CN112435252B - A detection method for warhead fragment perforation and pit - Google Patents

A detection method for warhead fragment perforation and pit Download PDF

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CN112435252B
CN112435252B CN202011405498.1A CN202011405498A CN112435252B CN 112435252 B CN112435252 B CN 112435252B CN 202011405498 A CN202011405498 A CN 202011405498A CN 112435252 B CN112435252 B CN 112435252B
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李翰山
张晓倩
高俊钗
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Xian Technological University
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Abstract

The invention provides a method for detecting breaking perforation and pit of a warhead, which belongs to the technical field of image processing and comprises the following steps: for an equivalent target plate image acquired after static explosion of a warhead, carrying out geometric correction and actual physical size recovery based on a homography matrix of photographic transformation; linearly dividing the equivalent target plate based on the vertex and the boundary; smoothing the equivalent target plate image based on the guided filtering; combining the change of the illumination of the flash lamp at different positions on the equivalent target plate, and generating a hyperboloid threshold value by adopting image gradients; dividing a broken piece perforation area with bright gray and a broken piece pit area with dark gray on an equivalent target plate by using a hyperboloid threshold value; the broken perforation and pit area are used as seed points with gray level similarity to perform area growth; and removing the pseudo target area by using the fragment perforation and pit area and shape characteristic criterion. The calculation method can save the state information of the broken perforation and the pit, accurately divide the broken perforation and the pit area, and conveniently and rapidly realize the detection of the broken perforation and the pit.

Description

一种战斗部破片穿孔和凹坑检测方法A method for detecting warhead fragment perforations and pits

技术领域Technical Field

本发明属于图像处理技术领域,涉及战斗部破片击中等效靶板的图像处理技术领域,具体涉及一种战斗部破片穿孔和凹坑检测方法。The invention belongs to the field of image processing technology, relates to the field of image processing technology of warhead fragments hitting equivalent target plates, and specifically relates to a warhead fragment perforation and pit detection method.

背景技术Background Art

在静爆条件下获得精确的破片场参数,是构建战斗部威力态势的基础,也是分析破片场动爆状态的前提。静爆前,在战斗部周围布置一定距离、角度的等效靶板,由于破片分散特性的不确定性,爆炸后破片分布在每块等效靶板的数量、位置、穿孔和凹坑面积等是截然不同的,需要快速获取并统计每块等效靶板被破片击中的情况,如等效靶板上破片穿孔的数量,是破片飞散特性计算的前提和基础,而破片的飞散特性是考核弹药威力参量的一项重要指标。针对破片场参数测量的靶板法,迫切需要提出一种快速的、全方位、自动统计破片数据的检测技术。Obtaining accurate fragmentation field parameters under static explosion conditions is the basis for constructing the power situation of the warhead and the prerequisite for analyzing the dynamic explosion state of the fragmentation field. Before the static explosion, equivalent target plates are arranged at a certain distance and angle around the warhead. Due to the uncertainty of the fragment dispersion characteristics, the number, position, perforation and pit area of the fragments distributed on each equivalent target plate after the explosion are completely different. It is necessary to quickly obtain and count the situation of each equivalent target plate being hit by fragments, such as the number of fragment perforations on the equivalent target plate, which is the premise and basis for calculating the fragment dispersion characteristics, and the fragment dispersion characteristics are an important indicator for assessing the power parameters of ammunition. For the target plate method of measuring fragmentation field parameters, it is urgent to propose a fast, all-round, and automatic statistical fragmentation data detection technology.

目前,等效靶板上破片穿孔的检测主要通过人工检测,但一般情况下战斗部爆炸半径较大,等效靶板数量多,破片穿孔数量也较多,所以破片穿孔检测工作量较大。同时在破片穿孔情况复杂时存在判断标准不统一,需要多人共同现场确认。而且破片穿孔的状态信息没有保存,不能复现破片穿孔的具体位置,更不利于后续的核查,从而影响检测的客观性、准确性和可靠性。因此,有必要研究一种基于图像处理技术的破片穿孔和凹坑检测方法。At present, the detection of fragment perforation on equivalent target plates is mainly carried out through manual detection. However, in general, the explosion radius of the warhead is large, the number of equivalent target plates is large, and the number of fragment perforations is also large, so the workload of fragment perforation detection is large. At the same time, when the fragment perforation situation is complicated, there is no unified judgment standard, and multiple people are required to confirm on site. Moreover, the status information of fragment perforation is not saved, and the specific location of the fragment perforation cannot be reproduced, which is not conducive to subsequent verification, thus affecting the objectivity, accuracy and reliability of the detection. Therefore, it is necessary to study a fragment perforation and pit detection method based on image processing technology.

为了进一步客观、准确、可靠地检测破片穿孔和凹坑,发明了一种战斗部破片穿孔和凹坑检测方法,该计算方法可以保存破片穿孔和凹坑状态信息,准确分割出破片穿孔和凹坑区域,方便、快捷地实现破片穿孔和凹坑的检测。In order to further objectively, accurately and reliably detect fragment perforations and pits, a warhead fragment perforation and pit detection method was invented. This calculation method can save the fragment perforation and pit state information, accurately segment the fragment perforation and pit area, and conveniently and quickly realize the detection of fragment perforations and pits.

发明内容Summary of the invention

为了克服上述现有技术存在的不足,本发明提供了一种战斗部破片穿孔和凹坑检测方法。In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides a warhead fragment perforation and pit detection method.

为了实现上述目的,本发明提供如下技术方案:In order to achieve the above object, the present invention provides the following technical solutions:

基于双曲面阈值分割的破片穿孔和凹坑检测方法,包括以下步骤:The fragment perforation and pit detection method based on hyperbolic threshold segmentation includes the following steps:

步骤1、采集战斗部静爆后的第一等效靶板图像,采用人工交互方式准确选择第一等效靶板图像四个顶点,获取顶点图像坐标(x′i,y′i,1)T;结合等效靶板先验形状和物理尺寸,获得等效靶板顶点物理坐标(xi,yi,1)T,i=1,4,建立并计算摄影变换的单应矩阵H3×3Step 1: Collect the first equivalent target plate image after the static explosion of the warhead, accurately select the four vertices of the first equivalent target plate image by manual interaction, and obtain the vertex image coordinates (x′ i , y′ i , 1) T ; combine the prior shape and physical size of the equivalent target plate to obtain the physical coordinates of the equivalent target plate vertices (x i , y i , 1) T , i = 1, 4, and establish and calculate the homography matrix H 3×3 of the photographic transformation:

Figure BDA0002816525900000021
Figure BDA0002816525900000021

基于单应矩阵H3×3对第一等效靶板图像进行几何校正和实际物理尺寸恢复得到第二等效靶板图像;Based on the homography matrix H 3×3, the first equivalent target plate image is geometrically corrected and the actual physical size is restored to obtain a second equivalent target plate image;

步骤2、基于第二等效靶板图像中的等效靶板四个顶点和边界直线性,分割第二等效靶板图像,得到第三等效靶板图像piStep 2: based on the four vertices of the equivalent target plate and the boundary linearity in the second equivalent target plate image, segment the second equivalent target plate image to obtain a third equivalent target plate image p i ;

步骤3、基于引导滤波,平滑第三等效靶板图像pi,得到第四等效靶板图像qi,并对第四等效靶板图像qi进行引导滤波;Step 3: based on guided filtering, smooth the third equivalent target image p i to obtain a fourth equivalent target image q i , and perform guided filtering on the fourth equivalent target image q i ;

引导滤波后的第四等效靶板图像为:The fourth equivalent target plate image after guided filtering is:

qi′=akIi+b i∈ωk (2)q i ′=a k I i +bi∈ω k (2)

其中,qi′为输出的第四等效靶板图像,Ii为引导图像,这里用第三等效靶板图像pi作为引导图像,ak和b是当窗口中心位于k时该线性函数的不变系数,ak和b为最小化图像pi和qi′差别的代价函数E:Where, qi ′ is the output fourth equivalent target image, Ii is the guide image, here the third equivalent target image pi is used as the guide image, ak and b are the invariant coefficients of the linear function when the window center is located at k, ak and b are the cost function E that minimizes the difference between images pi and qi ′:

Figure BDA0002816525900000031
Figure BDA0002816525900000031

步骤4、结合闪光灯光照在现场布置的等效靶板上不同位置的变化,采用引导滤波后的第四等效靶板图像qi′的梯度生成双曲面阈值;Step 4: combining the changes of the flash light on different positions of the equivalent target plate arranged on site, using the gradient of the fourth equivalent target plate image q i ′ after guided filtering to generate a hyperbolic threshold;

步骤5、利用双曲面阈值分割引导滤波后的第四等效靶板图像qi′后获得的亮灰度的破片穿孔区域和暗灰度的破片凹坑区域;Step 5: using a hyperbolic threshold to segment the fourth equivalent target plate image q i ′ after the filtering to obtain a bright gray fragment perforation area and a dark gray fragment pit area;

步骤6、以破片穿孔和凹坑区域作为灰度相似性的种子点进行区域生长;Step 6: Use the fragment perforation and pit areas as seed points of grayscale similarity to perform region growing;

步骤7、利用破片穿孔和凹坑面积、形状特征准则去除伪目标区域。Step 7: Use the fragment perforation and pit area and shape feature criteria to remove the false target area.

优选地,所述步骤4具体包括:Preferably, the step 4 specifically includes:

步骤4.1、基于canny算子计算引导滤波后的第四等效靶板图像qi′的灰度梯度;对于先正后负的梯度,取绝对值,同时对于先负后正的梯度,置0,采用均值计算第一梯度阈值;Step 4.1, calculate the grayscale gradient of the fourth equivalent target plate image qi ′ after guided filtering based on the canny operator; for the gradient that is positive first and then negative, take the absolute value, and for the gradient that is negative first and then positive, set it to 0, and use the mean value to calculate the first gradient threshold;

步骤4.2、采用细化算法获得边缘点,将边缘点所对应的平滑图像的灰度值作为第一基准阈值;Step 4.2, using a thinning algorithm to obtain edge points, and using the grayscale value of the smoothed image corresponding to the edge points as the first reference threshold;

步骤4.3、对于先负后正的梯度,取绝对值,同时对于先正后负的梯度,置0,基于均值计算第二梯度阈值;Step 4.3: For the gradient that is negative first and then positive, take the absolute value, and for the gradient that is positive first and then negative, set it to 0, and calculate the second gradient threshold based on the mean;

步骤4.4、采用细化算法获得边缘点;将边缘点所对应的平滑图像的灰度值作为第二基准阈值;Step 4.4, using a thinning algorithm to obtain edge points; using the grayscale value of the smoothed image corresponding to the edge points as the second reference threshold;

步骤4.5、对于利用闪光灯照明拍摄的第一等效靶板图像,以空间等效靶板左上角为原点,两条垂直的边为坐标轴建立世界坐标系OXYZ;根据相机成像模型,结合等效靶板的先验形状和尺寸,采用单应矩阵计算相机坐标系相对于世界坐标系的旋转矩阵R=[r1,r2,r3]和平移向量t,然后根据式:Step 4.5: For the first equivalent target plate image taken with flash lighting, establish a world coordinate system OXYZ with the upper left corner of the space equivalent target plate as the origin and two vertical sides as coordinate axes; according to the camera imaging model, combined with the prior shape and size of the equivalent target plate, use the homography matrix to calculate the rotation matrix R = [r 1 , r 2 , r 3 ] and the translation vector t of the camera coordinate system relative to the world coordinate system, and then according to the formula:

Figure BDA0002816525900000041
Figure BDA0002816525900000041

将第一等效靶板图像上每个像素点的三维坐标从世界坐标系[X Y Z]T转换到相机坐标系[x y z]T,从而得到第一等效靶板图像上每个像素点到相机光心(x0,y0,z0)的距离d:The three-dimensional coordinates of each pixel point on the first equivalent target plate image are converted from the world coordinate system [XYZ] T to the camera coordinate system [xyz] T , thereby obtaining the distance d from each pixel point on the first equivalent target plate image to the camera optical center (x 0 , y 0 , z 0 ):

Figure BDA0002816525900000051
Figure BDA0002816525900000051

闪光灯光源的尺寸相对于拍摄的大物体,远距离,可以近似为点光源,其位置近似在相机光心,则闪光灯光源照度在图像中的成像灰度f(x,y)与距离d的关系为:The size of the flash light source is relatively large and far away from the object being photographed, so it can be approximated as a point light source, and its position is approximately at the optical center of the camera. The relationship between the imaging grayscale f(x, y) of the flash light source illumination in the image and the distance d is:

Figure BDA0002816525900000052
Figure BDA0002816525900000052

从而给出第一等效靶板图像不同位置相对于成像物体中心位置的灰度变化比例;Thus, the grayscale change ratio of different positions of the first equivalent target plate image relative to the center position of the imaging object is given;

步骤4.6、基于基准阈值1和第二基准阈值,结合闪光灯照度的灰度变化比例,生成第一曲面阈值和第二曲面阈值。Step 4.6: Based on the reference threshold 1 and the second reference threshold, combined with the grayscale change ratio of the flash illumination, generate a first curved surface threshold and a second curved surface threshold.

优选地,所述步骤5具体包括:Preferably, the step 5 specifically includes:

步骤5.1、利用第一曲面阈值分割引导滤波后的第四等效靶板图像qi′,对于大于双第一曲面阈值的像素灰度置为1,否则置为0,获得亮灰度破片穿孔区域第一分割图像;Step 5.1, using the first curved surface threshold to segment the fourth equivalent target plate image q i ′ after the guide filtering, the grayscale of the pixels greater than the double first curved surface threshold is set to 1, otherwise it is set to 0, to obtain the first segmented image of the bright grayscale fragment perforation area;

步骤5.2、利用双第二曲面阈值分割引导滤波后的第四等效靶板图像qi′,对于小于第二曲面阈值的像素灰度置为1,否则置为0,获得暗灰度破片凹坑区域第二分割图像;Step 5.2, using the double second curved surface threshold segmentation to guide the fourth equivalent target plate image q i ′ after filtering, setting the grayscale of pixels less than the second curved surface threshold to 1, otherwise set to 0, to obtain the second segmentation image of the dark gray fragment pit area;

步骤5.3、对分割图像1和第二分割图像进行与运算,获得包含破片穿孔和破片凹坑区域的第三分割图像。Step 5.3, performing an AND operation on the segmented image 1 and the second segmented image to obtain a third segmented image including the fragment perforation and fragment pit area.

优选地,所述步骤6具体包括:Preferably, the step 6 specifically includes:

对于第三分割图像,将破片穿孔和凹坑区域作为种子点区域,对其周围进行单个像素膨胀预操作;如果膨胀像素与种子点区域所对应的引导滤波后的第四等效靶板图像qi′的像素灰度和的灰度均值相差在阈值准则R范围内,则所膨胀像素置为1,进行区域生长,否则不进行区域生长;膨胀预操作和区域生长重复进行,一直到没有像素生长停止,最后得到生长图像。For the third segmented image, the fragment perforation and pit area is taken as the seed point area, and a single pixel expansion pre-operation is performed around it; if the difference between the expanded pixel and the grayscale mean of the fourth equivalent target plate image qi ′ after the guided filtering corresponding to the seed point area is within the threshold criterion R, the expanded pixel is set to 1 and regional growth is performed, otherwise regional growth is not performed; the expansion pre-operation and regional growth are repeated until there is no pixel growth and finally a growth image is obtained.

优选地,所述步骤7具体包括:Preferably, the step 7 specifically includes:

对于生长图像中的破片穿孔和凹坑区域含有伪目标,确定破片穿孔和凹坑所含像素数量的范围准则Wn,以及它们长轴与短轴的形状比例范围准则Wb,计算每个破片穿孔或凹坑区域的像素数量和形状比例,并与范围准则进行比较,如果在准则范围外,则为伪目标,予以去除。For the fragment perforation and pit regions in the growth image that contain pseudo targets, determine the range criterion Wn for the number of pixels contained in the fragment perforations and pits, as well as the range criterion Wb for the shape ratio of their major axis to minor axis. Calculate the number of pixels and shape ratio of each fragment perforation or pit region and compare them with the range criterion. If they are outside the criterion range, they are pseudo targets and are removed.

本发明提供的一种战斗部破片穿孔和凹坑检测方法具有以下有益效果:针对等效靶板粗糙性引起的幅值和密度较大的成像噪声,采用引导滤波,获得了保护边缘的去噪图像;针对背景灰度不一致和目标属性不同的情况,结合闪光灯光照函数,同时并准确地分割检测出破片穿孔和凹坑区域,通过任意位姿拍摄等效靶板的几何校正,可以计算破片穿孔和凹坑的实际位置坐标;本发明客观、准确、可靠地检测破片穿孔和凹坑,该计算方法可以保存破片穿孔和凹坑状态信息,准确分割出破片穿孔和凹坑区域,方便、快捷地实现破片穿孔和凹坑的检测。A warhead fragment perforation and pit detection method provided by the present invention has the following beneficial effects: for imaging noise with large amplitude and density caused by the roughness of an equivalent target plate, guided filtering is used to obtain a denoised image with protected edges; for situations where background grayscale is inconsistent and target attributes are different, the fragment perforation and pit areas are simultaneously and accurately segmented and detected in combination with a flash light illumination function, and the actual position coordinates of the fragment perforations and pits can be calculated by geometric correction of shooting the equivalent target plate in any posture; the present invention objectively, accurately and reliably detects fragment perforations and pits, and the calculation method can save fragment perforation and pit state information, accurately segment fragment perforation and pit areas, and conveniently and quickly realize the detection of fragment perforations and pits.

附图说明BRIEF DESCRIPTION OF THE DRAWINGS

为了更清楚地说明本发明实施例及其设计方案,下面将对本实施例所需的附图作简单地介绍。下面描述中的附图仅仅是本发明的部分实施例,对于本领域普通技术人员来说,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

图1为本发明实施例1的一种战斗部破片穿孔和凹坑检测方法的流程图。FIG1 is a flow chart of a method for detecting warhead fragment perforations and dents according to Embodiment 1 of the present invention.

具体实施方式DETAILED DESCRIPTION

为了使本领域技术人员更好的理解本发明的技术方案并能予以实施,下面结合附图和具体实施例对本发明进行详细说明。以下实施例仅用于更加清楚地说明本发明的技术方案,而不能以此来限制本发明的保护范围。In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

实施例1Example 1

本发明提供了一种战斗部破片穿孔和凹坑检测方法,具体如图1所示,包括以下步骤:The present invention provides a warhead fragment perforation and pit detection method, as shown in FIG1, comprising the following steps:

步骤1、采集战斗部静爆后的第一等效靶板图像,采用人工交互方式准确选择第一等效靶板图像四个顶点,结合先验形状和尺寸对等效靶板基于摄影变换的单应矩阵进行几何校正和实际物理尺寸恢复,获取顶点图像坐标(x′i,y′i,1)T;结合等效靶板先验形状和物理尺寸,获得等效靶板顶点物理坐标(xi,yi,1)T,i=1,...4,建立并计算摄影变换的单应矩阵H3×3Step 1: collect the first equivalent target plate image after the static explosion of the warhead, accurately select the four vertices of the first equivalent target plate image by manual interaction, perform geometric correction and actual physical size restoration on the homography matrix of the equivalent target plate based on photographic transformation in combination with the prior shape and size, and obtain the vertex image coordinates (x′ i , y′ i , 1) T ; obtain the equivalent target plate vertex physical coordinates (x i , y i , 1) T , i=1,...4, and establish and calculate the homography matrix H 3×3 of photographic transformation:

Figure BDA0002816525900000071
Figure BDA0002816525900000071

基于单应矩阵H3×3对第一等效靶板图像进行几何校正和实际物理尺寸恢复得到第二等效靶板图像;Based on the homography matrix H 3×3, the first equivalent target plate image is geometrically corrected and the actual physical size is restored to obtain a second equivalent target plate image;

步骤2、基于第二等效靶板图像中的等效靶板四个顶点和边界直线性,分割第二等效靶板图像,得到第三等效靶板图像piStep 2: based on the four vertices of the equivalent target plate and the boundary linearity in the second equivalent target plate image, segment the second equivalent target plate image to obtain a third equivalent target plate image p i ;

步骤3、基于引导滤波,平滑第三等效靶板图像pi,得到第四等效靶板图像qi,并对第四等效靶板图像qi进行引导滤波;Step 3: based on guided filtering, smooth the third equivalent target image p i to obtain a fourth equivalent target image q i , and perform guided filtering on the fourth equivalent target image q i ;

引导滤波后的第四等效靶板图像为:The fourth equivalent target plate image after guided filtering is:

qi′=akIi+b i∈ωk (2)q i ′=a k I i +bi∈ω k (2)

其中,qi′为输出的第四等效靶板图像,Ii为引导图像,这里用第三等效靶板图像pi作为引导图像,ak和b是当窗口中心位于k时该线性函数的不变系数,ak和b为最小化图像pi和qi′差别的代价函数E:Where, qi ′ is the output fourth equivalent target image, Ii is the guide image, here the third equivalent target image pi is used as the guide image, ak and b are the invariant coefficients of the linear function when the window center is located at k, ak and b are the cost function E that minimizes the difference between images pi and qi ′:

Figure BDA0002816525900000081
Figure BDA0002816525900000081

步骤4、结合闪光灯光照在现场布置的等效靶板上不同位置的变化,采用引导滤波后的第四等效靶板图像qi′的梯度生成双曲面阈值;Step 4: combining the changes of the flash light on different positions of the equivalent target plate arranged on site, using the gradient of the fourth equivalent target plate image q i ′ after guided filtering to generate a hyperbolic threshold;

具体的,本实施例中,步骤4具体包括:Specifically, in this embodiment, step 4 specifically includes:

步骤4.1、基于canny算子计算引导滤波后的第四等效靶板图像qi′的灰度梯度;对于先正后负的梯度,取绝对值,同时对于先负后正的梯度,置0,采用均值计算第一梯度阈值;Step 4.1, calculate the grayscale gradient of the fourth equivalent target plate image qi ′ after guided filtering based on the canny operator; for the gradient that is positive first and then negative, take the absolute value, and for the gradient that is negative first and then positive, set it to 0, and use the mean value to calculate the first gradient threshold;

步骤4.2、采用细化算法获得边缘点,将边缘点所对应的平滑图像的灰度值作为第一基准阈值;Step 4.2, using a thinning algorithm to obtain edge points, and using the grayscale value of the smoothed image corresponding to the edge points as the first reference threshold;

步骤4.3、对于先负后正的梯度,取绝对值,同时对于先正后负的梯度,置0,基于均值计算第二梯度阈值;Step 4.3: For the gradient that is negative first and then positive, take the absolute value, and for the gradient that is positive first and then negative, set it to 0, and calculate the second gradient threshold based on the mean;

步骤4.4、采用细化算法获得边缘点;将边缘点所对应的平滑图像的灰度值作为第二基准阈值;Step 4.4, using a thinning algorithm to obtain edge points; using the grayscale value of the smoothed image corresponding to the edge points as the second reference threshold;

步骤4.5、对于利用闪光灯照明拍摄的第一等效靶板图像,以空间等效靶板左上角为原点,两条垂直的边为坐标轴建立世界坐标系OXYZ;根据相机成像模型,结合等效靶板的先验形状和尺寸,采用单应矩阵计算相机坐标系相对于世界坐标系的旋转矩阵R=[r1,r2,r3]和平移向量t,然后根据式:Step 4.5: For the first equivalent target plate image taken with flash lighting, establish a world coordinate system OXYZ with the upper left corner of the space equivalent target plate as the origin and two vertical sides as coordinate axes; according to the camera imaging model, combined with the prior shape and size of the equivalent target plate, use the homography matrix to calculate the rotation matrix R = [r 1 , r 2 , r 3 ] and the translation vector t of the camera coordinate system relative to the world coordinate system, and then according to the formula:

Figure BDA0002816525900000091
Figure BDA0002816525900000091

将第一等效靶板图像上每个像素点的三维坐标从世界坐标系[X Y Z]T转换到相机坐标系[x y z]T,从而得到第一等效靶板图像上每个像素点到相机光心(x0,y0,z0)的距离d:The three-dimensional coordinates of each pixel point on the first equivalent target plate image are converted from the world coordinate system [XYZ] T to the camera coordinate system [xyz] T , thereby obtaining the distance d from each pixel point on the first equivalent target plate image to the camera optical center (x 0 , y 0 , z 0 ):

Figure BDA0002816525900000092
Figure BDA0002816525900000092

闪光灯光源的尺寸相对于拍摄的大物体,远距离,可以近似为点光源,其位置近似在相机光心,则闪光灯光源照度在图像中的成像灰度f(x,y)与距离d的关系为:The size of the flash light source is relatively large and far away from the object being photographed, so it can be approximated as a point light source, and its position is approximately at the optical center of the camera. The relationship between the imaging grayscale f(x, y) of the flash light source illumination in the image and the distance d is:

Figure BDA0002816525900000101
Figure BDA0002816525900000101

从而给出第一等效靶板图像不同位置相对于成像物体中心位置的灰度变化比例;Thus, the grayscale change ratio of different positions of the first equivalent target plate image relative to the center position of the imaging object is given;

步骤4.6、基于基准阈值1和第二基准阈值,结合闪光灯照度的灰度变化比例,生成第一曲面阈值和第二曲面阈值。Step 4.6: Based on the reference threshold 1 and the second reference threshold, combined with the grayscale change ratio of the flash illumination, generate a first curved surface threshold and a second curved surface threshold.

步骤5、利用双曲面阈值分割引导滤波后的第四等效靶板图像qi′后获得的亮灰度的破片穿孔区域和暗灰度的破片凹坑区域;Step 5, using a hyperbolic threshold to segment the fourth equivalent target plate image qi ′ after the guide filtering to obtain the bright gray fragment perforation area and the dark gray fragment pit area;

具体的,本实施例中,步骤5具体包括:Specifically, in this embodiment, step 5 specifically includes:

步骤5.1、利用第一曲面阈值分割引导滤波后的第四等效靶板图像qi′,对于大于双第一曲面阈值的像素灰度置为1,否则置为0,获得亮灰度破片穿孔区域第一分割图像;Step 5.1, using the first curved surface threshold to segment the fourth equivalent target plate image q i ′ after the guide filtering, the grayscale of the pixels greater than the double first curved surface threshold is set to 1, otherwise it is set to 0, to obtain the first segmented image of the bright grayscale fragment perforation area;

步骤5.2、利用双第二曲面阈值分割引导滤波后的第四等效靶板图像qi′,对于小于第二曲面阈值的像素灰度置为1,否则置为0,获得暗灰度破片凹坑区域第二分割图像;Step 5.2, using the double second curved surface threshold segmentation to guide the fourth equivalent target plate image q i ′ after filtering, setting the grayscale of pixels less than the second curved surface threshold to 1, otherwise set to 0, to obtain the second segmentation image of the dark gray fragment pit area;

步骤5.3、对分割图像1和第二分割图像进行与运算,获得包含破片穿孔和破片凹坑区域的第三分割图像。Step 5.3, performing an AND operation on the segmented image 1 and the second segmented image to obtain a third segmented image including the fragment perforation and fragment pit area.

步骤6、以破片穿孔和凹坑区域作为灰度相似性的种子点进行区域生长;Step 6: Use the fragment perforation and pit areas as seed points of grayscale similarity to perform region growing;

具体的,本实施例中,步骤6具体包括:Specifically, in this embodiment, step 6 specifically includes:

对于第三分割图像,将破片穿孔和凹坑区域作为种子点区域,对其周围进行单个像素膨胀预操作;如果膨胀像素与种子点区域所对应的引导滤波后的第四等效靶板图像qi′的像素灰度和的灰度均值相差在阈值准则R范围内,则所膨胀像素置为1,进行区域生长,否则不进行区域生长;膨胀预操作和区域生长重复进行,一直到没有像素生长停止,最后得到生长图像。For the third segmented image, the fragment perforation and pit area is taken as the seed point area, and a single pixel expansion pre-operation is performed around it; if the difference between the expanded pixel and the grayscale mean of the fourth equivalent target plate image q i ′ after the guided filtering corresponding to the seed point area is within the threshold criterion R, the expanded pixel is set to 1 and regional growth is performed, otherwise regional growth is not performed; the expansion pre-operation and regional growth are repeated until there is no pixel growth and finally a growth image is obtained.

步骤7、利用破片穿孔和凹坑面积、形状特征准则去除伪目标区域。Step 7: Use the fragment perforation and pit area and shape feature criteria to remove the false target area.

具体的,本实施例中,步骤7具体包括:Specifically, in this embodiment, step 7 specifically includes:

对于生长图像中的破片穿孔和凹坑区域含有伪目标,确定破片穿孔和凹坑所含像素数量的范围准则Wn,以及它们长轴与短轴的形状比例范围准则Wb,计算每个破片穿孔或凹坑区域的像素数量和形状比例,并与范围准则进行比较,如果在准则范围外,则为伪目标,予以去除。For the fragment perforation and pit regions in the growth image that contain pseudo targets, determine the range criterion Wn for the number of pixels contained in the fragment perforations and pits, as well as the range criterion Wb for the shape ratio of their major axis to minor axis. Calculate the number of pixels and shape ratio of each fragment perforation or pit region and compare them with the range criterion. If they are outside the criterion range, they are pseudo targets and are removed.

本实施例中提出的检测方法客观、准确、可靠地检测了破片穿孔和凹坑,采用投影变换的单应矩阵对等效靶板进行几何校正,保证了任意位姿拍摄等效靶板的效果一致性;基于顶点与边界直线性的等效靶板分割,去除了复杂背景干扰;基于引导滤波,去噪同时保护了边缘;结合闪光灯光照在等效靶板上不同位置的变化,采用图像梯度生成双曲面阈值,同时兼顾了亮灰度的破片穿孔和暗灰度的破片凹坑;分别利用双曲面阈值分割等效靶板上亮灰度的破片穿孔区域和暗灰度的破片凹坑区域,有效提取种子点;以破片穿孔和凹坑区域作为灰度相似性的种子点进行区域生长,准确地获取目标区域;利用破片穿孔和凹坑面积、形状特征准则去除伪目标区域,获取有效的目标区域,准确分割出破片穿孔和凹坑区域,方便、快捷地实现破片穿孔和凹坑的检测。The detection method proposed in this embodiment objectively, accurately and reliably detects fragment perforations and pits, and uses the homography matrix of projection transformation to perform geometric correction on the equivalent target plate, thereby ensuring the consistency of the effect of shooting the equivalent target plate in any posture; the equivalent target plate is segmented based on the linearity of vertices and boundaries to remove complex background interference; based on guided filtering, denoising is performed while protecting the edge; combined with the changes in the flash light shining on different positions of the equivalent target plate, the image gradient is used to generate a hyperbolic threshold, while taking into account the bright gray fragment perforations and dark gray fragment pits; the hyperbolic threshold is used to segment the bright gray fragment perforation area and the dark gray fragment pit area on the equivalent target plate, respectively, to effectively extract seed points; the fragment perforation and pit area are used as seed points of grayscale similarity for regional growth, and the target area is accurately obtained; the fragment perforation and pit area and shape feature criteria are used to remove the pseudo target area, obtain the effective target area, accurately segment the fragment perforation and pit area, and conveniently and quickly realize the detection of fragment perforations and pits.

以上所述实施例仅为本发明较佳的具体实施方式,本发明的保护范围不限于此,任何熟悉本领域的技术人员在本发明披露的技术范围内,可显而易见地得到的技术方案的简单变化或等效替换,均属于本发明的保护范围。The embodiments described above are only preferred specific implementation modes of the present invention, and the protection scope of the present invention is not limited thereto. Any simple changes or equivalent replacements of the technical solutions that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belong to the protection scope of the present invention.

Claims (5)

1. The method for detecting the perforation and pit of the broken piece of the warhead is characterized by comprising the following steps:
step 1, acquiring a first equivalent target plate image after static explosion of a warhead, selecting four vertexes of the first equivalent target plate image in a manual interaction mode, and acquiring vertex image coordinates (x '' i ,y′ i ,1) T The method comprises the steps of carrying out a first treatment on the surface of the Combining the prior shape and the physical size of the equivalent target plate to obtain the equivalent target plate topPoint physical coordinates (x i ,y i ,1) T I=1,..4, building and calculating homography matrix H of photographic transformation 3×3
Figure FDA0004152408090000011
Based on homography matrix H 3×3 Performing geometric correction and actual physical size recovery on the first equivalent target plate image to obtain a second equivalent target plate image;
step 2, dividing the second equivalent target plate image based on the linearity of four vertexes and boundaries of the equivalent target plate in the second equivalent target plate image to obtain a third equivalent target plate image p i
Step 3, for the third equivalent target plate image p i Smoothing to obtain a fourth equivalent target plate image q i And for the fourth equivalent target plate image q i Conducting guide filtering;
the fourth equivalent target plate image after the guide filtering is as follows:
q′ i =a k I i +b (2)
wherein q i ' fourth equivalent target plate image as output, I i For guiding the image, i.e. the third equivalent target plate image p i ,a k And b is the invariant coefficient of the linear function when the window center is at k;
step 4, combining the change of different positions of the flash lamp illumination on the equivalent target plate arranged on site, and adopting a fourth equivalent target plate image q i ' gradient generation hyperboloid threshold;
step 5, segmenting the fourth equivalent target plate image q by using hyperboloid threshold value i The obtained bright gray fragment perforation area and dark gray fragment pit area;
step 6, taking the broken perforation and the pit area as seed points with gray level similarity for area growth;
and 7, removing the pseudo target area by using the fragment perforation and pit area and shape characteristic criterion.
2. The warhead fragment perforation and pit detection method of claim 1, wherein the step 4 specifically comprises:
step 4.1, calculating a fourth equivalent target plate image q based on a canny operator i ' gray scale gradient; taking an absolute value for a gradient which is positive and negative firstly, setting 0 for the gradient which is negative and positive firstly, and calculating a first gradient threshold value by adopting an average value;
step 4.2, obtaining edge points of a first gradient threshold by adopting a thinning algorithm, and taking a gray value of a smooth image corresponding to the edge points of the first gradient threshold as a first reference threshold;
step 4.3, taking an absolute value for the gradient which is negative before positive, setting 0 for the gradient which is positive before negative, and calculating a second gradient threshold value based on the average value;
step 4.4, obtaining edge points of a second gradient threshold value by adopting a thinning algorithm; taking the gray value of the smooth image corresponding to the edge point of the second gradient threshold value as a second reference threshold value;
step 4.5, for a first equivalent target plate image shot by using flash lamp illumination, establishing a world coordinate system OXYZ by taking the upper left corner of a space equivalent target plate as an original point and two vertical sides as coordinate axes; according to the camera imaging model, combining the prior shape and the prior size of the equivalent target plate, adopting a homography matrix to calculate a rotation matrix R= [ R ] of a camera coordinate system relative to a world coordinate system 1 ,r 2 ,r 3 ]And a translation vector t, then according to the equation:
Figure FDA0004152408090000021
three-dimensional coordinates of each pixel point on the first equivalent target plate image are obtained from a world coordinate system [ X Y Z] T Conversion to camera coordinate system [ x y z ]] T Thereby obtaining the image of each pixel point on the first equivalent target plate to the optical center (x 0 ,y 0 ,z 0 ) Distance d of (2):
Figure FDA0004152408090000031
the relation between the imaging gray scale f (x, y) of the flash light source illumination in the image and the distance d is as follows:
Figure FDA0004152408090000032
thereby giving gray scale variation ratios of different positions of the first equivalent target plate image relative to the center position of the imaging object;
and 4.6, generating a first curved surface threshold value and a second curved surface threshold value based on the first reference threshold value and the second reference threshold value and combining the gray scale change proportion of the flash illumination.
3. The warhead fragment perforation and pit detection method of claim 2, wherein the step 5 specifically comprises:
step 5.1, segmenting the fourth equivalent target plate image q by utilizing the first curved surface threshold value i Setting the pixel gray level larger than the threshold value of the double first curved surfaces as 1, otherwise setting the pixel gray level as 0, and obtaining a first segmentation image of the bright gray level fragment perforation area;
step 5.2, guiding the filtered fourth equivalent target plate image q by utilizing the threshold segmentation of the double second curved surfaces i Setting the pixel gray level smaller than the threshold value of the second curved surface to be 1, otherwise setting the pixel gray level to be 0, and obtaining a second segmentation image of the dark gray level fragment pit area;
and 5.3, performing AND operation on the segmented image 1 and the second segmented image to obtain a third segmented image containing the broken piece perforation and the broken piece pit area.
4. The warhead fragment perforation and pit detection method of claim 3, wherein the step 6 specifically comprises:
for the third segmented image, taking the fragment perforation and pit area as seed point areas, and performing single pixel expansion pre-operation on the periphery of the fragment perforation and pit area; if the expansion pixel corresponds to the seed point regionFourth equivalent target plate image q after conducting filtering i Setting the expanded pixel as 1 if the difference between the gray scale of the pixel and the gray average value of the gray scale is within the range of a threshold criterion R, and carrying out region growth, otherwise, not carrying out region growth; the dilation pre-operation and region growing are repeated until no pixel growth stops, and finally a growing image is obtained.
5. The warhead fragment perforation and pit detection method of claim 4, wherein the step 7 specifically comprises:
for the broken perforation and pit area in the growth image to contain pseudo target, determining the range criterion W of the pixel number contained in the broken perforation and pit n And shape ratio range criterion W of their major axis and minor axis b The number of pixels and the shape ratio of each fragment perforation or pit area are calculated and compared with a range criterion, and if the number of pixels and the shape ratio are out of the range criterion, the number of pixels and the shape ratio are pseudo targets and removed.
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