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CN106225702A - Fracture width detection apparatus and method - Google Patents

Fracture width detection apparatus and method Download PDF

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Publication number
CN106225702A
CN106225702A CN201610630124.7A CN201610630124A CN106225702A CN 106225702 A CN106225702 A CN 106225702A CN 201610630124 A CN201610630124 A CN 201610630124A CN 106225702 A CN106225702 A CN 106225702A
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crack
sigma
image
width
camera
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雷斌
徐鹏成
周亮
杜幸运
易文
赵慧
蒋林
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Wuhan University of Science and Technology WHUST
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Wuhan University of Science and Technology WHUST
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/14—Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/0008—Industrial image inspection checking presence/absence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Analysis (AREA)

Abstract

The present invention proposes a kind of fracture width detection devices and methods therefor, and this detection method is it can be avoided that the interference that causes of artificial subjective factor, more in real time, accurate, objective, efficient；The crack that assembly of the invention can be mounted on unmanned plane road and bridge is detected, and has that detection efficiency is high, the feature of applied range；The method of the present invention can have preferable transplantability with existing PC and arm processor portable set slitless connection；Crack detecting device, simple in construction, with low cost.

Description

裂缝宽度检测装置和方法Crack width detection device and method

技术领域technical field

本发明涉及表面检测设备技术领域，尤其涉及一种裂缝宽度检测装置和方法。The invention relates to the technical field of surface detection equipment, in particular to a crack width detection device and method.

背景技术Background technique

在房屋、道路和桥梁以及一些精密的工件等工程构件表面避免不了地存在着大量裂缝，而裂缝常被作为构件、施工验收、事故鉴定和维修补救的重要依据，因而对裂缝的检测与分析对重要的工程具有实际意义。A large number of cracks inevitably exist on the surface of engineering components such as houses, roads and bridges, and some precision workpieces, and cracks are often used as an important basis for components, construction acceptance, accident identification, and maintenance and remedy. Therefore, the detection and analysis of cracks is very important. Important projects have practical significance.

传统的裂缝宽度检测方法包括塞尺测量法、显微镜测量法、图像显示和人工读数法、图像像素标定法，这些方法由于人为主观因素较大，检测设备笨重，检测效率较低，导致其所能实用的范围受限，尤其是在一些危险地带以及多处裂缝需要检测的情形下，上述方法很难精准完成。Traditional crack width detection methods include feeler gauge measurement, microscope measurement, image display and manual reading, and image pixel calibration. These methods are subject to human factors, heavy detection equipment, and low detection efficiency. The practical range is limited, especially in some dangerous areas and the situation where multiple cracks need to be detected, the above method is difficult to complete accurately.

发明内容Contents of the invention

有鉴于此，本发明提出了一种测量实时、精准、客观、高效的裂缝宽度检测装置和方法。In view of this, the present invention proposes a real-time, accurate, objective and efficient crack width detection device and method.

本发明的技术方案是这样实现的：Technical scheme of the present invention is realized like this:

一方面，本发明提供了一种裂缝宽度检测装置，其包括激光测距仪、摄像头、支架和处理器，激光测距仪和摄像头分别与处理器信号连接，On the one hand, the present invention provides a kind of crack width detecting device, and it comprises laser rangefinder, camera, bracket and processor, and laser rangefinder and camera are respectively connected with processor signal,

激光测距仪和摄像头固定在支架上，其中，The laser range finder and the camera are fixed on the bracket, wherein,

激光测距仪，检测摄像头到裂缝的距离T并传输给处理器；Laser rangefinder, detects the distance T from the camera to the crack and transmits it to the processor;

摄像头，获取裂缝的正视图图像并传输给处理器；The camera acquires the front view image of the crack and transmits it to the processor;

处理器，依次对图像进行预处理，提取特征及分析，计算裂缝在图像中的最大和最小宽度，由距离T得到裂缝实际最大与最小宽度。The processor sequentially preprocesses the image, extracts features and analyzes it, calculates the maximum and minimum width of the crack in the image, and obtains the actual maximum and minimum width of the crack from the distance T.

在以上技术方案的基础上，优选的，所述图像预处理包括，图像的灰度化、图像中值滤波处理和图像的增强。进一步优选的，所述提取特征及分析包括图像的二值化处理、二值化图像去噪处理和裂缝方向判定。更进一步优选的，所述图像的二值化处理采用中值滤波方法。更进一步优选的，所述裂缝方向判定步骤包括，假设一副大小为M×N二值化的数字图像f(x,y)，其中M代表数字图像高度，N代表数字图像宽度，x代表数字图像中横坐标值，y代表数字图像中纵坐标值，On the basis of the above technical solutions, preferably, the image preprocessing includes image grayscale, image median filtering and image enhancement. Further preferably, the feature extraction and analysis include image binarization processing, binarized image denoising processing and fracture direction determination. Still further preferably, the binarization processing of the image adopts a median filtering method. Still further preferably, the crack direction determination step includes assuming a binary digital image f(x, y) with a size of M×N, where M represents the height of the digital image, N represents the width of the digital image, and x represents the digital image The abscissa value in the image, y represents the ordinate value in the digital image,

rr == maxmax {{ ΣΣ xx == 11 Mm ff (( xx ,, 11 )) ,, ΣΣ xx == 11 Mm ff (( xx ,, 22 )) ,, ΣΣ xx == 11 Mm ff (( xx ,, 33 )) ,, ...... ΣΣ xx == 11 Mm ff (( xx ,, NN )) }} maxmax {{ ΣΣ ythe y == 11 Mm ff (( 11 ,, ythe y )) ,, ΣΣ ythe y == 11 Mm ff (( 22 ,, ythe y )) ,, ΣΣ ythe y == 11 Mm ff (( 33 ,, ythe y )) ,, ...... ΣΣ ythe y == 11 Mm ff (( Mm ,, ythe y )) }}

当r>1时，判定裂缝为纵向裂缝；When r>1, it is determined that the crack is a longitudinal crack;

当0<r<1时，判定裂缝为横向裂缝。When 0<r<1, the fracture is judged to be a transverse fracture.

再进一步优选的，计算裂缝最大和最小宽度步骤包括，若判定裂缝为纵向裂缝，裂缝在图像中的最大宽度和最小宽度分别为，Still further preferably, the step of calculating the maximum and minimum width of the crack includes, if the crack is determined to be a longitudinal crack, the maximum width and the minimum width of the crack in the image are respectively,

DD. mm aa xx == mm aa xx {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }}

DD. mm ii nno == mm ii nno {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }} ;;

若判定裂缝为横向裂缝，裂缝在图像中的最大宽度和最小宽度分别为，If it is determined that the crack is a transverse crack, the maximum width and minimum width of the crack in the image are respectively,

DD. mm aa xx == maxmax {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }}

DD. mm ii nno == minmin {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }}

其中，Dmax代表裂缝最大宽度，Dmin代表裂纹最小宽度。Among them, D max represents the maximum crack width, and D min represents the minimum crack width.

最后，由距离T得到裂缝实际最大与最小宽度的步骤包括，Finally, the step of obtaining the actual maximum and minimum width of the crack from the distance T includes,

获取图像的宽度N，摄像头的水平视场角α，将距离T和裂缝在图像中的最大宽度和最小宽度代入下式得到裂缝实际最大与最小宽度，Obtain the width N of the image, the horizontal field of view α of the camera, and substitute the distance T and the maximum and minimum width of the crack in the image into the following formula to obtain the actual maximum and minimum width of the crack,

WW == 22 TT tt aa nno (( &alpha;&alpha; 22 )) NN ww

其中，W为裂缝的实际宽度，w为裂缝在图像中的宽度。Among them, W is the actual width of the crack, and w is the width of the crack in the image.

第二方面，本发明提供了一种裂缝宽度检测方法，包括以下步骤，In a second aspect, the present invention provides a crack width detection method, comprising the following steps,

S1，采用激光测距仪检测摄像头到裂缝的距离T并传输给处理器；S1, using a laser range finder to detect the distance T from the camera to the crack and transmit it to the processor;

S2，采用摄像头获取裂缝的正视图图像并传输给处理器；S2, adopting the camera to obtain the front view image of the crack and transmitting it to the processor;

S3，采用处理器依次对图像进行预处理，提取特征及分析，计算裂缝在图像中的最大和最小宽度，由距离T得到裂缝实际最大与最小宽度。S3, the processor is used to preprocess the image in turn, extract features and analyze, calculate the maximum and minimum width of the crack in the image, and obtain the actual maximum and minimum width of the crack from the distance T.

在以上技术方案的基础上，优选的，将激光测距仪和摄像头固定在支架上，其中，激光测距仪和摄像头中心点所在直线与待测裂缝所在平面平行，测试激光测距仪到待测裂缝所在平面的距离作为摄像头到裂缝的距离T。进一步优选的，将摄像头正对裂缝所拍到的图像作为裂缝的正视图图像。On the basis of the above technical scheme, preferably, the laser range finder and the camera are fixed on the bracket, wherein the straight line where the center point of the laser range finder and the camera is located is parallel to the plane where the crack to be measured is located, and the laser range finder is tested to the point where the crack is to be tested. Measure the distance of the plane where the crack is located as the distance T from the camera to the crack. Further preferably, the image captured by the camera facing the crack is used as the front view image of the crack.

本发明的裂缝宽度检测装置及其方法相对于现有技术具有以下有益效果：Compared with the prior art, the crack width detection device and method thereof of the present invention have the following beneficial effects:

(1)该检测方法能够避免人为主观因素造成的干扰，更加实时、精准、客观、高效；(1) The detection method can avoid the interference caused by human subjective factors, and is more real-time, accurate, objective and efficient;

(2)本发明的装置可以搭载在无人机上对道路和桥梁的裂缝进行检测，具有检测效率高、应用范围广的特点；(2) The device of the present invention can be mounted on an unmanned aerial vehicle to detect cracks in roads and bridges, and has the characteristics of high detection efficiency and wide application range;

(3)本发明的方法可以与现有的PC机以及ARM处理器便携式设备无缝对接，具有较好的移植性；(3) the method of the present invention can be seamlessly docked with existing PCs and ARM processor portable devices, and has good portability;

(4)裂缝检测装置，结构简单、成本低廉。(4) The crack detection device has simple structure and low cost.

附图说明Description of drawings

为了更清楚地说明本发明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发明的一些实施例，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 technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

图1为本发明裂缝宽度检测装置的结构示意图；Fig. 1 is the structural representation of crack width detecting device of the present invention;

图2为本发明裂缝宽度检测方法的工艺流程图；Fig. 2 is the process flow chart of crack width detection method of the present invention;

图3为本发明裂缝宽度检测装置的原理图。Fig. 3 is a schematic diagram of the crack width detecting device of the present invention.

具体实施方式detailed description

下面将结合本发明实施方式中的附图，对本发明实施方式中的技术方案进行清楚、完整地描述，显然，所描述的实施方式仅仅是本发明一部分实施方式，而不是全部的实施方式。基于本发明中的实施方式，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施方式，都属于本发明保护的范围。The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the implementation manners in the present invention, all other implementation manners obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

如图1所示，本发明的裂缝宽度检测装置，其包括激光测距仪1、摄像头2、支架3和处理器，激光测距仪1和摄像头2固定在支架3上，并分别与处理器信号连接。As shown in Figure 1, crack width detecting device of the present invention, it comprises laser range finder 1, camera 2, support 3 and processor, laser range finder 1 and camera 2 are fixed on the support 3, and respectively with processor signal connection.

激光测距仪1，检测摄像头2到裂缝的距离T并传输给处理器4。具体的，激光测距仪1和摄像头2中心点所在直线与待测裂缝所在平面平行，测试激光测距仪1到待测裂缝所在平面的距离，即可作为摄像头2到裂缝的距离T。The laser rangefinder 1 detects the distance T from the camera 2 to the crack and transmits it to the processor 4 . Specifically, the straight line where the center point of the laser range finder 1 and the camera 2 is parallel to the plane where the crack to be measured is located, and the distance T from the camera 2 to the crack is measured by measuring the distance from the laser range finder 1 to the plane where the crack to be measured is located.

摄像头2，获取裂缝的正视图图像并传输给处理器。具体的，将摄像头2正对裂缝所拍到的图像作为裂缝的正视图图像。The camera 2 acquires the front view image of the crack and transmits it to the processor. Specifically, the image captured by the camera 2 facing the crack is used as the front view image of the crack.

处理器，依次对图像进行预处理，提取特征及分析，计算裂缝在图像中的最大和最小宽度，由距离T得到裂缝实际最大与最小宽度。具体的，如图2所示，所述图像预处理包括，图像的灰度化、图像中值滤波处理和图像的增强。具体的，所述提取特征及分析包括图像的二值化处理、二值化图像去噪处理和裂缝方向判定。具体的，所述图像的二值化处理采用中值滤波方法。具体的，所述裂缝方向判定采用矩形的特征来判断，即矩形长宽比的方式来进行判断。步骤包括，假设一副大小为M×N二值化的数字图像f(x,y)，其中，M代表数字图像高度，N代表数字图像宽度，x代表数字图像中横坐标值，y代表数字图像中纵坐标值，The processor sequentially preprocesses the image, extracts features and analyzes it, calculates the maximum and minimum width of the crack in the image, and obtains the actual maximum and minimum width of the crack from the distance T. Specifically, as shown in FIG. 2 , the image preprocessing includes image grayscale, image median filter processing, and image enhancement. Specifically, the feature extraction and analysis include image binarization processing, binarization image denoising processing, and fracture direction determination. Specifically, the binarization processing of the image adopts a median filtering method. Specifically, the crack direction is judged by using the characteristics of a rectangle, that is, judging by the aspect ratio of a rectangle. The steps include assuming a digital image f(x, y) with a size of M×N binarization, where M represents the height of the digital image, N represents the width of the digital image, x represents the abscissa value in the digital image, and y represents the number The ordinate value in the image,

rr == maxmax {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }} maxmax {{ &Sigma;&Sigma; ythe y == 11 Mm ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 Mm ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 Mm ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 Mm ff (( Mm ,, ythe y )) }}

当r>1时，判定裂缝为纵向裂缝；When r>1, it is determined that the crack is a longitudinal crack;

当0<r<1时，判定裂缝为横向裂缝。When 0<r<1, it is determined that the fracture is a transverse fracture.

计算裂缝最大和最小宽度采用像素积分投影法，步骤包括，若判定裂缝为纵向裂缝，裂缝在图像中的最大宽度和最小宽度分别为，The pixel integral projection method is used to calculate the maximum and minimum widths of the cracks, and the steps include, if the cracks are determined to be longitudinal cracks, the maximum and minimum widths of the cracks in the image are respectively,

DD. mm aa xx == mm aa xx {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }}

DD. mm ii nno == mm ii nno {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }} ;;

若判定裂缝为横向裂缝，裂缝在图像中的最大宽度和最小宽度分别为，If it is determined that the crack is a transverse crack, the maximum width and minimum width of the crack in the image are respectively,

DD. mm aa xx == maxmax {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }}

DD. mm ii nno == minmin {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }}

其中，Dmax代表裂缝最大宽度，Dmin代表裂纹最小宽度。Among them, D max represents the maximum crack width, and D min represents the minimum crack width.

最后，由距离T得到裂缝实际最大与最小宽度，其方法是根据在成像过程中三角形相似的原理提出的，如图3所示，假设T为摄像头2到裂缝的距离；W为裂缝的实际宽度；α为摄像头2的水平视场角；N为所采集的图像的宽度；M为所采集的图像的高度；w为裂缝在图像中的宽度，h为裂缝在图像中的长度，W1为摄像头2的视角高度。根据成像过程当中三角形相似的原理，可得以下关系：Finally, the actual maximum and minimum width of the crack is obtained from the distance T. The method is proposed based on the principle of triangle similarity in the imaging process, as shown in Figure 3, assuming that T is the distance from the camera 2 to the crack; W is the actual width of the crack ; α is the horizontal field of view of camera 2; N is the width of the collected image; M is the height of the collected image; w is the width of the crack in the image, h is the length of the crack in the image, W1 is the camera 2 viewing angles. According to the principle of triangle similarity in the imaging process, the following relationship can be obtained:

WW hh == 22 WW 11 NN

其中， in,

由以上两式，可得： From the above two formulas, we can get:

其中获取裂缝在图像中的最大宽度Dmax和最小宽度Dmin代入上式中可得到裂缝最大的实际宽度和最小实际宽度值。The maximum and minimum actual widths of the cracks can be obtained by substituting the maximum width D max and minimum width D min of the crack in the image into the above formula.

以上所述仅为本发明的较佳实施方式而已，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.

Claims (10)

1.一种裂缝宽度检测装置，其包括激光测距仪(1)、摄像头(2)、支架(3)和处理器，激光测距仪(1)和摄像头(2)分别与处理器信号连接，其特征在于：1. a crack width detection device, it comprises laser range finder (1), camera (2), support (3) and processor, laser range finder (1) and camera (2) are connected with processor signal respectively , characterized by: 激光测距仪(1)和摄像头(2)固定在支架(3)上，其中，Laser range finder (1) and camera (2) are fixed on the bracket (3), wherein, 激光测距仪(1)，检测摄像头(2)到裂缝的距离T并传输给处理器；A laser range finder (1) detects the distance T from the camera (2) to the crack and transmits it to the processor; 摄像头(2)，获取裂缝的正视图图像并传输给处理器；The camera (2) acquires the front view image of the crack and transmits it to the processor; 处理器，依次对图像进行预处理，提取特征及分析，计算裂缝在图像中的最大和最小宽度，由距离T得到裂缝实际最大与最小宽度。The processor sequentially preprocesses the image, extracts features and analyzes it, calculates the maximum and minimum width of the crack in the image, and obtains the actual maximum and minimum width of the crack from the distance T. 2.如权利要求1所述的裂缝宽度检测装置，其特征在于：所述图像预处理包括，图像的灰度化、图像中值滤波处理和图像的增强。2 . The crack width detection device according to claim 1 , wherein the image preprocessing includes image grayscale, image median filter processing and image enhancement. 3 . 3.如权利要求2所述的裂缝宽度检测装置，其特征在于：所述提取特征及分析包括图像的二值化处理、二值化图像去噪处理和裂缝方向判定。3. The crack width detection device according to claim 2, characterized in that: said feature extraction and analysis include image binarization processing, binarized image denoising processing and crack direction determination. 4.如权利要求3所述的裂缝宽度检测装置，其特征在于：所述图像的二值化处理采用中值滤波方法。4. The crack width detection device according to claim 3, characterized in that: the binary processing of the image adopts a median filter method. 5.如权利要求3所述的裂缝宽度检测装置，其特征在于：所述裂缝方向判定步骤包括，假设一副大小为M×N二值化的数字图像f(x,y)，其中M代表数字图像高度，N代表数字图像宽度，x代表数字图像中横坐标值，y代表数字图像中纵坐标值，5. The crack width detection device according to claim 3, wherein: the crack direction determination step comprises, assuming a size of M * N binarized digital image f (x, y), wherein M represents The height of the digital image, N represents the width of the digital image, x represents the abscissa value in the digital image, y represents the ordinate value in the digital image, rr == maxmax {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }} maxmax {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }} 当r>1时，判定裂缝为纵向裂缝；When r>1, it is determined that the crack is a longitudinal crack; 当0<r<1时，判定裂缝为横向裂缝。When 0<r<1, it is determined that the fracture is a transverse fracture. 6.如权利要求5所述的裂缝宽度检测装置，其特征在于：计算裂缝最大和最小宽度步骤包括，若判定裂缝为纵向裂缝，裂缝在图像中的最大宽度和最小宽度分别为，6. The crack width detection device as claimed in claim 5, wherein: the step of calculating the maximum and minimum width of the crack comprises, if the crack is determined to be a longitudinal crack, the maximum width and the minimum width of the crack in the image are respectively, DD. mm aa xx == mm aa xx {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }} DD. minmin == minmin {{ &Sigma;&Sigma; ythe y == 11 NN ff (( 11 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 22 ,, ythe y )) ,, &Sigma;&Sigma; ythe y == 11 NN ff (( 33 ,, ythe y )) ,, ...... &Sigma;&Sigma; ythe y == 11 NN ff (( Mm ,, ythe y )) }} ;; 若判定裂缝为横向裂缝，裂缝在图像中的最大宽度和最小宽度分别为，If it is determined that the crack is a transverse crack, the maximum width and minimum width of the crack in the image are respectively, DD. maxmax == maxmax {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }} DD. mm ii nno == minmin {{ &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 11 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 22 )) ,, &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, 33 )) ,, ...... &Sigma;&Sigma; xx == 11 Mm ff (( xx ,, NN )) }} 其中，Dmax代表裂缝最大宽度，Dmin代表裂纹最小宽度。Among them, D max represents the maximum crack width, and D min represents the minimum crack width. 7.如权利要求6所述的裂缝宽度检测装置，其特征在于：由距离T得到裂缝实际最大与最小宽度的步骤包括，7. The crack width detecting device according to claim 6, characterized in that: the step of obtaining the actual maximum and minimum width of the crack from the distance T comprises, 获取图像的宽度N，摄像头(2)的水平视场角α，将距离T和裂缝在图像中的最大宽度和最小宽度代入下式得到裂缝实际最大与最小宽度，Obtain the width N of the image, the horizontal field of view α of the camera (2), and substitute the distance T and the maximum width and minimum width of the crack in the image into the following formula to obtain the actual maximum and minimum width of the crack, WW == 22 TT tt aa nno (( &alpha;&alpha; 22 )) NN ww 其中，W为裂缝的实际宽度，w为裂缝在图像中的宽度。Among them, W is the actual width of the crack, and w is the width of the crack in the image. 8.一种裂缝宽度检测方法，其特征在于：包括以下步骤，8. A crack width detection method, characterized in that: comprising the following steps, S1，采用激光测距仪(1)检测摄像头(2)到裂缝的距离T并传输给处理器；S1, using the laser range finder (1) to detect the distance T from the camera (2) to the crack and transmit it to the processor; S2，采用摄像头(2)获取裂缝的正视图图像并传输给处理器；S2, using the camera (2) to obtain the front view image of the crack and transmit it to the processor; S3，采用处理器依次对图像进行预处理，提取特征及分析，计算裂缝在图像中的最大和最小宽度，由距离T得到裂缝实际最大与最小宽度。S3, the processor is used to preprocess the image in turn, extract features and analyze, calculate the maximum and minimum width of the crack in the image, and obtain the actual maximum and minimum width of the crack from the distance T. 9.如权利要求8所述的裂缝宽度检测方法，其特征在于：将激光测距仪(1)和摄像头(2)固定在支架(3)上，其中，激光测距仪(1)和摄像头(2)中心点所在直线与待测裂缝所在平面平行，测试激光测距仪(1)到待测裂缝所在平面的距离作为摄像头(2)到裂缝的距离T。9. crack width detection method as claimed in claim 8, is characterized in that: laser range finder (1) and camera (2) are fixed on the support (3), wherein, laser range finder (1) and camera (2) The straight line where the center point is located is parallel to the plane where the crack to be measured is located, and the distance from the test laser range finder (1) to the plane where the crack is located is taken as the distance T from the camera (2) to the crack. 10.如权利要求8所述的裂缝宽度检测方法，其特征在于：将摄像头(2)正对裂缝所拍到的图像作为裂缝的正视图图像。10. The crack width detection method according to claim 8, characterized in that: the image captured by the camera (2) facing the crack is used as the front view image of the crack.
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