Digital image correlation for large deformation applied in Ti alloy compression and tension test

In this paper, digital speckle correlation is used in the measurement of Ti alloy compression and tension test. The key technologies applied in the measurement are discussed in detail, including camera calibration with telephoto lens and digital image correlation in large deformation. Single camera self-calibration algorithm based on photogrammetry is proposed. In the algorithm, the interior parameters of camera are estimated without calibrated object, using the bundle adjustment technique, so the 3-D coordinates of calibration target points are not needed in advance to get a reliable camera calibration result. An updating reference image scheme could be employed to deal with large deformation situation. A large deformation measurement scheme, updating reference image scheme, is proposed in this paper. The un-deformed image is used as reference in correlation at first. Only for extremely large deformation field, in which iteration of correlation is not convergent, the reference image is updated to the image of previous deformed stage. Using this method, not only extremely large deformation can be measured successfully but also the accumulated error could be controlled. The 75 mm lens is calibrated in the measurement and compared the result with extensometer and un-calibrated image. Experimental results show that up to 150% tensile deformation and 50% compression deformation can be measured successfully.     

Incremental calculation for large deformation measurement using reliability-guided digital image correlation

Conventional digital image correlation (DIC) technique using a fixed reference image provides high-accuracy measurements but normally fails when serious decorrelation effect occurs in the deformed images due to large deformation, serious illumination fluctuations or other reasons. In this paper, an incremental reliability-guided digital image correlation (RG-DIC) technique, by combining the recently developed RG-DIC technique and an automatic reference image updating scheme, is proposed for large deformation measurement. In the incremental RG-DIC technique, a seed point is defined in the original reference image and searched in the deformed images, if the estimated correlation coefficient is larger than a preset threshold, which means no serious decorrelation effect exists in the deformed image, the RG-DIC technique is used to continue correlation analysis to obtain full-field displacements. Otherwise, the image recorded just before the current deformed image is chosen as an updated reference image to proceed with correlation analysis. Afterwards, the incremental displacements extracted by comparing the current deformed image and the updated reference image can be cumulated to determine the overall deformation. The effectiveness of the proposed technique is demonstrated by retrieving the full-field deformation of a foam sample subjected to large compressive deformation.     

数字图像相关中基于位移场局部最小二乘拟合的全场应变测量

为了从含噪声的位移场中计算得到可靠的应变场,提出一种基于位移场局部最小二乘拟合的全场应变求解方法。介绍了数字图像相关方法的原理,阐述了基于位移场局部最小二乘拟合的全场应变求解方法,并讨论了计算区域边界、孔洞及裂纹附近区域等情况下的应变计算。对均匀变形和中心带圆孔的薄铝板拉伸实验的计算结果表明,该方法能有效地从原始位移场数据中提取全场应变信息。在均匀变形情况下应选择大的应变计算窗口,计算结果更逼近真值;在非均匀变形情况下,如果位移场中包含较强的噪声,则应选择较大的应变计算窗口,而位移场精度很高时可选择更小的应变计算窗口。     

噪声对数字图像相关法计算结果的影响研究

不同的散斑场会显示出不同的灰度分布特征,并对数字图像相关方法的计算结果有着重要影响。使用计算机模拟生成一系列单向拉伸图像和双向拉伸图像,并在生成的图像中添加噪声,从而获得一系列含噪声单向拉伸图像和含噪声双向拉伸图像。使用数字图像相关方法对无噪声图像和含噪声图像分别进行相关计算,并分析研究图像应变量与相关计算结果正确率间的关系,研究结果表明发现当图像的应变量在一定范围内时,数字图像相关方法计算结果的正确率较高。同时发现,当图像的应变量较小时,噪声对相关计算结果的影响较大,随着图像应变量的增大,噪声对相关计算结果的影响逐渐减小,当图像的应变量到达一定程度时,噪声对相关计算的影响就不明显了。     

Single-step scanner-based digital image correlation (SB-DIC) method for large deformation mapping in rubber

The incremental digital image correlation (DIC) method has been applied in the past to determine strain in large deformation materials like rubber. This method is, however, prone to cumulative errors since the total displacement is determined by combining the displacements in numerous stages of the deformation. In this work, a method of mapping large strains in rubber using DIC in a single-step without the need for a series of deformation images is proposed. The reference subsets were deformed using deformation factors obtained from the fitted mean stress-axial stretch ratio curve obtained experimentally and the theoretical Poisson function. The deformed reference subsets were then correlated with the deformed image after loading. The recently developed scanner-based digital image correlation (SB-DIC) method was applied on dumbbell rubber specimens to obtain the in-plane displacement fields up to 350% axial strain. Comparison of the mean axial strains determined from the single-step SB-DIC method with those from the incremental SB-DIC method showed an average difference of 4.7%. Two rectangular rubber specimens containing circular and square holes were deformed and analysed using the proposed method. The resultant strain maps from the single-step SB-DIC method were compared with the results of finite element modeling (FEM). The comparison shows that the proposed single-step SB-DIC method can be used to map the strain distribution accurately in large deformation materials like rubber at much shorter time compared to the incremental DIC method.     

An improved fast fractal image compression using spatial texture correlation

This paper utilizes a spatial texture correlation and the intelligent classification algorithm (ICA) search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.     

A fast digital image correlation method for deformation measurement

Fast and high-accuracy deformation analysis using digital image correlation (DIC) has been increasingly important and highly demanded in recent years. In literature, the DIC method using the Newton-Rapshon (NR) algorithm has been considered as a gold standard for accurate sub-pixel displacement tracking, as it is insensitive to the relative deformation and rotation of the target subset and thus provides highest sub-pixel registration accuracy and widest applicability. A significant drawback of conventional NR-algorithm-based DIC method, however, is its extremely huge computational expense. In this paper, a fast DIC method is proposed deformation measurement by effectively eliminating the repeating redundant calculations involved in the conventional NR-algorithm-based DIC method. Specifically, a reliability-guided displacement scanning strategy is employed to avoid time-consuming integer-pixel displacement searching for each calculation point, and a pre-computed global interpolation coefficient look-up table is utilized to entirely eliminate repetitive interpolation calculation at sub-pixel locations. With these two approaches, the proposed fast DIC method substantially increases the calculation efficiency of the traditional NR-algorithm-based DIC method. The performance of proposed fast DIC method is carefully tested on real experimental images using various calculation parameters. Results reveal that the computational speed of the present fast DIC is about 120-200 times faster than that of the traditional method, without any loss of its measurement accuracy     

一种保持非负整数值的图像加密算法

提出了一种能够使双随机相位图像加密方法的密文图像保持为非负整数值的变换——重构变换.重构变换包括预处理和频谱搬移两个过程,其主要特点为,在图像进行频域变换之前,通过叠加的方式将整数图像压缩成一半大小的复数图像,从而能缩小后续运算的计算空间;基于重构变换的双随机相位图像加密方法可以实现联合图像压缩和加密的效果.与基于混沌系统的数字图像加密方法相比,本文方法的密文图像具有更低的信息熵.实验结果表明,该方法具有较强的安全性,解密图像基本无失真,并且密文图像对加性噪音攻击具有一定的鲁棒性.     

一种保持非负整数值的图像加密算法

提出了一种能够使双随机相位图像加密方法的密文图像保持为非负整数值的变换——重构变换.重构变换包括预处理和频谱搬移两个过程,其主要特点为,在图像进行频域变换之前,通过叠加的方式将整数图像压缩成一半大小的复数图像,从而能缩小后续运算的计算空间;基于重构变换的双随机相位图像加密方法可以实现联合图像压缩和加密的效果.与基于混沌系统的数字图像加密方法相比,本文方法的密文图像具有更低的信息熵.实验结果表明,该方法具有较强的安全性,解密图像基本无失真,并且密文图像对加性噪音攻击具有一定的鲁棒性.     

大孔径静态干涉光谱仪图像压缩技术

从图像压缩的角度分析了大孔径静态干涉成像光谱仪成像原理，并提出了一种新的遥感多光谱图像压缩方案。新方案利用大孔径静态干涉成像光谱仪推扫成像特点提出了一种低存储量，帧间小波域匹配的图像序列压缩方法，提高图像质量3～4dB。为了保证图像的光谱信息在8倍压缩比下有效应用，系统采用了一种新的感兴趣区域(ROD编码技术。感兴趣区域编码时，由于方案中采用率失真优化斜率提升，而不是比特平面移位，从而使图像在相同的光谱分辨率下拥有更好的空间分辨率。实验结果表明，算法大大保护了图像的光谱特性，在8倍压缩比下，满足了该类干涉多光谱遥感图像的质量要求。     

矿山多源遥感图像像点位移测试系统设计

针对矿山地形的起伏变化影响对其进行分析研究的准确性,提出矿上多源遥感图像像点位移测试系统的设计方法。结合GPS定位原理,选取遥感图像上某一时刻点作为测试点,对拍摄得到的矿山图像和电子测试系统各触点之间的距离进行计算,进而得到测试点具体坐标位置,将其与测试点真实现场坐标相对比,实现矿山多源遥感图像像点位移的测试。通过实验证明,所设计的测试系统可以高精度实现对遥感图像像点位移的测试,有效减小了矿山地形变化带来的遥感图像研究误差。     

Initial guess by improved population-based intelligent algorithms for large inter-frame deformation measurement using digital image correlation

Digital image correlation (DIC) has received a widespread research and application in experimental mechanics. In DIC, the performance of subpixel registration algorithm (e.g., Newton-Raphson method, quasi-Newton method) relies heavily on the initial guess of deformation. In the case of small inter-frame deformation, the initial guess could be found by simple search scheme, the coarse-fine search for instance. While for large inter-frame deformation, it is difficult for simple search scheme to robustly estimate displacement parameters and deformation parameters simultaneously with low computational cost. In this paper, we proposed three improving strategies, i.e. Q-stage evolutionary strategy (T), parameter control strategy (C) and space expanding strategy (E), and then combined them into three population-based intelligent algorithms (PIAs), i.e. genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO), and finally derived eighteen different algorithms to calculate the initial guess for qN. The eighteen algorithms were compared in three sets of experiments including large rigid body translation, finite uniaxial strain and large rigid body rotation, and the results showed the effectiveness of proposed improving strategies. Among all compared algorithms, DE-TCE is the best which is robust, convenient and efficient for large inter-frame deformation measurement.     

Strain measurement of SU-8 photoresist by a digital image correlation method with a hybrid genetic algorithm

Digital image correlation (DIC) is a whole-field and non-contact strain measuring method. It could provide deformation information of a specimen by processing two digital images that are captured before and after the deformation. To search the deformed images, a hybrid genetic algorithm, in which a simulated annealing mutation process and adaptive mechanisms are added to the real-parameter genetic algorithm, is proposed in this work. To increase the accuracy and reliability of this method, some key parameters of this method are suggested. Then, this method is used to measure the strain during the micro tensile testing of SU-8 photoresist. In addition to the conventional single region, a double region is proposed to calculate the strain by DIC. The results indicate that while the strains obtained by single region are reasonable, those obtained by double region are accurate. Also the mechanical properties of SU-8 could be accurately obtained.     

A weighting window applied to the digital image correlation method

In the digital image correlation method, two steps are used to calculate the displacements of tested images. The first step is to locate the integer-pixel displacement, and the next one is to compute the sub-pixel displacement based on the first step. The benefit from the computation method for the integer-pixel displacement is that its results directly affect the displacement accuracy of each point in tested images. In this paper, a new method is developed to calculate the displacement fields between two images taken before and after deformation of an object. A new correlation function with a weighting factor related to the position of each point in the image is taken into account. The analysis and experimental results confirm the validity of the new method. In addition, the calculation results from our method have more accuracy than that of the traditional one.     

有效的板料成形反向模拟法应力修正策略

金属在流经凹模圆角时受到强烈的弯曲作用,传统的板料成形反向模拟法没有考虑变形历史对应力预测的影响,使得反向模拟法计算的应力值与实际情况有较大偏差.针对反向模拟法无法准确预测成形零件应力分布的缺点,提出一种快速搜索流经凹模圆角区域的单元的方法,对该部分单元进行应力修正.采用一种高效的单轴连续拉伸应力应变本构关系模型,避免了增量有限元法应力应变更新算法的复杂性,同时充分考虑了凹模圆角对金属变形历史的影响.NUMISHEET'93盒形件拉深的标准考题中,通过与增量有限元模拟软件DYNAFORM计算结果的比较,验证了采用提出的多步连续拉伸本构关系模型可以有效地反映变形历史的影响,获得更加接近实际的应力分布.     

Curvelet based image compression via core vector machine

In this paper, a novel curvelet based digital image compression scheme is proposed. Aiming at achieving high compression ratio, the proposed scheme embeds a representative machine learning method, core vector machine (CVM), in the encoding process of the image compression technique. The core vector machine (CVM) has been introduced as an extremely fast classifier which is demonstrably superior to standard support vector machine (SVM) on very large datasets. In this scheme, we appropriately utilize the characteristic of CVM to reduce huge numbers of curvelet coefficients. Compared with image compression algorithms do not use CVM and methods based on wavelet transform, experimental results show that the compression performance of our method gains much improvement in peak-signal-to-noise-ratio (PSNR) and CPU time. Moreover, the algorithm works fairly well for declining block effect at higher compression ratios.     

光谱失真客观度量方法初探

分析了在光谱图像压缩的性能评价中常用的几种光谱失真客观度量方法,针对光谱曲线的关键区域,改进了相对光谱二次误差,提出了一种基于光谱导数曲线的光谱失真客观度量方法.该方法与光谱图像的应用需求一致,对谱线特征吸收峰的变化尤为敏感.仿真实验结果表明,该方法能有效地度量光谱图像压缩引入的各种光谱失真.     

适于星上应用的高光谱图像无损压缩算法

针对常见基于预测、变换、矢量量化及其组合的高光谱无损压缩算法压缩比低、压缩算法整体耗时以及硬件实现困难的问题,提出一种适于星上应用的高光谱图像无损压缩算法。首先,沿光谱线的第一谱段图像采用中值预测器进行谱段内预测,其他谱段图像采用谱间预测。谱间预测采用两步双向预测算法,第一步预测采用双向二阶预测器得到参考预测值,第二步预测采用本文提出的改进LUT搜索预测算法得出4个LUT预测值,然后将参考预测值与其比较得出最终的预测值。最后,使用XX-X空间高光谱相机的压缩系统试验设备对该文提出的压缩算法进行了试验验证。结果表明,压缩系统能快速稳定地工作,平均压缩比达到3.05 bpp,与传统方法相比,平均压缩比提高了0.14~2.94 bpp。有效的提高了高光谱图像无损压缩比和解决了压缩算法整体实现困难的问题。     

基于摄影测量校正的斜光轴数字图像相关方法

提出一种针对单相机、斜光轴测量条件下,基于摄影测量校正的二维数字图像相关法(DIC).变形前,在被测物表面粘贴不少于3个控制点(圆形标志点),通过摄影测量技术得到控制点的三维坐标,利用控制点的三维坐标及其在图像上对应的二维坐标,通过空间后方交会法得到斜光轴相机的三维空间方位,拟合控制点的三维坐标得到控制面.变形过程中,...     

Kalman filter based initial guess estimation for digital image correlation

In applications digital image correlation based algorithms often present a basis for analysis of movement/deformation of bodies. The sequence of the obtained images is analyzed for this purpose. Especially, in cases when the body׳s movement/deformation between two successive images is significant, the initial guess can have a major influence on the execution speed of the algorithm. In the worst case it can even cause the divergence of the algorithm. This was the inspiration to develop a new and unique approach for an accurate and reliable determination of an initial guess for each image pixel. Kalman filter has been used for this purpose. It uses past measurements of observed variable(s) for calculations. Beside that it also incorporates state space model of the actual system. This is one of the most important advantages provided by Kalman filter. The determined initial guess by the proposed method is actually close to the true one and it enables fast convergence. Even more important property of this approach is the fact that it is not path-dependant because each image pixel, which is defined in ROI, is tracked through the sequence of images based on its own past measurements and general state space model. Consequently, the proposed method can be used to analyze tasks where discontinuities between image pixels are present. The applied method can be used to predict an initial guess where reference and deformed subsets are related by translational and rotational motion. The advantages mentioned above are verified with numerical and real experiments. The experimental validations are performed by NR (Newton–Raphson) approach which is the most widely used. Beside NR method the presented algorithm is applicable for other registration methods as well. It is used as an addition for calculation of initial guesses in a sequence of deformed images.