773-776, 1992. [9] Muhammad Asif, Aamir Saeed Malk and Tae-Sun Choi, "3D shape recovery from image defocus using wavelet analysis," IEEE International Conference on Image Processing, pp.1025-1028, 2005. [10] Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", Pearson Education Taiwan Ltd, 2008. [11] Raghuveer M. Rao, Ajit S. Bopardikar, "Wavelet transforms: introduction to theory and applications", Addison Wesley Longman, Inc, 1998. [12] C. Sidney Burrus, Ramesh A. Gopinath and Haitao Guo, "Introduction to Wavelets and Wavelet Transforms", Prentice Hall, Inc, 1998. [13] Kenneth R. Castleman, "Digital Image Processing", Prentice-Hall, Inc,1996 [14]王意如,小波轉換應用於光纖感測之研究,國立中山大學電機工程學系,碩士論文,2006 [15]黃國維,小波理論應用於模鑄型變壓器部份放電音頻信號之分析,國立成功大學電機工程研究所,碩士論文,2004
摘要: 本研究以失焦之模糊影像還原三維形貌輪廓,模糊影像可藉由三個攝影機參數調整得到,分別為焦距、光圈直徑、鏡頭中心與成像面距離,本實驗調整成像面距離獲得失焦影像,計算兩張不同失焦程度影像小波係數之功率頻譜差異還原三維形貌輪廓,功率頻譜差異大小與影像模糊程度有關係,物體表面的起伏會影響此差異值。 在演算法中會運用到小波函數,在頻率域上小波函數可以視為一個帶通濾波器,運用小波轉換的目的是減少計算傅立葉轉換時產生的邊界效應,聚焦影像經過點擴散函數模糊後可以產生失焦模糊影像,在頻率域中兩張影像功率頻譜差異會呈現指數衰減的形式,實驗結果顯示使用高放大倍率鏡頭且拍攝微小物體可以完整重建物體形貌輪廓。
In this paper, three dimension shape is recovered by blurring images, the blurring images can be adjusted by three camera parameters, namely focal length, aperture diameter, distance between the lens and the image detector plane, in this study, we get the defocusing images by adjusting the image detector plane, and then calculate the wavelet coefficient power spectrum of two different defocusing images recover three dimension shape, the relationship with differences in size of the power spectrum and the degree of blur, the fluctuation of surface will affect the value of this difference. The algorithm of this paper will use the wavelet function, wavelet function in the frequency domain can be regarded as a bandpass filter, the purpose of the use of wavelet transform is to reduce the calculation of Fourier transform producing the border effect, the focus image through the point spread function can produce the defocusing blur images, the power spectrum of two images in the frequency domain differences in the form of exponential decay, the experimental results show that using a high magnification lens and shooting a small object can be a complete reconstruction of the object morphology.
其他識別: U0005-2208201115313100
Appears in Collections:機械工程學系所



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