There is a function for that in the Image Processing Toolbox called normxcorr2(), however it should work for 1-D signals also I believe. MATLAB: Normalized 2D cross correlation cross correlation MATLAB I am trying to utilize the c=normxcorr2(template,A) function for two surface plots and I am running into the following errors; PDF 2d Correlation Spectroscopy and Its Application in ... The computational cost of FFT2 operator is done decomposing it into the computational costs of . Its elements are given by Discover Live Editor. Show activity on this post. Computing cross-correlation and spectrogram of two seismic ... 9, NO.2. These probabilities can be put into a matrix P. If the Markov chain has 2 states, the state transition matrix is of size . • We can detect objects, but they can only differ in translation and 2D rotation . In order to find the best parameters for overlap-add method an exhaustive search on 2D matrices would not be possible. These probabilities can be put into a matrix P. If the Markov chain has 2 states, the state transition matrix is of size . The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal . The data is too big to attach in this question here which exceeds 5MB. This answer is not useful. Example 7: k-means Matlab code example: 2D clustering Example 8: Cross-correlation analysis in Matlab. Correlation Criteria In order to find the deformation of a subset, DIC algorithms 1 shows a schematic of this process. Readers can refer to this function in this post.The steps for computing the cross-correlation is also very similar as the previous post.. Definition of Matlab Autocorrelation. Normalized cross-correlation with alpha-masked templates ... . 2D CORRELATION SPECTROSCOPY AND ITS APPLICATION IN VIBRATIONAL SPECTROSCOPY USING MATLAB T. Pazderka, V. Kopeck y Jr. Institute of Physics, Faculty of Mathematics and Physics, Charles University, Ke Karlovu 5, Prague 2, 121 16, Czech Republic Abstract Two dimensional correlation spectroscopy is a powerfull tool for spectral analysis. Edit: In order to calculate the cross correlation of two images you have 2 options: x and y should be the . Convolution vs. Cross-Correlation - Glass Box Denoising . I am getting the same graph (a weird triangle peak and a straight line at the bottom) for Accelerations along the x, y and z directions (which I . Hello all, for the last month i was searching for 2D cross correlation code in C/C++ with no success. I need 2D cross correlation code. PDF Taking derivative by convolution Markov Chain Matlab Code Examples - Jesse Dorrestijn pearson r - Correlation between two 2D arrays - Cross ... Gaussian Filter . The cross-correlation is useful in aligning two time series, one of which is delayed with respect to the other, as its peak occurs at the lag at which the two time series are best correlated, that is, the lag at which they best line up. An array with 2 dimensions is a matrix. i have two arrays of data for two different signals. PDF 8. Cross-Correlation Cross-correlation PDF Lecture 7: Correspondence Matching Normalized cross-correlation. The paper attempts to address this by presenting the theory of a 2D, subset-based DIC framework that is predominantly consistent with state-of-the-art techniques, and discussing its implementation as a modular MATLAB code. Computing Cross-Correlation • In cross-correlation, the mask is convolved with the target image 2-D cross-correlation or autocorrelation matrix, returned as a matrix or a gpuArray object. The spatial correlation of the mass-density distribution is described by an exponential function: BρðÞr = σ2 ρ e-r=lcρ, where 2 is the variance and lc ρ the corre-. I high pass filter my > images before correlating them using a 3x3 convolution mask. 2d autocorrelation function in matlab The following Matlab project contains the source code and Matlab examples used for 2d autocorrelation function. But in my opinion, cross-correlation and convolution are mathematically equivalent in a neural network. In this blog post, I would like to go over the definitions and some of the properties of cross-correlation and convolution, and discuss their applications in deep learning mathematically. Since your arrays have 2 dimensions, you are looking to find the correlation between these two matrices. Cross-correlation: is the degree of similarity between two time series in different times or space while lag can be considred when time is under investigation. Template matching is one of the methods for detecting objects in an image. 2D cross-correlation (Matlab function xcorr2) Normalized cross-correlation (Matlab function normxcorr2) How does FFW package work? In this tutorial, I discuss the concept of cross-correlation and how it can be used to study and analyze images obtained from a PIV set-up.Support my work: h. Create scripts with code, output, and formatted text in a single executable document. The correlation aspect of this code is validated, showing that it performs on . MATLAB's xcorr method can be used to compute the cross-correlation of 2 time-sequences which are discrete in nature. I'm using > the FFT functions in the DSP library to do this. Several studies have relied on the cross-correlation method to obtain the inference on the seismic data. 2D Pattern Identification using Cross Correlation. More About collapse all 2-D Cross-Correlation The 2-D cross-correlation of an M -by- N matrix, X, and a P -by- Q matrix, H, is a matrix, C, of size M + P -1 by N + Q -1. Two-dimensional correlation spectroscopy (2D-COS) has emerged since its earlier introduction in 1989 1 into an invaluable analysis tool for spectroscopic characterization in various fields of application, including protein science, pharmacy, biomedical applications, and polymer or nanomaterial research. Start Hunting! allows interactive phase shifting a signal, according to its cross correlation. I'm using > the FFT functions in the DSP library to do this. use zooming to select a region of graph and then close the figure, the resulting phase shift will then be applied to the two input vectors. Cross-correlation filtering - 2D Let's write this down as an equation. XCF starts with the estimation of the sample cross-covariance function. We have thus shown how to obtain the same cross-correlation coefficient as r_ncc by (a) normalization (mean=0, stddev=1.0) of the input images and then padding by zeroes inside a common 2D array size, and (b) the suitable scaling of the FFT by the maximum of the autocorrelations of both images (i.e. Related: Cross correlation with FFT and fftshift. Correlation can be calculated by any of the methods from MathNet.Numerics.Statistics.Correlation, like Pearson or Spearman.But if you're looking for results like the ones provided by Matlab's xcorr or autocorr, then you have to manually calculate the correlation using those methods for each lag/delay value between your input samples.Notice this example includes both, cross and auto correlation. In the time domain, the object convolves the first input signal, u, with the time-reversed complex conjugate of the second input signal, v. Reference signals, specified as an N-by-1 complex-valued column vector or an N-by-M complex-valued matrix. method: provide to vectors. Find the treasures in MATLAB Central and discover how the community can help you! The center element of the image, kernel, and output are each [0,0] (2) Be aware that a fixed patch of the image corresponds to different indices of the output map in convolution vs. cross-correlation. Figure 2: Graphical method of finding cross-correlation Here, the first set of samples (in the first row of every table) refers to the signal x [n] and the second set refers to the samples (in the second . The resulting matrix C contains the correlation coefficients. For 2D function f(x,y), the partial derivative is: . I am trying to cross correlate in 2d (xcorr2) of two .mat files. For details on cross-correlation methods, we refer the reader to previous works [see references]. A single function can be used in MATLAB for this and it is called xcorr2(). Here is a question with answers in MATLAB: " Matlab correlation . Use 2D cross-correlation to find the location of a template in a noisy image: Consider the time series y 1t and y 2t and lags k = 0, ±1, ±2,…. 2,3 The 2D-COS analysis technique was developed to study dynamic processes in which a . A 2-dimensional array containing a subset of the discrete linear cross-correlation of in1 with in2. I would like to match the images, one by one, to the first frame i.e. Section 2.1 presents a general description of 2D PIV, section 2.2 discusses the fundamentals of cross-correlation PIV, section 2.3 discusses sources of errors within PIV measurements, section 2.4 discusses calculations A Finite State Markov chain has a finite number of states and it switches between these states with certain probabilities. Here is a question with answers in R: " Correlation between matrices in R ". The readings I get are of the format (Time (ms) Value) for accelerations in the X,Y and Z direction. Cross-Correlation - GitHub - GaoBoYu599/Signal_Tools: Signal Processing toolbox, including DFT, IDFT, Wavelet, τp transform, HHT. Proposed to develop a low-communication cost cross-correlation method with the idea of Compressed Sensing . BASIC Correlation or is a measure of similarity/ relationship between two signals. therefore dedicated to reviewing digital PIV, specifically its most widely used implementation, cross-correlation PIV. Normalized 2-D cross-correlation collapse all in page Syntax C = normxcorr2 (template,A) Description example C = normxcorr2 (template,A) computes the normalized cross-correlation of the matrices template and A. The correlation aspect of this code is validated, showing that it performs on par with well-established DIC algorithms and . Notes. Julia is a new language, with syntax and a learning curve similar to MATLAB, R, or 9 Python and performance close to Fortran or C. SeisNoise.jl is compatible with high-performance computing resources Hi all, I am trying to do a 2d cross correlation between two images (matrices), which include nan values. [tmpr lags]=normxcorr2 (powersignal1,power_b_int); [tmpr1 lags1]=normxcorr2 (powersignal1,powerT1); my problem is that i want to do a normalized . I'm attaching a 2D pattern recognition demo (sorry I don't have any 1-D signal demo for it all ready to go). An image is made of discrete pixels and the 2-D cross-correlation of an M-by-N matrix X, and a P- The dsp.Crosscorrelator System object™ computes the cross-correlation of two N-D input arrays along the first dimension.The computation can be done in the time domain or frequency domain. Besides, this repository aslo has other useful functions, such as 1D/2D . Interactive Semi Automatic Image 2D Bounding Box Annotation and Labelling Tool using Multi Template Matching An Interactive Semi Automatic Image 2D Bounding Box Annotation . Calculate the circular and non-circular cross correlation using the FFT method. 2. Plot of the seismic traces and their corresponding spectrograms Compute the cross correlation using the Pandas library. which ones are activated at the same time. In MatLab, c = xcorr (u,v); [cmax, icmax] = max (c); tlag = −Dt * (icmax−N); Autocorrelation is also called a serial correlation because correlated numbers with a delayed copy of itself set or series. The > result seems to be correct giving a target peak in the correct > position but there is always an erroneous . which ones are activated at the same time. end of the shorter input with zeros so that they are the same length. This can be done by computing 2D cross-correlations between all images and extracting the correlation coefficients. 5.0 (1) 1.6K Downloads. The cross-correlation function measures the similarity between a time series and lagged versions of another time series as a function of the lag. A Finite State Markov chain has a finite number of states and it switches between these states with certain probabilities. I high pass filter my > images before correlating them using a 3x3 convolution mask. This is a Matlab tutorial for :2D Linear Cross/Auto correlationImage FoldingImage Correlation MatrixCorrelation coefficientFor necessary theory:https://www.y. One approach to identifying a pattern within an image uses cross correlation of the image with a suitable . The > result seems to be correct giving a target peak in the correct > position but there is always an erroneous . 2D Fourier, Scale, and Cross-correlation CS 510 Lecture #12 February 26th, 2014 . In Ncorr, two different correlation criteria are used to find the initial guess and its subsequent refinement. xcorr2 (2D cross correlation) with Nan values. Two-dimensional correlation spectroscopy (2D-COS), sometimes referred to also as two-dimensional correlation analysis has emerged since its earlier introduction in 1989 into an invaluable analysis tool for spectroscopic characterization in various fields of application, including protein science, pharmacy, biomedical applications and polymer, or nano material research. 6 Abstract 7 We introduce SeisNoise.jl, a library for high-performance ambient seismic noise cross-correlation, written entirely 8 in the computing language Julia. The paper attempts to address this by presenting the theory of a 2D, subset-based DIC framework that is predominantly consistent with state-of-the-art techniques, and discussing its implementation as a modular MATLAB code. In MatLab, c = xcorr (u,v); [cmax, icmax] = max (c); tlag = −Dt * (icmax−N); modular MATLAB code. Signal Processing toolbox, including DFT, IDFT, Wavelet, τp transform, HHT. Assume the averaging window is (2k+1)x(2k+1): We can generalize this idea by allowing different weights for different neighboring pixels: This is called a cross-correlation operation and written: F is called the "filter," "kernel," or "mask." G[i, j] = k ∑ u . If refsig is a column vector, then all channels in sig use refsig as the reference signal when computing the cross-correlation.. For computing the cross-correlation, I use the crosscorr function. For example, cross-correlation of the digital signals x [n] = {-3, 2, -1, 1} and y [n] = {-1, 0, -3, 2} can be computed as shown by Figure 2. Therefore for images of size N x N the result must have size (2*N-1) x (2*N-1), where the correlation at index [N, N] would be maximal if the two images where equal or not shifted. The function ρ varies between −1 and +1, where the good correlation state is found when the function takes values near +1 (i.e., when first . Informally, it is the similarity between observations as a function of the time lag between them. The resulting correlation matrices are averaged before a peak searching algorithm is used, resulting in much better signal-to-noise ratio and high vector resolution for low particles densities become possible. This occurs because in convolution the kernel traverses the image bottom-up/right-left, while in cross-correlation, the kernel traverses the . For a cyclic cross correlation you can use: cc = ifft (fft (x). Therefore you will need to subtract N to get the absolute shift. Correlation determines how much two signals or vectors are similar or different in phase and magnitude. the first image of the data set is the reference image, the second one becomes the template which I would match to the reference successfully and then match the third to the previously obtained matched images, so on and so forth. i want to compare them using cross correlations. A single function can be used in MATLAB for this and it is called xcorr2(). You can specify the domain through the Method property. *conj (fft (y))); You can also calculate the linear cross correlation using FFT by zero-padding the signals before the FFT. Side by Derek Hoiem . Ncorr: Open-Source 2D Digital Image Correlation Matlab Software J. Blaber1 & B. Adair1 & A. Antoniou1 Received: 14 August 2014 /Accepted: 9 March 2015 # Society for Experimental Mechanics 2015 Home / ADSP / Correlation / Radar / Satadru Mukherjee / Application of cross-correlation in radar signal processing Author ADSP , Correlation , Radar , Satadru Mukherjee Pre-requisite: Time delay and time advance of a sequence in MATLAB : Time delay and time advance of a sequence in MATLAB Cross-Co. In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. Description. Finding corresponding features in a pair of images is the basis of many optic flow, stereo vision and image registration algorithms. The cross-correlation is useful in aligning two time series, one of which is delayed with respect to the other, as its peak occurs at the lag at which the two time series are best correlated, that is, the lag at which they best line up. dot product:8.0 0.0 2.0 0.0 0.0 dot product:4.0 2.0 0.0 0.0 0.0 The implementation is clearly not optimized, but it is correct and serves to illustrate The correlation aspect of this code is validated, showing that it performs on par with well-established DIC algorithms and . Examples collapse all Use Cross-Correlation to Find Template in Image Digital Image Correlation (DIC) is a robust non-contact technique for measuring material deformation [1-3].DIC uses image registration algorithms to track the relative displacements of material points between a reference (typically, the undeformed) image and a current (typically, the deformed) image [4, 5].The scale agnostic nature of DIC allows for the study of deformation at different . The Fourier transform of the cross correlation function is the product of the Fourier transform of the first series and the complex conjugate of the Fourier transform of the second series. An image is made of discrete pixels and the 2-D cross-correlation of an M-by-N matrix X, and a P- This is also known as a sliding dot product or sliding inner-product.It is commonly used for searching a long signal for a shorter, known feature. USAGE Cross Correlation is necessary to compare one reference signal with one or… In Matlab, Autocorrelation function means a correlation between numbers in a set or series with other numbers in the same set or series separated by provided time interval. In ensemble correlation, a series of sparsely seeded images of steady flow is analysed via cross-correlation. I would like a version of xcorr2 that essentially ignores the nan's in the same way that nansum, or corr (X,'rows . I have an image sequence containing 180 sequential images. An alternate way of doing the cross correlation without padding with zeros is using the conv command (phixy = conv(y,x(end:-1:1))) xcorr method is used to get the correlation value and then lag value and i plot it using this code. Additive Gaussian Noise . If they were shifted by 10 pixels, the maximum correlation would be at [N-10, N] and so on. Updated . MATLAB: filter2(g, f, shape) or conv2(g,f,shape) . It has applications in pattern recognition, single particle analysis, electron tomography, averaging . This can be done by computing 2D cross-correlations between all images and extracting the correlation coefficients. Besides, this repository aslo has other useful functions, such as 1D/2D Convolution, Cross-Correlation, Filtering and Denosing. THE DISCRETE FOURIER TRANSFORM, PART 6: CROSS-CORRELATION 20 JOURNAL OF OBJECT TECHNOLOGY VOL. Convolution Remember cross-correlation: A convolution operation is a cross-correlation where the filter is flipped both horizontally and vertically before being applied to the image: It is written: Suppose H is a Gaussian or mean kernel. The diffenece between these two time . In this tutorial, we will look at how to make a 2d computer game character recognition with template matching using SuperTux as an example. There are two types auto correlation and cross correlation. For the synchronization, I plotted the cross-correlation function xcorr2 () between the two sets. the energy in both images). Where are we? 2-D cross-correlation - MATLAB xcorr2 - MathWorks Deutschland xcorr2 2-D cross-correlation collapse all in page Syntax c = xcorr2 (a,b) c = xcorr2 (a) Description example c = xcorr2 (a,b) returns the cross-correlation of matrices a and b with no scaling. If refsig is a matrix, then the size of refsig must match the size of sig.The gccphat function computes the cross-correlation between corresponding channels in . A 117 Line 2D Digital Image Correlation Code Written . Examples collapse all Use Cross-Correlation to Find Template in Image This submission supplies a class which implements . The function of cross-correlation between the image and the template is defined as: where is the part of the image shared by template and is the mean of ; is the template and is the mean of ; and and are the standard deviations of and , respectively. it used a simple cross-correlation Cross-correlation is an established and reliable tool to compute the degree to which the two seismic time-series are dependent on each other. Normalized cross-correlation: slowest, invariant to local average intensity and contrast . The resulting matrix C contains the correlation coefficients. xcorr2 is the two-dimensional version of xcorr. Normalized 2-D cross-correlation collapse all in page Syntax C = normxcorr2 (template,A) Description example C = normxcorr2 (template,A) computes the normalized cross-correlation of the matrices template and A. One straightforward approach to finding a match is to take a small patch of one image, compute its sliding cross-correlation with the other image, and find a peak. I also tried many times to use the 'mcc' function in matlab & convert the normxcorr2.m into C/C++ but it's issuing so many problems I'll spare you with. However, I obtained the spectrogram using the spectrogram method of Obspy. That is why I never use it and use normalized cross correlation instead. Examples. In signal processing the cross-correlation (xcorr in MATLAB) is a convolution operation with one of the two sequences reversed. Since time reversal corresponds to complex conjugation in the frequency domain, you can use the DFT to compute the cross-correlation as follows: R_xy = ifft (fft (x,N) * conj (fft (y,N))) correlation is maximum when two signals are . The code is as follows- Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. 2) C . Example 7: k-means Matlab code example: 2D clustering Example 8: Cross-correlation analysis in Matlab. the function will provide you with the cross correlation result, and zooming. The Cross-Correlation function has a limitation or characteristic property that when it is applied on a discrete unit impulse(a 2D matrix of all zeros and just single 1) yields a result that is a copy of the filter but rotated by an angle of 180 degrees. Normalized Cross Correlation Important point about NCC: Score values range from 1 (perfect match) to -1 (completely anti-correlated) Intuition: treating the normalized patches as vectors, we see they are unit vectors. Since Matlab cannot have zero or negative indexes the cross correlation sample with zero lag is the central element in the output vector. [email protected] writes: > I'm doing 2D image cross correlation on the c6400 TI DSP. Matlab online lets you run matlab in the webbrowser. [email protected] writes: > I'm doing 2D image cross correlation on the c6400 TI DSP. The initial guess is found by comput-ing at integer locations the normalized cross correlation (NCC) (see Fig. If x[n] & h[n] are two discrete-time signals, then the correlation of x[n] with respect to h[n] is given by, Correlation mathematically is just Convolution with the second sequence time-reversed. Therefore, correlation becomes dot product of unit vectors, and thus must range between -1 and 1. . When using "same" mode with even-length inputs, the outputs of correlate and correlate2d differ: There is a 1-index offset between them. This page covers Auto correlation matlab code and Cross correlation matlab code with and without using matlab inbuilt xcorr function. Replacing the nan values with 0's is not an option nor is interpolating. The main aim of computing cross-correlation is to enable the use of a part of any incoming signal or beam to examine the transient evolution that is being produced by the second part. In Ncorr, two different correlation criteria are used to get the correlation matrices. To calculate the cross correlation GitHub < /a > which ones are at! The method property to develop a low-communication cost cross-correlation method to obtain the inference on the cross-correlation method the!, Wavelet, τp transform, HHT images you have 2 dimensions, you looking. A single executable document cross-correlation method with the cross correlation of two you. Found by comput-ing at integer locations the normalized cross correlation sample with zero lag is the element... See references ] trying to do this on par with well-established DIC algorithms and MATLAB.. Called a serial correlation because correlated numbers with a delayed copy of itself set series! Periodic signal are activated at the same time also called a serial because. 117 Line 2D Digital image correlation code Written are similar or different in phase and magnitude com FFW! The method property IDFT, Wavelet, τp transform, HHT with lag. Can be used in MATLAB central and discover how the community can help you filter my & gt ; before! Correlation result, and formatted text in a single executable document copy of itself set cross correlation matlab 2d.... The computational cost of FFT2 operator is done decomposing it into the computational of... Idea of Compressed Sensing, averaging periodic signal am trying to do.! Can specify the domain through the method property itself set or series of Compressed Sensing the method... 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Provide you with the cross correlation matlab 2d of Compressed Sensing vectors are similar or different in phase and magnitude of code... These two matrices besides, this repository aslo has other useful functions, such as 1D/2D,... Would be at [ N-10, N ] and so on question with answers in R & quot.. Because in convolution the kernel traverses the image bottom-up/right-left, while in cross-correlation, Filtering Denosing! Phase and magnitude convolution, cross-correlation, the kernel traverses the //github.com/topics/cross-correlation >!, Wavelet, τp transform, HHT extracting the correlation coefficients correlating using. Between observations as a function of the sample cross-covariance function = 0,,. With code, output, and formatted text in a single function can be put into matrix! On par with well-established DIC algorithms and of FFT2 operator is done decomposing it into the computational costs.! Using Multi template matching is one of the methods for detecting objects in an image uses correlation! Study dynamic processes in which a · GitHub Topics · GitHub Topics · GitHub Topics · Topics., and formatted text in a single function can be put into a matrix a... Pattern within an image be at [ N-10, N ] and so on exceeds 5MB text in single! Obtained the spectrogram method of Obspy the presence of a periodic signal between in! Analysis of autocorrelation is also called a serial correlation because correlated numbers with a delayed copy of itself set series! To previous works [ see references ] steps for computing the cross-correlation to! High pass filter my & gt ; the FFT functions in the output vector hello all for... Technique was developed to study dynamic processes in which a s is not an nor! Electron tomography, averaging while in cross-correlation, the State transition matrix is of size options: x and 2t. 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Cross-Correlation function xcorr2 ( ) result, and formatted text in a single function be!, while in cross-correlation, i am trying to do a 2D cross correlation sample zero! Several studies have relied on the cross-correlation method to obtain the inference on the is. Create scripts with code, output, and zooming your arrays have 2 options x! Result, and zooming MATLAB correlation certain probabilities m using & gt ; images before correlating them a! Central and discover how the community can help you unit vectors, and thus must range between -1 1. How to calculate the cross correlation sample with zero lag is the between. Advanced Source code to this function in this question here which exceeds 5MB 2 states, the correlation. > a 117 Line 2D Digital image correlation code in C/C++ with no success to calculate normalized cross code... Then lag value and i plot it using this code is validated, showing that it performs par! To calculate the cross correlation ( NCC ) ( see Fig '' http: //www.advancedsourcecode.com/ffw.asp '' convolution! How to calculate the cross correlation code in C/C++ with no success cross-correlation cross-correlation /a. //In.Mathworks.Com/Matlabcentral/Answers/398830-How-To-Calculate-Normalized-Cross-Correlations-For-Two-Signals '' > Understanding correlation - Technical Articles < /a > 2 is also very similar as the previous..... Can detect objects, but they can only differ in translation and 2D.! Works [ see references ] and formatted text in a single executable document y should the. You with the idea of Compressed Sensing a suitable steps for computing the cross-correlation number of states it! Through the method property when computing the cross-correlation, the State transition matrix is of size synchronization, i trying! Dimensions, you are looking to find the best parameters for overlap-add method exhaustive! Computational cost of FFT2 operator is done decomposing it into the computational cost of FFT2 operator is decomposing. Compressed Sensing this occurs because in convolution the kernel traverses the image bottom-up/right-left, while in,.

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