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CN116934833B - Binocular vision-based underwater structure disease detection method, equipment and medium - Google Patents

Binocular vision-based underwater structure disease detection method, equipment and medium
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CN116934833B
CN116934833BCN202310886273.XACN202310886273ACN116934833BCN 116934833 BCN116934833 BCN 116934833BCN 202310886273 ACN202310886273 ACN 202310886273ACN 116934833 BCN116934833 BCN 116934833B
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binocular camera
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CN116934833A (en
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饶瑞
吴源
刘爱荣
毛吉化
陈炳聪
叶茂
黄永辉
陈立弘
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Guangdong Wengu Inspection And Identification Co ltd
Guangzhou Guangjian Construction Engineering Testing Center Co ltd
Guangzhou University
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Guangdong Wengu Inspection And Identification Co ltd
Guangzhou Guangjian Construction Engineering Testing Center Co ltd
Guangzhou University
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Abstract

The application provides a binocular vision-based underwater structure disease detection method, equipment and medium, which are characterized by comprising the following steps: calibrating the underwater binocular camera by adopting a calibration method, establishing a mapping relation between a coordinate system of the underwater binocular camera and a real world coordinate system, and acquiring parameters of the underwater binocular camera; performing enhancement processing on the acquired underwater picture, then performing feature point detection, performing stereo matching through binocular feature extraction, obtaining a parallax image containing depth information, and obtaining three-dimensional coordinates of feature points; calculating an included angle alpha between a plane where the underwater binocular camera is positioned and a plane where the detected structure is positioned for quality inspection; according to the method, the three-dimensional coordinates of the characteristic points are corrected according to the included angle alpha to obtain the three-dimensional size information of the diseases of the underwater tested structure.

Description

Translated fromChinese
基于双目视觉水下结构病害检测方法、设备及介质Method, equipment and medium for underwater structural disease detection based on binocular vision

技术领域Technical Field

本文件涉及视觉检测技术领域,尤其涉及一种基于双目视觉水下结构病害检测方法、设备及介质。This document relates to the field of visual inspection technology, and in particular to a method, equipment and medium for underwater structure defect detection based on binocular vision.

背景技术Background Art

水下双目视觉检测技术是一种基于计算机视觉和光学原理的技术,结合了水下光学传感器和计算机视觉技术,可以用于水下环境监测、水下搜救、海洋生物监测等领域。由于水下环境的复杂性和多样性,水下成像图片会由于水体浑浊、能见度低等因素导致成像不清晰。并且当使用摄像头来捕捉结构病害时,摄像头与被测物体不能完全平行会导致梯形畸变,造成较大的误差。Underwater binocular vision detection technology is a technology based on computer vision and optical principles. It combines underwater optical sensors and computer vision technology and can be used in underwater environmental monitoring, underwater search and rescue, marine life monitoring and other fields. Due to the complexity and diversity of the underwater environment, underwater imaging pictures may be unclear due to factors such as turbid water and low visibility. And when using a camera to capture structural defects, the camera and the object being measured cannot be completely parallel, which will cause trapezoidal distortion and cause large errors.

发明内容Summary of the invention

本发明提供了一种基于双目视觉水下结构病害检测方法、设备及介质方法,旨在解决上述问题。The present invention provides a binocular vision-based underwater structure disease detection method, equipment and medium method, aiming to solve the above-mentioned problem.

本发明提供了一种基于双目视觉水下结构病害检测方法,包括:The present invention provides a method for detecting underwater structural defects based on binocular vision, comprising:

S1、采用标定法对水下双目相机进行标定,建立水下双目相机的坐标系和现实世界的坐标系之间的映射关系,并获取水下双目相机的参数;S1. Calibrate the underwater binocular camera using a calibration method, establish a mapping relationship between the coordinate system of the underwater binocular camera and the coordinate system of the real world, and obtain the parameters of the underwater binocular camera;

S2、通过水下双目相机对水下环境进行图象采集,对采集到的水下图片进行增强处理;S2, collecting images of the underwater environment through an underwater binocular camera, and enhancing the collected underwater images;

S3、对增强后的水下图片进行特征点检测通过双目特征提取进行立体匹配,得到包含深度信息的视差图,根据视差图计算特征点的三维坐标;S3, performing feature point detection on the enhanced underwater image and performing stereo matching through binocular feature extraction to obtain a disparity map containing depth information, and calculating the three-dimensional coordinates of the feature points according to the disparity map;

S4、通过分别选取水下结构上边缘和下边缘的两个特征点的三维坐标,计算出水下双目相机所在平面与被测结构所在平面质检的夹角S4. By selecting the three-dimensional coordinates of the two feature points on the upper edge and the lower edge of the underwater structure, the angle between the plane where the underwater binocular camera is located and the plane where the structure to be tested is located is calculated. ;

S5、根据夹角对特征点的三维坐标进行矫正,获取水下被测结构病害的三维尺寸信息。S5, according to the angle The three-dimensional coordinates of the feature points are corrected to obtain the three-dimensional size information of the underwater structural defects.

本发明提供了一种电子设备,包括:The present invention provides an electronic device, comprising:

处理器;以及,processor; and,

被安排成存储计算机可执行指令的存储器,所述计算机可执行指令在被执行时使所述处理器执行上述基于双目视觉水下结构病害检测方法的步骤。A memory arranged to store computer executable instructions, which, when executed, cause the processor to perform the steps of the above-mentioned binocular vision-based underwater structure disease detection method.

通过采用本发明实施例,通过使用双目摄像头来获得三维坐标,从而修正梯形误差,并通过水下图像增强技术提高图像质量。双目摄像头可以通过成像原理中的角度差异来计算物体的三维坐标,以此来修正梯形畸变的影响,提高测量的准确性。同时,图像增强技术可以提高图像的质量,使得图像更加清晰,提高测量的精度。By adopting the embodiment of the present invention, the three-dimensional coordinates are obtained by using a binocular camera, thereby correcting the trapezoidal error, and improving the image quality through underwater image enhancement technology. The binocular camera can calculate the three-dimensional coordinates of the object through the angle difference in the imaging principle, thereby correcting the influence of trapezoidal distortion and improving the accuracy of measurement. At the same time, image enhancement technology can improve the quality of the image, make the image clearer, and improve the accuracy of measurement.

本发明提供了一种存储介质,用于存储计算机可执行指令,所述计算机可执行指令在被执行时实现上述基于双目视觉水下结构病害检测方法的步骤。The present invention provides a storage medium for storing computer executable instructions, which, when executed, implement the steps of the above-mentioned binocular vision-based underwater structure disease detection method.

附图说明BRIEF DESCRIPTION OF THE DRAWINGS

为了更清楚地说明本说明书一个或多个实施例或现有技术中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本说明书中记载的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动性的前提下,还可以根据这些附图获得其他的附图。In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

图1为本发明实施例的基于双目视觉水下结构病害检测方法的流程图;FIG1 is a flow chart of a method for detecting underwater structural defects based on binocular vision according to an embodiment of the present invention;

图2为本发明实施例的计算相机所在平面与被测结构所在平面的夹角的示意图。FIG. 2 is a diagram showing the angle between the plane where the camera is located and the plane where the structure to be measured is located according to an embodiment of the present invention. Schematic diagram of .

具体实施方式DETAILED DESCRIPTION

为了使本技术领域的人员更好地理解本说明书一个或多个实施例中的技术方案,下面将结合本说明书一个或多个实施例中的附图,对本说明书一个或多个实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本说明书的一部分实施例,而不是全部的实施例。基于本说明书一个或多个实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例,都应当属于本文件的保护范围。In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

方法实施例Method Embodiment

根据本发明实施例提供了一种基于双目视觉水下结构病害检测方法,图1为本发明实施例的基于双目视觉水下结构病害检测方法的示意图,根据图1所示,本发明实施例的基于双目视觉水下结构病害检测方法具体包括:According to an embodiment of the present invention, a method for detecting underwater structural defects based on binocular vision is provided. FIG. 1 is a schematic diagram of a method for detecting underwater structural defects based on binocular vision according to an embodiment of the present invention. As shown in FIG. 1 , the method for detecting underwater structural defects based on binocular vision according to an embodiment of the present invention specifically includes:

S1、采用标定法对水下双目相机进行标定,建立水下双目相机的坐标系和现实世界的坐标系之间的映射关系,并获取水下双目相机的参数,S1具体包括:S1. Calibrate the underwater binocular camera using a calibration method, establish a mapping relationship between the coordinate system of the underwater binocular camera and the coordinate system of the real world, and obtain the parameters of the underwater binocular camera. S1 specifically includes:

S11、利用张正友标定法对双目相机进行标定,获取相机内外参数,从而得到世界坐标系、相机坐标系与图像坐标系之间的转换关系。S11. Use Zhang Zhengyou calibration method to calibrate the binocular camera to obtain the internal and external parameters of the camera, so as to obtain the conversion relationship between the world coordinate system, the camera coordinate system and the image coordinate system.

三维空间点到二维空间点的映射光系为:The mapping optical system from a three-dimensional space point to a two-dimensional space point is:

;

其中,s为比例因子;N为相机内参矩阵;W外参矩阵,为x、y方向上的焦距,R为 3*3 旋转矩阵,t为3*1的平移向量。Among them, s is the scale factor; N is the camera internal parameter matrix; W is the external parameter matrix, is the focal length in the x and y directions, R is the 3*3 rotation matrix, and t is the 3*1 translation vector.

S12、张正友标定法选择棋盘格进行标定,令标定板处于Z=0的平面上,可得到下式:S12, Zhang Zhengyou calibration method selects the chessboard for calibration, and sets the calibration plate on the plane of Z=0, and the following formula can be obtained:

;

令:make:

;

其中H为所求三维空间坐标到二维像素坐标的映射矩阵。。通过旋转矩阵性质可知:Where H is the mapping matrix from the required three-dimensional space coordinates to two-dimensional pixel coordinates. . Through the rotation matrix The properties are known: .

每幅图像对于相机内参都有以下两个约束:Each image has the following two constraints on the camera intrinsic parameters:

;

;

S13、通过拍摄3幅以上图片可以得到相机的映像矩阵H,并计算出具体的摄像机内参和外参。S13. By taking more than three pictures, the image matrix H of the camera can be obtained, and the specific intrinsic and extrinsic parameters of the camera can be calculated.

S2、通过水下双目相机对水下环境进行图象采集,对采集到的水下图片进行增强处理,S2具体包括:S2, collecting images of the underwater environment through an underwater binocular camera, and enhancing the collected underwater images, S2 specifically includes:

S21、通过暗通道先验算法根据雾天成像模型对图像去浑浊,获取颜色校正图像;S21, de-turbidizing the image according to the foggy imaging model by using a dark channel prior algorithm to obtain a color-corrected image;

S22、通过基于加权分布的自适应伽玛校正算法获取对比度增强图像;S22, acquiring a contrast enhanced image by an adaptive gamma correction algorithm based on weighted distribution;

S23、通过直方图均衡化算法调整图像亮度分布获取亮度均衡图像;S23, adjusting the image brightness distribution by a histogram equalization algorithm to obtain a brightness balanced image;

S24、将所述颜色校正图像、对比度增强图像以及亮度均衡图像进行多尺度融合获得融合图像。S24, performing multi-scale fusion on the color-corrected image, the contrast-enhanced image, and the brightness-balanced image to obtain a fused image.

具体的,S21包括:Specifically, S21 includes:

雾天成像模型如下:The foggy imaging model is as follows:

;

;

其中,I表示水下拍摄图像,J表示清晰的理想图像,表示背景光,表示透射率,是衰减系数,d(x)为景深。Among them, I represents the underwater image, J represents the clear ideal image, Indicates background light, represents the transmittance, is the attenuation coefficient and d(x) is the depth of field.

根据暗通道原理可认为在RGB三个通道中,至少有一个通道强度值接近于0,则:According to the dark channel principle, it can be considered that among the three RGB channels, at least one channel intensity value is close to 0, then:

;

其中,表示暗通道图像,表示三个颜色通道,表示以像素x为中心的局部区域;in, represents the dark channel image, represents three color channels, represents the local area centered on pixel x;

根据暗通道先验,求出大气透射率为:According to the dark channel prior, the atmospheric transmittance is calculated as:

;

其中为调节参数。in To adjust the parameters.

求候选背景光点灰度直方图h,自右向左累加直方图h得到,当>0.05%N时,N为像素总数,获取此处的直方图横坐标值z,在[z,255]区间内求得水体背景光值:Find the candidate background light point grayscale histogram h, and accumulate the histogram h from right to left to get ,when When >0.05%N, N is the total number of pixels, obtain the histogram abscissa value z here, and obtain the water body background light value in the interval [z,255]:

;

对退化图像进行颜色校正,并计算出透射率和水体背景光值后,得到去浑浊图像:After color correction of the degraded image and calculation of the transmittance and water background light value, the de-turbidity image is obtained:

;

其中,为避免t(x)过小而设置的临界值,可有效防止复原图像出现过亮像素点或像素区域,取值为 0.1。in, The critical value set to avoid t(x) being too small can effectively prevent the restored image from having too bright pixels or pixel areas, and its value is 0.1.

具体的,S22包括:Specifically, S22 includes:

通过基于加权分布的自适应伽玛校正算法得到高对比度图像,图像中各强度级别的概率密度:A high-contrast image is obtained by an adaptive gamma correction algorithm based on weighted distribution. The probability density of each intensity level in the image is:

;

其中,为具有强度的像素,MN为像素总数,基于概率密度,加权分布函数表示为:in, To have strength pixels, MN is the total number of pixels, based on the probability density , the weighted distribution function is expressed as:

;

其中,为统计直方图中最大概率密度,为最小概率密度。in, is the maximum probability density in the statistical histogram, is the minimum probability density.

伽玛参数由固定系数优化为自适应伽玛参数,以实现水下图像产生相对于的强度变化:Gamma parameters Optimizing fixed coefficients to adaptive gamma parameters , to achieve the intensity change of underwater image generation relative to: ;

其中,为自适应伽玛参数,=为累计分布函数,in, is the adaptive gamma parameter, = is the cumulative distribution function,

;

其中,为输入最大强度。in, is the maximum input intensity.

具体的,S23包括:Specifically, S23 includes:

通过直方图均衡化算法调整图像亮度分布,使图像的亮度分布更加均匀。The image brightness distribution is adjusted through the histogram equalization algorithm to make the image brightness distribution more uniform.

;

式中,为照射分量,为反射分量。将上式中进行傅里叶变换得到:In the formula, is the irradiation component, is the reflection component. Perform Fourier transform on the above formula to get:

;

将上式与同态滤波函相乘并进行傅里叶逆变换得到:Combine the above formula with the homomorphic filter function Multiplying and inverse Fourier transforming gives:

;

通过指数变换得到同态滤波处理图像:The homomorphic filtering image is obtained by exponential transformation:

;

S3、对增强后的水下图片进行特征点检测通过双目特征提取进行立体匹配,得到包含深度信息的视差图,根据视差图计算特征点的三维坐标;S3, performing feature point detection on the enhanced underwater image and performing stereo matching through binocular feature extraction to obtain a disparity map containing depth information, and calculating the three-dimensional coordinates of the feature points according to the disparity map;

具体的,本发明实施例的S3包括:Specifically, S3 of the embodiment of the present invention includes:

S31、将增强后的双目图片通过sift算法进行特征点检测,并通过双目立体匹配进行左右两幅图的特征点进行匹配,并得到特征点的视图差。S31, the enhanced binocular image is subjected to feature point detection by the SIFT algorithm, and the feature points of the left and right images are matched by binocular stereo matching to obtain the view difference of the feature points.

S32、将匹配后得到的特征点的视差d,计算特征点的深度信息:S32, calculate the depth information of the feature points using the disparity d of the feature points obtained after matching:

;

其中,为相机焦距,B为双目摄像头之间的距离,分别是左右图像上特征点的横坐标。in, is the focal length of the camera, B is the distance between the binocular cameras, are the horizontal coordinates of the feature points on the left and right images respectively.

S33、结合相机参数,计算出特征点的三维坐标。S33. Calculate the three-dimensional coordinates of the feature points based on the camera parameters.

S4、通过分别选取水下结构上边缘和下边缘的两个特征点的三维坐标,计算出水下双目相机所在平面与被测结构所在平面质检的夹角S4. By selecting the three-dimensional coordinates of the two feature points on the upper edge and the lower edge of the underwater structure, the angle between the plane where the underwater binocular camera is located and the plane where the structure to be tested is located is calculated. ;

图2为本发明实施例的计算相机所在平面与被测结构所在平面的夹角的示意图,根据图2所示,本发明实施例的计算出水下双目相机所在平面与被测结构所在平面质检的夹角的步骤包括:FIG. 2 is a diagram showing the angle between the plane where the camera is located and the plane where the structure to be measured is located according to an embodiment of the present invention. 2, the angle between the plane where the underwater binocular camera is located and the plane where the structure to be measured is calculated according to the embodiment of the present invention. The steps include:

S41、选取图像上下四个角点特征点A1(x1,y1,z1)、A2(x2,y2,z2)、B1(x3,y3,z3)、B2(x4,y4,z4);S41, selecting the upper and lower corner feature pointsA1 (x1 ,y1 ,z1 ),A2 (x2 ,y2 ,z2 ),B1 (x3 ,y3 ,z3 ),B2 (x4 ,y4 ,z4 ) of the image;

S42、分别计算上边缘角点的平均值坐标),下边缘角点的平均值坐标),其中,S42, respectively calculate the average coordinates of the upper edge corner points , , ), the average coordinates of the lower edge corners , , ),in, , , ; ;

S43、计算被测结构表面与相机所在平面的夹角S43. Calculate the angle between the surface of the structure being measured and the plane where the camera is located .

S5、根据夹角对特征点的三维坐标进行矫正,获取水下被测结构病害的三维尺寸信息。S5, according to the angle The three-dimensional coordinates of the feature points are corrected to obtain the three-dimensional size information of the underwater structural defects.

具体的,本发明实施例的S5具体包括:Specifically, S5 of the embodiment of the present invention specifically includes:

将S3计算得到的三维坐标)进行深度修正,,得到修正后坐标);The three-dimensional coordinates calculated by S3 ) for depth correction, , and obtain the corrected coordinates );

将修正后的三维坐标与上边缘角点的平均值坐标)做差得到最终水下结构病害的精确三维尺寸信息。The corrected three-dimensional coordinates and the average coordinates of the upper edge corner points , , ) to obtain the final accurate three-dimensional size information of underwater structure defects.

通过采用本发明实施例,具备如下有益效果:By adopting the embodiments of the present invention, the following beneficial effects are achieved:

使用双目摄像头来获得三维坐标,从而修正梯形误差,并通过水下图像增强技术提高图像质量。双目摄像头可以通过成像原理中的角度差异来计算物体的三维坐标,以此来修正梯形畸变的影响,提高测量的准确性。同时,图像增强技术可以提高图像的质量,使得图像更加清晰,提高测量的精度。Use binocular cameras to obtain three-dimensional coordinates to correct trapezoidal errors and improve image quality through underwater image enhancement technology. The binocular camera can calculate the three-dimensional coordinates of the object through the angle difference in the imaging principle, thereby correcting the influence of trapezoidal distortion and improving the accuracy of measurement. At the same time, image enhancement technology can improve the quality of the image, making the image clearer and improving the accuracy of measurement.

装置实施例一Device Example 1

本发明实施例提供了一种电子设备,包括:An embodiment of the present invention provides an electronic device, including:

处理器;以及,processor; and,

被安排成存储计算机可执行指令的存储器,所述计算机可执行指令在被执行时使所述处理器执行如上述方法实施例的步骤。A memory is arranged to store computer executable instructions, which when executed cause the processor to perform the steps of the above method embodiments.

装置实施例二Device Example 2

本发明实施例提供了一种存储介质,用于存储计算机可执行指令,所述计算机可执行指令在被执行时实现如如上述方法实施例的步骤。An embodiment of the present invention provides a storage medium for storing computer-executable instructions, wherein the computer-executable instructions implement the steps of the above method embodiment when executed.

最后应说明的是:以上各实施例仅用以说明本发明的技术方案,而非对其限制;尽管参照前述各实施例对本发明进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分或者全部技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

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Citations (2)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
CN101656857A (en)*2008-08-192010-02-24精工爱普生株式会社Projection display apparatus and display method
CN103395391A (en)*2013-07-032013-11-20北京航空航天大学Lane changing warning device and lane changing state identifying method for vehicle

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
CN104766058B (en)*2015-03-312018-04-27百度在线网络技术(北京)有限公司A kind of method and apparatus for obtaining lane line
CN111800589B (en)*2019-04-082022-04-19清华大学 Image processing method, device and system, and robot
CN110148095B (en)*2019-05-142021-05-07北京科技大学Underwater image enhancement method and enhancement device
DE102019135107A1 (en)*2019-12-192021-06-24Bundesdruckerei Gmbh DEVICE AND METHOD FOR DETERMINING A BIOMETRIC FEATURE OF A FACE OF A PERSON
CN112132958B (en)*2020-09-232023-01-03哈尔滨工程大学Underwater environment three-dimensional reconstruction method based on binocular vision
CN113239918B (en)*2021-07-132021-10-01北京金博星指纹识别科技有限公司Image resolution normalization processing method and device
CN115187565A (en)*2022-07-202022-10-14东南大学 A kind of underwater bridge pier disease identification and positioning method, device, electronic equipment and storage medium
CN115272271B (en)*2022-08-092025-06-20郑州芯视道机器人技术有限公司 A pipeline defect detection and positioning ranging system based on binocular stereo vision
CN115752270A (en)*2022-10-182023-03-07湖北工业大学 Image Correction Method, System and Device for Shield Tail Gap Based on Segment Wedge Quantity

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
CN101656857A (en)*2008-08-192010-02-24精工爱普生株式会社Projection display apparatus and display method
CN103395391A (en)*2013-07-032013-11-20北京航空航天大学Lane changing warning device and lane changing state identifying method for vehicle

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