JP2018004389A - Crack analysis method and crack analysis system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a crack analysis method and a crack analysis system which allow a site worker to easily grasp a crack occurrence state.SOLUTION: A crack analysis method of one embodiment analyzes crack which occurs on a tunnel pit face. The crack analysis method comprises: a first step for acquiring an image G of the tunnel pit face, and performing binarization to the image G to a crack pixel P1 indicating a part where the crack occurs, and a non-crack pixel P2 indicating a part where no crack occurs; a second step for rotating the image G around an axis orthogonal to the image G to the vertical direction, and calculating a degree in which, an extension direction of the crack pixel P1 matches the vertical direction, for every rotation angle to the vertical direction; a third step for determining that, a direction to which rotation is performed to an opposite direction from the vertical direction by a rotation angle at which, the calculated degree is highest, is a direction where crack extends; and a fourth step for displaying the determined direction where the crack extends.SELECTED DRAWING: Figure 9

Description

  The present invention relates to a crack analysis method and a crack analysis system for a crack generated in an inspection object such as a rock mass or concrete.

  Various methods for analyzing a crack generated in an inspection object such as a bedrock or concrete have been conventionally known. As a conventional method, there is, for example, a method in which a site worker draws a crack generated in a face of a tunnel by a sketch at a construction site of the tunnel. Field workers generally grasp the state of cracks occurring in the face by looking at the face as a whole and sketching the face.

  Japanese Laid-Open Patent Publication No. 10-331575 describes a geological prediction method in front of a tunnel face and an image processing system for performing geological prediction, which are used when observing the tunnel face at a tunnel excavation site. . This image processing system includes a digital camera that captures an image of a face, an image memory that stores digital image data acquired by the digital camera, and an image processing arithmetic unit that performs image processing on the image data stored in the image memory And.

  The image processing calculation unit extracts a crack portion and a weathered weak portion from the image data based on the concentration distribution. The image processing calculation unit obtains a fractal dimension by performing a predetermined calculation on the extracted image data. The fractal dimension is used as a quantitative representation of the complexity of the structure such as undulations and cracks on the surface of the face in the grayscale image.

JP-A-10-331575

  In the above-described description of the crack by the sketch of the field worker, since the quality of the sketch varies depending on the skill level of the field worker, the accuracy of grasping the crack state varies. On the other hand, in the image processing system described in the above publication, an index related to the complexity of the irregularities on the surface of the face is output as a fractal dimension. Therefore, it is possible to output an index relating to the complexity of the surface of the face as a numerical value.

  However, since the field worker is trying to grasp the state of the crack as a whole as described above, there is a current situation that the output by the numerical value of the fractal dimension is not familiar to the field worker. In other words, the field worker cannot easily grasp the occurrence of cracks by looking at the output result of the fractal dimension. Therefore, it is required to output data that allows field workers to easily understand the state of cracks.

  An object of the present invention is to provide a crack analysis method and a crack analysis system in which a field worker can easily grasp the occurrence state of a crack.

  The crack analysis method according to the present invention is a crack analysis method for analyzing a crack generated in an inspection object, obtains an image of the inspection object, and the image includes a crack pixel indicating a portion where the crack is generated, and The first step of binarizing into non-cracked pixels indicating a portion where no crack has occurred, and for each rotation angle with respect to the reference direction while rotating the image around an axis perpendicular to the image with respect to the reference direction, The second step of calculating the degree that the extending direction of the crack pixel coincides with the reference direction, and the direction in which the calculated degree of rotation is rotated in the opposite direction from the reference direction by the highest rotation angle is determined as the direction in which the crack extends. And a fourth step for displaying the determined direction in which the crack extends.

  In the crack analysis method according to the present invention, the degree of coincidence of the extending direction of the crack pixel with respect to the reference direction is calculated for each rotation angle with respect to the reference direction while rotating the image. Then, a rotation angle with a high degree of coincidence is specified, and the direction rotated by the specified rotation angle in the opposite direction from the reference direction is determined as the direction in which the crack extends, and the direction is displayed. Therefore, by performing image processing for rotating the acquired image, it is possible to visually grasp the direction in which the crack extends in the inspection object. Therefore, it is possible to output data that can easily grasp the occurrence state of the crack to the field worker who manages the inspection object. Thus, since the direction in which the crack extends in the inspection object is displayed, the site worker can intuitively grasp the occurrence state of the crack.

  The second step is a step of dividing the image into a plurality of divided images, and a step of calculating a ratio of the number of divided images in which crack pixels extend from one end to the other end in the reference direction with respect to the total number of divided images. You may have. In this case, the degree of coincidence of the crack pixel extending direction with respect to the reference direction can be calculated as a numerical value. Since the calculated ratio is the ratio of the number of divided images in which crack pixels extend from one end to the other end in the reference direction, the algorithm is simpler than a predetermined calculation such as a fractal dimension. Therefore, since the calculation process in each step can be accelerated and the data output can be accelerated, data indicating the occurrence of cracks can be quickly output to the field worker.

  Further, the step of dividing and the step of calculating the ratio are performed a plurality of times while changing the number of divided images, the step of calculating the relational expression between the size and the ratio of the divided images, and the integral value of the relational expression as the degree. And a step of calculating. In this case, by calculating the degree to which the extending direction of the crack pixel matches the reference direction as an integral value, the direction in which the crack extends can be determined with higher accuracy. Therefore, the extending direction of the crack to be displayed can be output as data that matches the actual feeling of the field worker.

  In addition, after the third step, in a state where the image is rotated with respect to the reference direction by the rotation angle, the total number of pixels located on the imaginary line extending in the direction orthogonal to the reference direction is calculated as the number of crack pixels located on the imaginary line. The step of calculating the interval between cracks may be further provided by dividing by. Thus, by calculating the crack interval, the density of cracks occurring in the inspection object can be grasped. Therefore, it is possible to grasp the occurrence state of the crack with higher accuracy.

  In addition, the second step, the third step, and the fourth step are performed for each of the plurality of regions of the inspection object, and in the fourth step, the region that has the highest degree in the third step exceeds the first threshold value. Only the direction in which the crack extends may be displayed. In this case, the direction in which the crack extends is displayed only for the region where the crack pixels extend in a certain direction. Therefore, by selectively extracting a crack that needs to be grasped, the site worker can grasp the crack more reliably.

  Further, the second step, the third step, the fourth step, and the step of calculating the interval are performed for each of the plurality of regions of the inspection object, and in the fourth step, the interval calculated in the step of calculating the interval is the first interval. You may display the direction where a crack extends only about the area | region which is 2 threshold values or less. In this case, the direction in which the crack extends is displayed only in the region where the gap is narrow and the crack is formed at a higher density. Therefore, by selectively extracting a crack that needs to be grasped, the site worker can grasp the crack more reliably.

  The crack analysis system according to the present invention is a crack analysis system for analyzing a crack generated in an inspection object, obtains an image of the inspection object, and displays the image as a crack pixel indicating a portion where the crack is generated, and An image binarization unit that binarizes into non-cracked pixels indicating a portion where no crack has occurred, and a rotation angle with respect to the reference direction while rotating the image around an axis orthogonal to the image with respect to the reference direction. In addition, a degree calculation unit that calculates the degree that the extending direction of the crack pixel coincides with the reference direction, and a direction in which the crack extends a direction that is rotated in the opposite direction from the reference direction by the rotation angle with the highest degree of calculation. And a display unit that displays a direction in which the determined crack extends.

  In the crack analysis system according to the present invention, the degree calculation unit rotates the image and calculates the coincidence degree of the extending direction of the crack pixel with respect to the reference direction. The determination unit specifies a rotation angle with a high degree of coincidence, and determines a direction in which the specified rotation angle is rotated in the opposite direction from the reference direction as the direction in which the crack extends. Then, the display unit displays the direction in which the determined crack extends. Accordingly, the degree calculation unit rotates the image, and the determination unit determines the direction in which the crack extends, whereby the extension direction of the crack generated in the inspection object can be grasped. Therefore, it is possible to output data that can easily grasp the occurrence state of the crack to the field worker who manages the inspection object. Thus, since the direction in which the crack extends in the inspection object is displayed, the site worker can intuitively grasp the occurrence state of the crack.

  According to the present invention, an on-site worker can easily grasp the occurrence of a crack.

It is a block diagram which shows the crack analysis system which concerns on embodiment of this invention. It is a figure which shows the image data of the test target object (tunnel face) image | photographed and taken in with the camera. It is a figure which shows the image data which cut out a part of image data of FIG. It is a figure which shows the image which binarized the image data of FIG. 3 into the crack pixel and the non-crack pixel. (A) is a figure which shows the divided image obtained by dividing the image of FIG. 4 into four. (B) is a graph which shows the relationship between the magnitude | size of a divided image, and a connection rate. (A) is a figure which shows the divided image obtained by dividing the image of FIG. 4 into 9 parts. (B) is a graph which shows the relationship between the magnitude | size of a divided image, and a connection rate. (A) is a figure which shows the division | segmentation image obtained by dividing the image of FIG. 4 into 16. (B) is a graph which shows the relationship between the magnitude | size of a divided image, and a connection rate. It is a graph which shows the relationship between the magnitude | size of a divided image, and a connection rate. (A) is a figure which shows a crack pixel and a non-crack pixel when it rotates 50 degrees clockwise from a reference direction. (B) is a figure which shows the crack pixel and the non-crack pixel which are not rotated with respect to the reference direction. (C) is a figure which shows a crack pixel and a non-crack pixel when it rotates 20 degrees clockwise from a reference direction. It is a figure which shows the step which calculates the space | interval of a crack. It is a figure which shows the some area | region of a test object (tunnel face). It is a figure which shows the direction where the determined crack extends for every area | region. It is a figure which shows the step which displays the direction where a crack extends from each direction of FIG. It is a figure which shows the step which displays the direction where a crack extends following FIG. It is a flowchart which shows each step of the crack analysis method which concerns on embodiment of this invention.

  Hereinafter, embodiments of a crack analysis method and a crack analysis system according to the present invention will be described with reference to the drawings. In the following description, the same or corresponding elements are denoted by the same reference numerals, and redundant description is omitted.

  First, the crack analysis system according to the present embodiment will be described. FIG. 1 is a block diagram illustrating a crack analysis system 1 according to the present embodiment, and FIG. 2 is a diagram illustrating image data of a tunnel face T to be analyzed by the crack analysis system 1. The tunnel face T is, for example, a cracked rock, and the stability of the tunnel constructed in the tunnel face T is easily affected by the state of the crack. Therefore, it is important for performing tunnel construction or the like to appropriately evaluate the rock surface of the tunnel face T by grasping and managing the crack state of the tunnel face T. In the present embodiment, a crack analysis system 1 that analyzes a crack generated in the tunnel face T using the tunnel face T as an inspection object will be described.

  For example, the crack analysis system 1 provides technical support to a person in charge of the site who sketches a crack in the tunnel face T. That is, the crack analysis system 1 has a function of displaying the dominant direction of the crack of the tunnel face T (the direction in which the crack extends). It is possible to make a sketch based on this. Moreover, the dominant direction of the crack displayed by the crack analysis system 1 is easy to understand for the field worker, and can be substituted for the above sketch.

  As shown in FIG. 1, the crack analysis system 1 includes an image acquisition unit 2 that acquires a captured image of the tunnel face T, an image processing unit 10 that performs image processing of the captured image acquired by the image acquisition unit 2, and And a monitor 3 (display unit) for displaying an image related to the dominant direction of the crack generated by the image processing unit 10.

  The image acquisition unit 2 is a digital camera, for example, and acquires digital data of an image of the tunnel face T. Various types of image acquisition unit 2 can be used. The image acquisition unit 2 may include, for example, a camera that takes a silver halide photograph and a scanner, and various cameras that can acquire an image of the tunnel face T can be used.

  The monitor 3 displays a crack image generated by image processing performed by the image processing unit 10. The monitor 3 is a display of a personal computer, for example. As the monitor 3, various display devices can be used as long as they can display crack images.

  The image processing unit 10 can communicate with the image acquisition unit 2 and the monitor 3. The image processing unit 10 receives the digital data of the image of the tunnel face T acquired by the image acquisition unit 2. The image processing unit 10 includes an image binarization unit 11, an image extraction unit 12, a connection rate calculation unit 13, an image rotation unit 14, an angle detection unit 15, an interval calculation unit 16, and a display control unit 17. The image processing unit 10 is a general-purpose personal computer, for example, and includes a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory). Each function of the image processing unit 10 is realized by loading a program stored in the ROM into the RAM and executing it by the CPU.

  The image binarization unit 11 receives the digital data of the image of the tunnel face T, and defines the lower left A1, the lower right A2, and the top A3 with respect to the received digital data of the image as shown in FIG. To create an arc-shaped analysis region D. The outer edge of the analysis region D corresponds to the outer edge of the tunnel face T.

  The image binarization unit 11 performs black and white binarization on the image inside the analysis region D. In the present embodiment, the white pixel in FIG. 2 is a crack pixel P1 indicating a portion where the tunnel face T is cracked, and the black pixel in FIG. 2 is a non-crack pixel indicating a portion where the tunnel face T is not cracked. P2.

  As shown in FIG. 3, the image extraction unit 12 extracts an arbitrary part from the analysis region D generated by the image binarization unit 11. That is, the image extraction unit 12 extracts the region R of the tunnel face T from the image binarized by the image binarization unit 11. The region R shown in FIG. 3 is circular, but the shape and size of the region R extracted by the image extraction unit 12 are not limited to the example shown in FIG. 3 and can be changed as appropriate.

  Hereinafter, an example in which the region R is a square as illustrated in FIG. 4 will be described. The connection rate calculation unit 13 (degree calculation unit) calculates the connection rate in order to obtain the dominant direction of cracks in the tunnel face T. The connection rate indicates the continuity in the vertical direction (reference direction) of the crack in the region R extracted by the image extraction unit 12. For example, if the image G in the region R is composed of 20 × 20 pixels, the crack pixel P1 does not extend from one end (upper end) to the other end (lower end) in the vertical direction in the image G. The connection rate of the image G is 0. In FIG. 4, the crack pixel P <b> 1 and the non-crack pixel P <b> 2 have a square shape, but may have a shape other than a square, such as a rectangle.

  The connection rate calculation unit 13 divides the image G into a plurality of divided images B as shown in FIG. FIG. 5A shows an example in which the region R is divided into four (2 × 2) divided images B. The connection rate calculation unit 13 calculates the ratio of the number of divided images B in which crack pixels P1 extend from the upper end to the lower end with respect to the total number of divided images B. This ratio corresponds to the connection ratio.

  In the example shown in FIG. 5A, the divided image B in which the crack pixel P1 extends from the upper end to the lower end is only one upper left divided image B. The connection rate calculation unit 13 divides the image G into four (2 × 2) divided images B. The connection rate calculation unit 13 calculates the connection rate as 1/4, assuming that the total number of the divided images B is 4, and the number of the divided images B in which the crack pixels P1 extend from the upper end to the lower end is 1. As illustrated in FIG. 5B, the connection rate calculation unit 13 stores the relationship between the size of the divided image B and the connection rate. In the present embodiment, the size of the divided image B indicates the ratio of the number of pixels on one side of the divided image B to the number of pixels on one side of the image G (20). In the example shown in FIG. 10/20).

  As shown in FIG. 6A, the connection rate calculation unit 13 divides the image G into nine (3 × 3) divided images B. Then, the connection rate calculation unit 13 calculates the connection rate as 3/9, where the total number of the divided images B is 9, and the number of the divided images B in which the crack pixel P1 extends from the upper end to the lower end is 3. Thereafter, the connection rate calculation unit 13 stores a relationship between the size of the divided image B and the connection rate, as illustrated in FIG. At this time, the size of the divided image B is 1/3.

  As shown in FIG. 7A, the connection rate calculation unit 13 divides the image G into 16 (4 × 4) divided images B. At this time, the connection rate calculation unit 13 calculates the connection rate as 8/16, where the total number of the divided images B is 16, and the number of the divided images B in which the crack pixel P1 extends from the upper end to the lower end is 8. And the connection rate calculation part 13 memorize | stores the relationship between the magnitude | size of the divided image B, and a connection rate, as FIG.7 (b) shows.

  As described above, the connection rate calculation unit 13 divides the image G into a plurality of divided images B and calculates the connection rate a plurality of times while changing the number of divided images B. Then, as shown in FIG. 8, the connection rate calculation unit 13 is similar to an approximate expression represented by Y = AX + B (Y: connection rate, X: size of divided image B, A, B: coefficient), for example. Then, a relational expression between the size of the divided image B and the connection rate is calculated. The relational expression calculated by the connection rate calculation unit 13 is not limited to the linear expression as described above, and can be changed as appropriate. For example, the connection rate calculation unit 13 can use various relational expressions such as a linear approximation curve, a polynomial approximation curve, a logarithmic approximation curve, a power approximation curve, an exponential approximation curve, or a moving average.

  After calculating the relational expression as described above, the connection rate calculation unit 13 integrates the relational expression and calculates the area S of the graph shown in FIG. 8 as an integration value. The area S (integral value) indicates the degree to which the extending direction of the crack pixel P1 matches the vertical direction. That is, the larger the area S, the more cracks extend in the vertical direction, and the smaller the area S, the fewer cracks extend in the vertical direction (there are many cracks extending in other directions or cracks). It is less).

  As shown in FIG. 9, the image rotation unit 14 (degree calculation unit) rotates the image G in the region R extracted by the image extraction unit 12. The image rotation unit 14 rotates the image G around an axis orthogonal to the image G with respect to the vertical direction. The image rotation unit 14 rotates the image G clockwise or counterclockwise at every constant angle (for example, 5 ° or 10 °). Then, while the image rotation unit 14 rotates the image G, the connection rate calculation unit 13 described above determines the degree of integration of the crack pixel P1 in the vertical direction for each rotation angle with respect to the vertical direction. Calculate as

  FIG. 9B shows an example in which the image rotation unit 14 does not rotate the image G, FIG. 9A shows an example in which the image rotation unit 14 rotates the image G by 50 degrees clockwise, and FIG. An example in which the image rotation unit 14 rotates the image G by 20 degrees clockwise is shown. In these examples, the integration value (degree) calculated by the connection rate calculation unit 13 is small when the image G is rotated 50 ° clockwise (FIG. 9A), and when the image G is not rotated ( FIG. 9 (b)) is the largest, and the largest when the image G is rotated 20 ° clockwise (FIG. 9 (c)).

  The angle detection unit 15 (determination unit) detects the direction in which the crack of the image G extends from the integral value for each rotation angle described above. The angle detection unit 15 determines that the direction in which the calculated integral value is rotated in the opposite direction from the vertical direction by the rotation angle with the highest integral value is the direction in which the crack extends. In the example shown in FIGS. 9A to 9C, the angle detection unit 15 determines that the direction rotated counterclockwise from the vertical direction by 20 ° is the direction in which the crack extends.

  The interval calculation unit 16 calculates the interval between cracks after the angle detection unit 15 determines the direction in which the crack extends. For example, as shown in FIG. 9C, when the integral value (degree) becomes the largest when the image G is rotated 20 ° clockwise, the image G is rotated clockwise by 20 ° in the vertical direction. In this state, the crack interval is calculated.

  Specifically, as shown in the example of FIG. 10, in the image G rotated clockwise by 20 °, the interval calculation unit 16 is on an imaginary line L extending in the left-right direction (the orthogonal direction of the up-down direction). By dividing the total number of pixels (pixels) positioned by the number of crack pixels P1 positioned on the virtual line L, the crack interval is calculated.

  In the example shown in FIG. 10, the interval calculation unit 16 calculates the number of crack pixels P1 for each virtual line L extending in the left-right direction. The numerical value on the right side of the image G in FIG. 10 indicates the calculated number of crack pixels P1. Thus, after calculating the number of crack pixels P1 for all virtual lines L, the interval calculation unit 16 calculates an average value (or a maximum value) of the number of crack pixels P1.

  In the example of FIG. 10, the interval calculation unit 16 sets the total number of pixels located on the virtual line L extending in the left-right direction to 20, and sets the average value of the crack pixels P1 located on the virtual line L to 2.6. “7.7” obtained by dividing 20 by 2.6 is calculated as a crack interval. When dividing 20 by the maximum value of the crack pixel P1 located on the virtual line L, the interval calculation unit 16 calculates “5.0” obtained by dividing 20 by 4 as the crack interval.

  The display controller 17 displays on the monitor 3 the direction in which the crack determined by the angle detector 15 extends. The display control unit 17 displays the direction in which the crack extends for each region R (image G) extracted by the image extraction unit 12. Specifically, as shown in FIG. 11, when each region R has a square shape, the display control unit 17 indicates the direction in which the crack extends for each region R as a line segment N.

  The direction in which the line segment N extends indicates the dominant direction of the crack determined by the angle detection unit 15, and the length of the line segment N indicates the above-described integrated value (degree). That is, the longer the length of the line segment N, the stronger the continuity of cracks in the dominant direction.

  In addition, the display control unit 17 performs the line segment N (a crack is generated only on the region R in which the integral value (degree) exceeds the first threshold value and the interval calculated by the interval calculation unit 16 is equal to or less than the second threshold value. (Extending direction) is displayed. In FIG. 11, a region R in which the line segment N is not displayed is a region R whose integrated value (degree) is equal to or smaller than the first threshold value or whose interval calculated by the interval calculation unit 16 is larger than the second threshold value. It is.

  The first threshold value described above indicates a threshold value for the strength of continuity of cracks for displaying the direction in which cracks extend, and the second threshold value indicates a threshold value for the interval (density) of cracks for displaying the direction in which cracks extend. ing. The first threshold value and the second threshold value are both set values and can be changed as appropriate.

  After displaying the line segment N as described above, the display control unit 17 erases the image of the tunnel face T and leaves only the outer edge of the analysis region D and the line segment N as shown in FIG. State. Then, as shown in FIG. 13, the display control unit 17 compares the continuity of cracks and the dominant direction between the plurality of adjacent regions R in the line segment N. Thereafter, the display control unit 17 smoothly connects the plurality of line segments N having high continuity and the plurality of line segments N having similar predominance directions with a curve C.

  After generating the curve C as described above, the display control unit 17 deletes the line segment N and leaves only the outer edge of the analysis region D and the curve C, as shown in FIG. A sketch image of the crack of the tunnel face T is obtained. Thus, in the crack analysis system 1, since the sketch image of the crack of the tunnel face T can be obtained by the display control unit 17, it is possible to save the labor of the site worker to draw the sketch.

  In addition, since the sketch image generated by the display control unit 17 is automatically displayed rather than by the hand of the field worker, there is no variation in the quality of the sketch of the tunnel face T. Therefore, it is possible to eliminate the variation in accuracy that can be caused by grasping the crack state of the tunnel face T.

  Next, a crack analysis method according to this embodiment will be described. FIG. 15 is a flowchart illustrating an example of a crack analysis method using the crack analysis system 1. Below, the example which analyzes the crack which has arisen in the tunnel face T which is a test object shown by FIG. 2 is demonstrated.

  First, the crack analysis system 1 acquires an image of the tunnel face T by the image acquisition unit 2. At this time, the image acquisition unit 2 acquires digital data of the image of the tunnel face T, and the image processing unit 10 receives the digital data acquired by the image acquisition unit 2 (step S1).

  Next, the image binarization unit 11 binarizes the image of the tunnel face T into a crack pixel P1 and a non-crack pixel P2 (first step). Specifically, the image binarization unit 11 creates an analysis region D for the received digital data, and performs black and white binarization on the image inside the analysis region D (step S2).

  Subsequently, the image extraction unit 12 divides the analysis region D generated by the image binarization unit 11 into a plurality of regions R. Then, the image extraction unit 12 extracts an arbitrary portion from the plurality of divided regions R, that is, extracts the region R of the tunnel face T (step S3). The connection rate calculation unit 13 calculates the degree to which the extending direction of the crack pixel P1 matches the vertical direction with respect to the region R extracted by the image extraction unit 12. At this time, the connection rate calculation unit 13 divides the image G into a plurality of divided images B, calculates the connection rate, calculates a relational expression between the size of the divided image B and the connection ratio, and an integral value (degree of the relational expression). ) Is calculated (step S4).

  Step S4 described above is executed while rotating the image G by the image rotating unit 14 by 180 ° (90 ° clockwise and 90 ° counterclockwise) with respect to the vertical direction. Specifically, the integral value is calculated while rotating the image G from the vertical direction (reference direction) clockwise by a certain angle, and after 90 degrees clockwise is calculated, the integral value is calculated. The integral value is calculated while rotating a certain angle counterclockwise from the direction, and all the angles end after calculating the integral value by rotating 90 ° counterclockwise.

  Therefore, the process proceeds from step S4 to step S5, and if it is determined in step S5 that all angles are not finished (NO in step S5), the process proceeds to step S6, and the image rotation unit 14 displays the image G. Rotate a certain angle. Then, the process proceeds to step S4, and the integral value (degree) is calculated again (second step).

  If it is determined in step S5 that all angles have been completed (YES in step S5), the angle detection unit 15 uses the plurality of integral values obtained through the plurality of steps S4 to crack the image G. Detects the direction in which. At this time, the angle detection unit 15 determines that the direction in which the crack is extended is the direction rotated in the opposite direction from the vertical direction by the rotation angle at which the integral value obtained in Step S4 is the highest (Step S7, No. 1). 3 steps).

  Next, the interval calculation unit 16 calculates the interval between cracks. As described above, the interval calculation unit 16 divides the total number of pixels located on the virtual line L by the number of crack pixels P1 located on the virtual line L in the image G of the region R, thereby generating cracks. The interval is calculated (step S8).

  Subsequently, the process proceeds to step S9, and it is determined whether or not all the regions R have been completed, that is, whether or not the process of steps S4 to S8 has been completed for all the regions R. If it is determined in step S9 that all regions R have not ended (NO in step S9), the process returns to step S3, the image extraction unit 12 extracts another region R, and a series of steps S4 to S8. Do the journey.

  On the other hand, if it is determined in step S9 that all the regions R have been completed (YES in step S9), the display control unit 17 performs display control of the crack image displayed on the monitor 3. At this time, as shown in FIG. 11 to FIG. 14, the display control unit 17 indicates the line segment N for each region R, and leaves only the outer edge of the analysis region D and the line segment N, and displays a plurality of lines on the curve C. A sketch image of a crack is generated by smoothly connecting the segment N and deleting the segment N (step S10). And the display control part 17 displays the produced | generated sketch image on the monitor 3 (step S11, 4th step), and a series of processes are completed.

  Next, effects obtained from the crack analysis method and the crack analysis system 1 according to the present embodiment will be described.

  In the crack analysis method according to the present embodiment, as shown in FIG. 9, the image G is rotated, and the degree of coincidence of the extending direction of the crack pixel P1 with respect to the vertical direction is calculated for each rotation angle with respect to the vertical direction. . And the rotation angle with the said high degree of coincidence is specified, the direction rotated by the specified rotation angle from the up-down direction to the opposite direction is determined as the direction in which the crack extends, and the direction is displayed. Therefore, by performing image processing for rotating the acquired image G, it is possible to grasp the direction in which the crack extends in the tunnel face T.

  Therefore, it is possible to output data that allows the operator of the site managing the tunnel face T to easily grasp the occurrence state of the crack. Thus, since the direction in which the crack extends in the tunnel face T is displayed, the site worker can intuitively grasp the occurrence state of the crack.

  In addition, as shown in FIGS. 5 to 7, the second step described above includes a step of dividing the image G into a plurality of divided images B, and crack pixels P <b> 1 from the upper end to the lower end with respect to the total number of the divided images B. Calculating a ratio (connection rate) of the number of extended divided images B. Therefore, the degree of coincidence of the extending direction of the crack pixel P1 with respect to the vertical direction can be calculated as a numerical value.

  Further, since the ratio (connection ratio) calculated above is the ratio of the number of the divided images B in which the crack pixel P1 extends from the upper end to the lower end, the algorithm is simpler than a predetermined calculation such as a fractal dimension. It is. Therefore, the calculation process in each step can be speeded up and the data output can be speeded up, so that the data indicating the crack occurrence state can be quickly outputted to the field worker.

  Further, the above-described division step and the step of calculating the ratio (connection rate) are performed a plurality of times while changing the number of division images B, and as shown in FIG. And a step of calculating an integral value of the relational expression as the above-described degree. Therefore, by calculating the degree to which the extending direction of the crack pixel P1 coincides with the vertical direction as an integral value, the direction in which the crack extends can be determined with higher accuracy. Therefore, the extending direction of the crack to be displayed can be output as data that matches the actual feeling of the field worker.

  As shown in FIGS. 9C and 10, after the third step described above, the image G is rotated in the vertical direction by the rotation angle at which the calculated integral value is the highest, that is, the most By dividing the total number of pixels located on the virtual line L extending in the left-right direction by the number of crack pixels P1 located on the virtual line L in a state where the crack pixel P1 extends in the vertical direction, The step of calculating the interval is provided. Thus, the density of cracks occurring at the tunnel face T can be grasped by calculating the crack interval. Therefore, it is possible to grasp the occurrence state of the crack with higher accuracy.

  As shown in FIG. 11, the second step, the third step, and the fourth step described above are performed for each of the plurality of regions R of the tunnel face T, and the fourth step is the highest in the third step. Only the region R where the integral value exceeds the first threshold value indicates the direction in which the crack extends. Therefore, the direction in which the crack extends is displayed only in the region R in which the crack pixels P1 extend in a certain direction. Therefore, by selectively extracting a crack that needs to be grasped, the site worker can grasp the crack more reliably.

  The second step, the third step, the fourth step, and the step of calculating the interval are performed for each of the plurality of regions R of the tunnel face T. In the fourth step, the interval calculated in the step of calculating the interval is The direction in which the crack extends is displayed only for the region that is equal to or less than the second threshold value. Therefore, the direction in which the crack extends is displayed only in the region R where the gap is narrow and the crack is formed at a higher density. Therefore, by selectively extracting a crack that needs to be grasped, the site worker can grasp the crack more reliably.

  In the crack analysis system 1 according to the present embodiment, as illustrated in FIG. 9, the image rotation unit 14 rotates the image G, and the connection rate calculation unit 13 extends in the extending direction of the crack pixel P1 with respect to the vertical direction. The degree of coincidence is calculated. The angle detection unit 15 specifies a rotation angle with a high degree of coincidence, and determines that the direction in which the specified rotation angle is rotated in the opposite direction from the vertical direction is the direction in which the crack extends. Then, the monitor 3 displays the direction in which the determined crack extends. Therefore, the image rotation unit 14 rotates the image G, and the angle detection unit 15 determines the direction in which the crack extends, whereby the extension direction of the crack generated in the tunnel face T can be grasped. Therefore, the same effect as the crack analysis method described above can be obtained.

  As mentioned above, although embodiment of this invention was described, this invention is not limited to the above-mentioned embodiment, It deform | transformed in the range which does not change the summary described in each claim, or applied to others It may be a thing. That is, the present invention can be variously modified without departing from the scope of the claims.

  For example, in the above-described embodiment, an example has been described in which the connection rate calculation unit 13 calculates the connection rate to calculate the degree to which the extending direction of the crack pixel P1 matches the vertical direction. However, the method of calculating the degree that the extending direction of the crack pixel P1 coincides with the vertical direction may be executed by means other than the connection rate. Further, the connection rate calculation unit 13 may not calculate the above-described integral value. Furthermore, in the above-described embodiment, the example in which the reference direction is the vertical direction has been described, but a direction other than the vertical direction may be set as the reference direction.

  In the above-described embodiment, the example in which the analysis region D has an arc shape including the lower left A1, the lower right A2, and the apex A3 has been described. However, the shape of the analysis region D is not limited to the arc shape and can be changed as appropriate. It is.

  In the above-described embodiment, the display control unit 17 generates a line segment N and generates a curve C connecting the plurality of line segments N, thereby displaying a sketch image of the crack of the tunnel face T on the monitor 3. An example was described. However, the method of displaying the direction in which the crack extends is not limited to the above example, and can be changed as appropriate. For example, the direction in which the crack extends, the continuity of the crack, and the interval between the cracks may be numerically displayed on the monitor 3.

  In the above-described embodiment, the example in which the inspection target of the crack analysis system 1 and the crack analysis method is the tunnel face T has been described. However, the crack analysis system 1 and the crack analysis method can be applied to other rock masses such as a dam body, and can also be applied to other rock masses such as concrete.

DESCRIPTION OF SYMBOLS 1 ... Crack analysis system, 2 ... Image acquisition part, 3 ... Monitor (display part), 10 ... Image processing part, 11 ... Image binarization part, 12 ... Image extraction part, 13 ... Connection rate calculation part (degree calculation part) ), 14... Image rotation unit (degree calculation unit), 15. Angle detection unit, 16. Interval calculation unit, 17. Display control unit, A 1 ... lower left, A 2 ... lower right, A 3 ... top, B ... divided image, C ... curve, D ... analysis region, G ... image, L ... virtual line, N ... line segment, P1 ... cracked pixel, P2 ... non-cracked pixel, R ... region, S ... area, T ... tunnel face (inspection object) ).

Claims (7)

A crack analysis method for analyzing a crack generated in an inspection object,
A first step of acquiring an image of the inspection object and binarizing the image into a crack pixel indicating a portion where the crack is generated and a non-crack pixel indicating a portion where the crack is not generated;
Secondly, the degree of extension of the crack pixel coincides with the reference direction at each rotation angle with respect to the reference direction while rotating the image about an axis orthogonal to the image with respect to the reference direction. Steps,
A third step of determining, as the direction in which the crack extends, a direction rotated in the opposite direction from the reference direction by the rotation angle having the highest calculated degree;
A fourth step of displaying a direction in which the determined crack extends;
A crack analysis method comprising: The second step includes
Dividing the image into a plurality of divided images;
Calculating a ratio of the number of the divided images in which the crack pixels extend from one end to the other end in the reference direction with respect to the total number of the divided images;
The crack analysis method of Claim 1 which has these. The step of dividing and the step of calculating the ratio are performed a plurality of times while changing the number of the divided images.
Calculating a relational expression between the size of the divided image and the ratio;
Calculating an integral value of the relational expression as the degree;
The crack analysis method according to claim 2, further comprising: After the third step,
In a state where the image is rotated by the rotation angle with respect to the reference direction, the total number of the pixels located on the imaginary line extending in a direction orthogonal to the reference direction is the number of crack pixels located on the imaginary line. Further comprising the step of calculating the spacing of the cracks by dividing by
The crack analysis method as described in any one of Claims 1-3. The second step, the third step, and the fourth step are performed for each of a plurality of regions of the inspection object,
In the fourth step, the direction in which the crack extends is displayed only for the region in which the degree that is the highest in the third step exceeds the first threshold.
The crack analysis method as described in any one of Claims 1-4. The second step, the third step, the fourth step, and the step of calculating the interval are performed for each of a plurality of regions of the inspection object,
In the fourth step, the direction in which the crack extends is displayed only for the region in which the interval calculated in the step of calculating the interval is equal to or less than a second threshold value.
The crack analysis method according to claim 4. A crack analysis system for analyzing a crack generated in an inspection object,
An image binarization unit that acquires an image of the inspection object and binarizes the image into a crack pixel indicating a portion where the crack is generated and a non-crack pixel indicating a portion where the crack is not generated When,
A degree calculation for calculating the degree to which the extending direction of the crack pixel matches the reference direction at each rotation angle with respect to the reference direction while rotating the image about an axis orthogonal to the image with respect to the reference direction. And
A determination unit that determines a direction in which the crack is extended as a direction rotated in the opposite direction from the reference direction by the rotation angle with the highest degree calculated;
A display for displaying a direction in which the determined crack extends;
Crack analysis system with