数字图像相关的多尺度图像子区匹配算法
|
摘要
数字图像相关(DIC)是一种测量固体表面位移和应变的非接触式光学实验方法,其关键步骤是基于图像子区的图像匹配算法,但是图像子区的选择仍然是一个难题,过大或过小的图像子区都会对测量精度不利,为此,本文提出一种基于多尺度图像子区匹配的算法,利用权重函数族调整图像子区内各个像素点对图像子区相关性的贡献,使图像子区的边界完全变得模糊,实现动态调整图像子区大小,更加合适大形变或不连续形变的表面.实验结果表明,本文方法能够得到令人满意的测量效果,模拟实验中测量位移的相对误差仅为1.6%和2.8%;真实实验进一步验证了本文方法在材料表面发生不连续形变时能够有效监测到位移和应变的变化.
Digital image correlation(DIC)is a kind of non-contact optical experiment approach for measuring displacement and strain of solid surface. The key step of DIC is the image matching algorithm based on subset. However, the selection of subset is still a difficult problem. Subset size has a significant influence on measurement accuracy. Therefore, multi-scale subset matching is proposed in this paper. A family of weight function is presented to adjust the contribution of the pixels in a subset via calculation correlation. The boundary of the subset becomes fuzzy and subset size is dynamic adjusted. It is more suitable for large or discontinuous deformed surface.The experimental results show that this method achieves satisfactory results. The relative errors of displacement measured in simulation experiments are only 1.6% and 2.8%. The real experiment further verifies that this method can effectively monitor the changes of displacement and strain when discontinuous deformation occurs on material surface.
Digital image correlation(DIC)is a kind of non-contact optical experiment approach for measuring displacement and strain of solid surface. The key step of DIC is the image matching algorithm based on subset. However, the selection of subset is still a difficult problem. Subset size has a significant influence on measurement accuracy. Therefore, multi-scale subset matching is proposed in this paper. A family of weight function is presented to adjust the contribution of the pixels in a subset via calculation correlation. The boundary of the subset becomes fuzzy and subset size is dynamic adjusted. It is more suitable for large or discontinuous deformed surface.The experimental results show that this method achieves satisfactory results. The relative errors of displacement measured in simulation experiments are only 1.6% and 2.8%. The real experiment further verifies that this method can effectively monitor the changes of displacement and strain when discontinuous deformation occurs on material surface.
引文
[1] PETERS W H,RANSON W F. Digital imaging technique in experimental stress analysis[J]. Optical Engineering,1982,21(3):427-431.
[2] PETERS W H,RANSON W F,SUTTON M A,et al. Application of digital correlation methods to rigid body mechanics[J]. Optical Engineering,1983,22(6):738-742.
[3] CHU T C,RANSON W F,SUTTON M A. Applications of digital-image-correlation techniques to experimental mechanics[J]. Experimental Mechanics,1985,25(3):232-244.
[4] SUTTON M,MINGQI C,PETERS W,et al. Application of an optimized digital correlation method to planar deformation analysis[J]. Image&Vision Computing,1986,4(3):143-150.
[5] SCHREIER,HUBERT W. Systematic errors in digital image correlation caused by intensity interpolation[J].Optical Engineering,2000,39(11):2915-2921.
[6] SCHREIER H W,SUTTON M A. Systematic errors in digital image correlation due to undermatched subset shape functions[J]. Experimental Mechanics,2002,42(3):303-310.
[7] CHENG P,SUTTON M A,SCHREIER H W,et al. Full-field speckle pattern image correlation with B-Spline deformation function[J]. Experimental Mechanics,2002,42(3):344-352.
[8] HE R S,HORN C T,WANG H J,et al. Deformation measurement by a digital image correlation method combined with a hybrid genetic algorithm[J]. Key Engineering Materials,2006,326/328:139-142.
[9] ZHANG Z F,KANG Y L,WANG H W,et al. A novel coarse-fine search scheme for digital image correlation method[J]. Measurement,2006,39(8):710-718.
[10] HOU Z D,QIN Y W. The study of fractal correlation method in the displacement measurement and its application[J]. Optics and Lasers in Engineering,2003,39(4):465-472.
[11] JIN H,BRUCK H A. Pointwise digital image correlation using genetic algorithms[J]. Experimental Techniques,2010,29(1):36-39.
[12] PAN B,XIE H M. Digital image correlation method with differential evolution[J]. Journal of Optoelectronics Laser,2007,18(1):100-103.
[13] PITTER M C,SEE C W,SOMEKH M G. Subpixel microscopic deformation analysis using correlation and artificial neural networks[J]. Optics Express,2001,8(6):322-327.
[14] CHEN T,QING Y H,ZHEN Y D,et al. A new synthetical algorithm for digital image correlation method and its application in the fracture[J]. Optical Technology,2003,29(1):69-72.
[15] SUN Y F,PANG J H L. Study of optimal subset size in digital image correlation of speckle pattern images[J]. Optics&Lasers in Engineering,2007,45(9):967-974.
[16] SUN Y,PANG J H L,WONG C K,et al. Finite element formulation for a digital image correlation method[J]. Appl Opt,2005,44(34):7357-7363.
[17] ZHANG J,JIN G,MA S,et al. Application of an improved subpixel registration algorithm on digital speckle correlation measurement[J]. Optics&Laser Technology,2003,35(7):533-542.
[18] PAN B,XIE H,GUO Z,et al. Full-field strain measurement using a two-dimensional Savitzky-Golay digital differentiator in digital image correlation[J]. Optical Engineering,2007,46(3):033601.
[19] PAN B,HUIMIN X,BOQIN X,et al. Performance of sub-pixel registration algorithms in digital image correlation[J]. Measurement Science&Technology,2006,17(6):1615-1621.
[20] MELLO A W,BOOK T A,NICOLAS A,et al. Distortion correction protocol for digital image correlation after scanning electron microscopy:emphasis on long duration and ex-situ experiments[J].Experimental Mechanics,2017,57(9):1395-1409.
[21] JIN P,LI X D. Correction of image drift and distortion in a scanning electron microscopy[J]. Journal of Microscopy. 2015,260(3):268-280.
[22] PAN B. Reliability-guided digital image correlation for image deformation measurement[J]. Applied Optics,2009,48(8):1535-1542.
[23] PAN B,DAFANG W,YONG X. Incremental calculation for large deformation measurement using reliability-guided digital image correlation[J]. Optics And Lasers In Engineering, 2012, 50(4):586-592.
[24] GUO X,LI Y,SUO T,et al. De-noising of digital image correlation based on stationary wavelet transform[J]. Optics&Lasers in Engineering,2017,90:161-172.
[25] PAN B,LI K. A fast digital image correlation method for deformation measurement[J]. Optics and Lasers in Engineering,2011,49(7):841-847.
[26] PAN B,LI K,TONG W. Fast,robust and accurate digital image correlation calculation without redundant computations[J]. Experimental Mechanics,2013,53(7):1277-1289.
[27] PAN B,TIAN L. Superfast robust digital image correlation analysis with parallel computing[J]. Optical Engineering,2015,54(3):034106.
[28] PAN B,WANG B. Digital image correlation with enhanced accuracy and efficiency:a comparison of two subpixel registration algorithms[J]. Experimental Mechanics,2016,56(8):1395-1409.
[29] HUANG J W, ZHANG L Q, JIANG Z Y, et al. Heterogeneous parallel computing accelerated iterative subpixel digital image correlation[J]. Science China Technological Sciences, 2018, 61(1):74-85.
[30] PAN B,XIE HM,WANG ZY,et al. Study of subset size selection in digital image correlation for speckle patterns[J]. Optics Express,2008,16(10):7037-7048.
[31] HASSAN G M,MACNISH C,DYSKIN A,et al. Digital image correlation with dynamic subset selection[J]. Optics&Lasers in Engineering,2016,84:1-9.
[32] LIANG Z,YIN B,MO J,et al. A new method to deal with the effect of subset size for digital image correlation[J]. Optik-International Journal for Light and Electron Optics,2015,126(24):4940-4945.
[33] BLABER J,ADAIR B,ANTONIOU A. Ncorr:Open-Source 2D Digital Image Correlation Matlab Software[J].Experimental Mechanics,2015,55(6):1105-1122.
[34] CAND魬SE,DONOHO D. Curvelets:A surprisingly effective nonadaptive representation of objects with edges[M]. Nashville:Vanderbilt University Press,1999.
[35] Donoho D L. Wedgelets:nearly minimax estimation of edges[J]. The Annals of Statistics,1999,27(3):859-897.
[36] PENNEC E L,MALLAT S. Sparse geometric image representations with bandelets[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2005,14(4):423-438.
[37] MALLAT S. Geometrical grouplets[J]. Applied&Computational Harmonic Analysis,2009,26(2):161-180.
[38] LIN Z,YAN J,YUAN Y. Algorithm for image fusion based on orthogonal grouplet transform and pulse-coupled neural network[J]. Journal of Electronic Imaging,2013,22(3):033028.
[39] DONOHO D L,HUO X. Beamlets and Multiscale Image Analysis[J]. Multiscale&Multiresolution Methods,2001,20:149-196.
[40] LIN Z,YAN J,YUAN Y. Target detection for SAR images based on beamlet transform[J]. Multimedia Tools and Applications,2016,75(4):2189-2202.
[2] PETERS W H,RANSON W F,SUTTON M A,et al. Application of digital correlation methods to rigid body mechanics[J]. Optical Engineering,1983,22(6):738-742.
[3] CHU T C,RANSON W F,SUTTON M A. Applications of digital-image-correlation techniques to experimental mechanics[J]. Experimental Mechanics,1985,25(3):232-244.
[4] SUTTON M,MINGQI C,PETERS W,et al. Application of an optimized digital correlation method to planar deformation analysis[J]. Image&Vision Computing,1986,4(3):143-150.
[5] SCHREIER,HUBERT W. Systematic errors in digital image correlation caused by intensity interpolation[J].Optical Engineering,2000,39(11):2915-2921.
[6] SCHREIER H W,SUTTON M A. Systematic errors in digital image correlation due to undermatched subset shape functions[J]. Experimental Mechanics,2002,42(3):303-310.
[7] CHENG P,SUTTON M A,SCHREIER H W,et al. Full-field speckle pattern image correlation with B-Spline deformation function[J]. Experimental Mechanics,2002,42(3):344-352.
[8] HE R S,HORN C T,WANG H J,et al. Deformation measurement by a digital image correlation method combined with a hybrid genetic algorithm[J]. Key Engineering Materials,2006,326/328:139-142.
[9] ZHANG Z F,KANG Y L,WANG H W,et al. A novel coarse-fine search scheme for digital image correlation method[J]. Measurement,2006,39(8):710-718.
[10] HOU Z D,QIN Y W. The study of fractal correlation method in the displacement measurement and its application[J]. Optics and Lasers in Engineering,2003,39(4):465-472.
[11] JIN H,BRUCK H A. Pointwise digital image correlation using genetic algorithms[J]. Experimental Techniques,2010,29(1):36-39.
[12] PAN B,XIE H M. Digital image correlation method with differential evolution[J]. Journal of Optoelectronics Laser,2007,18(1):100-103.
[13] PITTER M C,SEE C W,SOMEKH M G. Subpixel microscopic deformation analysis using correlation and artificial neural networks[J]. Optics Express,2001,8(6):322-327.
[14] CHEN T,QING Y H,ZHEN Y D,et al. A new synthetical algorithm for digital image correlation method and its application in the fracture[J]. Optical Technology,2003,29(1):69-72.
[15] SUN Y F,PANG J H L. Study of optimal subset size in digital image correlation of speckle pattern images[J]. Optics&Lasers in Engineering,2007,45(9):967-974.
[16] SUN Y,PANG J H L,WONG C K,et al. Finite element formulation for a digital image correlation method[J]. Appl Opt,2005,44(34):7357-7363.
[17] ZHANG J,JIN G,MA S,et al. Application of an improved subpixel registration algorithm on digital speckle correlation measurement[J]. Optics&Laser Technology,2003,35(7):533-542.
[18] PAN B,XIE H,GUO Z,et al. Full-field strain measurement using a two-dimensional Savitzky-Golay digital differentiator in digital image correlation[J]. Optical Engineering,2007,46(3):033601.
[19] PAN B,HUIMIN X,BOQIN X,et al. Performance of sub-pixel registration algorithms in digital image correlation[J]. Measurement Science&Technology,2006,17(6):1615-1621.
[20] MELLO A W,BOOK T A,NICOLAS A,et al. Distortion correction protocol for digital image correlation after scanning electron microscopy:emphasis on long duration and ex-situ experiments[J].Experimental Mechanics,2017,57(9):1395-1409.
[21] JIN P,LI X D. Correction of image drift and distortion in a scanning electron microscopy[J]. Journal of Microscopy. 2015,260(3):268-280.
[22] PAN B. Reliability-guided digital image correlation for image deformation measurement[J]. Applied Optics,2009,48(8):1535-1542.
[23] PAN B,DAFANG W,YONG X. Incremental calculation for large deformation measurement using reliability-guided digital image correlation[J]. Optics And Lasers In Engineering, 2012, 50(4):586-592.
[24] GUO X,LI Y,SUO T,et al. De-noising of digital image correlation based on stationary wavelet transform[J]. Optics&Lasers in Engineering,2017,90:161-172.
[25] PAN B,LI K. A fast digital image correlation method for deformation measurement[J]. Optics and Lasers in Engineering,2011,49(7):841-847.
[26] PAN B,LI K,TONG W. Fast,robust and accurate digital image correlation calculation without redundant computations[J]. Experimental Mechanics,2013,53(7):1277-1289.
[27] PAN B,TIAN L. Superfast robust digital image correlation analysis with parallel computing[J]. Optical Engineering,2015,54(3):034106.
[28] PAN B,WANG B. Digital image correlation with enhanced accuracy and efficiency:a comparison of two subpixel registration algorithms[J]. Experimental Mechanics,2016,56(8):1395-1409.
[29] HUANG J W, ZHANG L Q, JIANG Z Y, et al. Heterogeneous parallel computing accelerated iterative subpixel digital image correlation[J]. Science China Technological Sciences, 2018, 61(1):74-85.
[30] PAN B,XIE HM,WANG ZY,et al. Study of subset size selection in digital image correlation for speckle patterns[J]. Optics Express,2008,16(10):7037-7048.
[31] HASSAN G M,MACNISH C,DYSKIN A,et al. Digital image correlation with dynamic subset selection[J]. Optics&Lasers in Engineering,2016,84:1-9.
[32] LIANG Z,YIN B,MO J,et al. A new method to deal with the effect of subset size for digital image correlation[J]. Optik-International Journal for Light and Electron Optics,2015,126(24):4940-4945.
[33] BLABER J,ADAIR B,ANTONIOU A. Ncorr:Open-Source 2D Digital Image Correlation Matlab Software[J].Experimental Mechanics,2015,55(6):1105-1122.
[34] CAND魬SE,DONOHO D. Curvelets:A surprisingly effective nonadaptive representation of objects with edges[M]. Nashville:Vanderbilt University Press,1999.
[35] Donoho D L. Wedgelets:nearly minimax estimation of edges[J]. The Annals of Statistics,1999,27(3):859-897.
[36] PENNEC E L,MALLAT S. Sparse geometric image representations with bandelets[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2005,14(4):423-438.
[37] MALLAT S. Geometrical grouplets[J]. Applied&Computational Harmonic Analysis,2009,26(2):161-180.
[38] LIN Z,YAN J,YUAN Y. Algorithm for image fusion based on orthogonal grouplet transform and pulse-coupled neural network[J]. Journal of Electronic Imaging,2013,22(3):033028.
[39] DONOHO D L,HUO X. Beamlets and Multiscale Image Analysis[J]. Multiscale&Multiresolution Methods,2001,20:149-196.
[40] LIN Z,YAN J,YUAN Y. Target detection for SAR images based on beamlet transform[J]. Multimedia Tools and Applications,2016,75(4):2189-2202.