KR101848067B1 - Method for detecting concrete neutralization zone using digital image processing - Google Patents

Abstract

The present invention relates to a technology for determining whether or not concrete is neutralized, and more specifically, to a detection method of a concrete neutralization region using a digital image processing in which objective detection is possible without subjectivity by detecting the neutralized region using the digital image obtained by spraying a phenolphthalein solution on the neutralized concrete.

Description

TECHNICAL FIELD The present invention relates to a concrete neutralization zone detection method using digital image processing,

The present invention relates to a technique for determining the neutralization of concrete, and more particularly, to a method for determining the neutralization degree of concrete by using a digital image obtained by spraying a phenolphthalein solution on concrete subjected to carbonation, The present invention relates to a method for detecting a concrete neutralization region.

Structures made of reinforced concrete domestically have undergone a lot of aging to evaluate the durability life of structures and to predict durability. Factors affecting concrete durability include salt, carbonation, and sulfate. Neutralization of concrete by double carbonation accelerates the corrosion of reinforcing steel in reinforced concrete structure, thereby reducing the durability of reinforced concrete structure.

Carbonation of concrete means that the calcium hydroxide (Ca (OH) ₂ ) generated through the hydration reaction of cement and water reacts with atmospheric CO ₂ to become calcium carbonate (CaCO ₃ ) as follows.

_{Ca (OH) 2 + CO 2} → CaCO 3 + H 2 O

When the concrete surrounding the reinforcing bar is neutralized by the carbonation reaction and the water and the air penetrate through the neutralization part, the reinforcing bar becomes the ferric oxide to the ferric oxide and the red rust is generated. As the steel corrodes, the volume expands, cracks occur in the concrete, and the strength and durability of the structure are lost due to the collapse of the coating of the concrete.

Therefore, the determination of the neutralization of the concrete is a very important problem in relation to the calculation of the life of the concrete structure. Although methods such as phenolphthalein method, differential thermogravimetric analysis method, and X-ray diffraction method are known as methods for determining the degree of neutralization of such concrete, in general, methods that are most commonly used in the field are methods Phenolphthalein method.

The phenolphthalein method is a method in which an alcohol solution of 1% phenolphthalein is applied to the measurement cross section of the concrete to determine that the part colored with purple is not neutralized and the part not colored with purple is regarded as neutralized part. Five areas are measured and the average value is rounded up to the unit of mm. At this time, the area fading after the coloring is regarded as the neutralization area.

According to KS F 2596 (Measuring Method of Depth of Concrete Carbonation Depth), it is judged that the part which does not show purple color is sprayed with phenoptthalene solution, and the neutralization depth is measured mainly by visual observation until now. Therefore, there is a problem that the reliability of measurement is low due to a large measurement error because the measurement result may vary depending on the measurer.

Therefore, there is a need to develop a new method for increasing the reliability by lowering the measurement error when measuring the depth of neutralization by the phenolphthalein method.

As a result of efforts to solve the above problems, the inventor of the present invention has completed the present invention by developing a technique in which the area of concrete subjected to neutralization can be detected by a computer without involving the subject of the measurer.

Therefore, the object of the present invention is to provide a method for treating a carbonated concrete, which comprises applying a phenolphthalein solution to a cross section of a concrete to be neutralized and treating the digital image using a computerized image processing technique, And to provide a concrete neutralization region detection method using digital image processing that can be detected by minimizing objectively error.

It is another object of the present invention to provide a concrete neutralization region detection method using digital image processing that is easy to further analyze, such as an accurate boundary where carbonation proceeds and an increase amount of a region.

The objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

In order to accomplish the objects of the present invention, the present invention provides a method for measuring a neutralization zone, comprising: obtaining a measurement specimen from a concrete structure to detect a neutralization zone; Treating the obtained measurement specimen with a phenolphthalein solution; A photographing step of photographing the entire surface of the specimen including the discolored area by the phenolphthalein to obtain a color image; And an image processing step of detecting a neutralized region from the color image.

In a preferred embodiment, the image processing step includes a gray image obtaining step of obtaining a gray image from the color image; And a primary detection step of processing the obtained gray image to obtain a primary color change area.

In a preferred embodiment, the image processing step further includes a secondary detection step of calculating a convex hull of the primary color change area to obtain a secondary color change area.

In a preferred embodiment, the gray image obtaining step is performed by extracting an image composed of only the brightness of G (green) from the color image.

In a preferred embodiment, the primary detecting step comprises the steps of converting the gray image into a monochrome image through a binarization method, inverting the monochrome image to obtain a primary inverse monochrome image, And calculating the number of erroneously detected portions that have not been removed in the second-order inverted monochrome image obtained by second-inverting the entire image from which the erroneously detected portion has been removed.

In a preferred embodiment, the secondary detecting step comprises calculating an outermost polygon (convex hull) formed by the white pixels in the secondary inverse monochrome image obtained in the primary detecting step, And determining whether the detected portion exists inside the outermost polygon.

In a preferred embodiment, the image processing step further includes a confirmation step of confirming the neutralization area from the primary color change area obtained in the primary detection step or the secondary color change area obtained in the secondary detection step.

In a preferred embodiment of the present invention, the checking step includes a third step of inverting the image including the primary color change area or the secondary color change area to obtain a third inverse monochrome image, converting the third inverse monochrome image into a color image And displaying the outermost pixels of the primary color change area or the secondary color change area in black or white in the color image.

According to the present invention, it is possible to automatically detect the neutralization region of the carbonated concrete without the intervention of the measurer, thereby eliminating the possibility of different measurement results depending on the measurer, An additional analysis such as an increase in the area can be easily performed.

Although the present invention has been fully described by way of example with reference to the accompanying drawings, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, Of course.

1A is a color image of a measurement specimen treated with a phenolphthalein solution, FIG. 1B is an RGB brightness value of each pixel in the portion shown in FIG. 1A, FIG. 1C is a G Green ").≪ / RTI >
FIG. 2A shows a monochrome image obtained by binarizing the gray image shown in FIG. 1C, FIG. 2B shows a first inverse monochrome image in which monochrome images are inverted, and FIG. FIG. 2D shows an image from which a wrongly detected portion is removed, FIG. 2D shows an image from which a wrongly detected portion existing outside the primary inverse monochrome image is removed, FIG. 2E shows an image obtained by inverting the image shown in FIG. FIG. 2F shows an image obtained by assigning a unique number to each region detected as white in the image shown in FIG. 2D.
FIG. 3A shows a conceptual diagram of an outermost polygon formed by a set of points used in the secondary detection step, and FIG. 3B shows an image in which a wrongly detected portion inside the outermost polygon is modified.
FIG. 4A shows an image obtained by reversing the image shown in FIG. 3B in order to display the area where carbonation proceeds, and FIG. 4B shows an image in which the carbonated part is detected and an original image .
Figs. 5A, 6A, 7A and 8A show color images obtained in the photographing step, and Figs. 5B, 6B, 7B and 8B show images obtained after the image processing step.
9a to 9c show gray images extracted from the color image with the brightness of only R (red), G (green), and B (blue), respectively.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprising" or "having ", and the like, are intended to specify the presence of stated features, integers, steps, operations, elements, parts, or combinations thereof, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, or combinations thereof.

The terms first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the meaning of the context in the relevant art and, unless expressly defined in the present invention, are to be interpreted as an ideal or overly formal sense Do not.

Hereinafter, the technical structure of the present invention will be described in detail with reference to the accompanying drawings and preferred embodiments.

However, the present invention is not limited to the embodiments described herein but may be embodied in other forms. Like reference numerals used to describe the present invention throughout the specification denote like elements.

The technical feature of the present invention is that the computer can automatically detect the neutralization region of the concrete in which carbonation has proceeded, thereby eliminating the possibility of different measurement results depending on the measurer, And a method of detecting a concrete neutralization region using digital image processing.

Accordingly, the method for detecting a concrete neutralization zone of the present invention comprises the steps of: obtaining a measurement specimen from a concrete structure to be detected as a neutralization zone; Treating the obtained measurement specimen with a phenolphthalein solution; A photographing step of photographing the entire surface of the specimen including the discolored area by the phenolphthalein to obtain a color image; And an image processing step of detecting a neutralization area from the color image.

Here, the image processing step is intended to further improve the detection performance of the area where carbonation proceeds, and after the phenolphthalein solution is sprayed on the measuring section of the concrete structure for measuring the degree of neutralization, carbonization proceeds in the captured color image, Is not changed and carbonation is not progressed, so that the portion having alkalinity is similar to purple color, and purple color and green are complementary color characteristics. In other words, by detecting the area where carbonation does not progress from the photographed color image first, and carbonation is promoted from the surface of the concrete exposed to carbon dioxide, the part that is wrongly detected in the first detection is called the convex hull, The detection performance can be improved and the neutralization region where the carbonation has progressed finally can be detected.

First, the image processing step includes a gray image obtaining step of obtaining a gray image from a color image; And a primary detection step of processing the obtained gray image to obtain a primary color change area. The second discoloration region obtained by calculating the outermost polygon (convex hull) of the first discoloration region and / or the second discoloration region obtained in the first discoloration region or the second discoloration region obtained in the first discoloration region, And a confirmation step of confirming the neutralization region from the region.

In particular, in the gray image acquisition step, the gray image is obtained by extracting the image of only the G (green) brightness from the color image. The reason for extracting only the G image is that the green (G) is close to the purple and complementary colors. Due to this relationship, the G image is not carbonated as compared to other images, and the brightness of the purple part appears dark.

 The first detecting step includes converting the gray image into a monochrome image through a binarization method, inverting the monochrome image to obtain a first inverted monochrome image, removing a wrongly detected portion of the first inverted monochrome image, And calculating the number of erroneously detected portions that can not be removed from the second-order inverse monochrome image obtained by second-inverting the entire image from which the detected portion has been removed.

In this case, the black and white image is obtained by converting the gray image through the binarization method. In the converted black and white image, the portion where the carbonation progresses is white, and the portion that is not progressed is black. Here, the binarization is a general method of extracting an object to be extracted from an image from a background and other objects. The binarization is a method of extracting pixels having various brightness values (0 to 255) The brightness value is changed to white (1) and black (0). Methods for determining the threshold value for binarization have been proposed by several researchers. In this invention, the method proposed by Otsu is used. This method assumes that the distribution of brightness values in the brightness histogram of the image is two classes, Finds a reference value that minimizes dispersion and sets this value as a threshold value for binarization.

The second detecting step may include a step of calculating an outermost polygon (convex hull) formed by the white pixels in the second-order inverted monochrome image obtained in the first-order detecting step, And determining whether or not the data is present in the data area. In the mathematical sense, the outermost polygon (minimum convex set) is defined as the minimum convex set containing points in arbitrary dimension, and the geometrical meaning is defined as the outermost convex polygon. Using the quickhull method proposed by Barber et al. Can be calculated.

In the checking step, a third inverted black-and-white image is obtained by inverting the image including the primary color change area or the secondary color change area three-dimensionally, a third inverted black-and-white image is converted into a color image, Or displaying the outermost pixels of the secondary color change area in black or white.

Example 1

1. Steps to Obtain a Measurement Specimen

A concrete specimen with a width of 10 cm and a depth of 3.6 cm was obtained perpendicular to the surface by drilling the wall of the concrete building to detect the neutralization zone.

2. Process for treating phenolphthalein solution

A 1% alcohol solution of phenolphthalein was sprayed on the test specimen.

3. Shooting steps

The measurement specimen was photographed to obtain a color image of the entire surface including the discolored area of the measurement specimen.

4. Image processing steps

An image processing procedure capable of automatically detecting a part where carbonation proceeds from a color image of a measurement specimen through a computer was performed as shown in FIGS. 1A to 4B.

(1) Gray image acquisition step

As shown in FIG. 1A, when a color image of a measurement specimen processed with the phenolphthalein solution is input, the RGB brightness values of the portion shown in FIG. 1A are displayed as R (red), G (green), and B As shown in FIG. 1C, an image having brightness of only G is extracted from the color image. 1C, it can be seen that the color image is converted into the gray image by extracting the image having the brightness of G only.

(2) Primary detection step

① Steps to convert to black and white image

As shown in FIG. 2A, the gray image of FIG. 1C is converted to a monochrome image by a binarization method. In the black and white image, the portion where carbonation proceeds is white, and the portion that is not progressed is black. Here we use the method proposed by Otsu. On the other hand, it is difficult to precisely detect a desired object or region using only a general binarization technique, and thus it can be seen that the portion where carbonation does not proceed is also incorrectly detected as a carbonated region in FIG.

② Step to obtain the first inverse monochrome image

In order to precisely detect the portion where carbonation did not proceed, the black-and-white image was inverted to obtain the first-order inverted black-and-white image shown in FIG. 2B. In the first reversed black and white image, the portion where carbonation does not proceed is white.

③ Removing the wrongly detected part

(Soille, P < / RTI > developed by Soille) to remove holes (erroneously detected portions) present in the detected region (white) as shown in the primary inverse monochrome image shown in FIG. This method converts white pixels surrounded by white, which are recognized as objects, into white). It can be confirmed that erroneously detected portions surrounded by white are removed as shown in FIG. 2C. However, pixels attached to the boundary can not be detected accurately by this method, and erroneously detected white pixels surrounded by black pixels are also impossible to remove.

Therefore, as shown in FIG. 2D, after calculating the respective areas in the additional detected areas, all the remaining areas excluding the area occupying the largest area can be removed, thereby eliminating the erroneously detected parts existing in the outside.

④ Calculate the number of incorrectly detected parts

As shown in FIGS. 2E and 2F, the number of erroneously detected portions that can not be removed after inverting the entire image including the detected region is calculated and displayed.

This step is a step for removing an erroneously detected part which has not been removed in the preceding step. In this case, as shown in FIG. 2E, after inverting the primary inverse monochrome image, The number of objects is calculated as 12 objects as shown in FIG. 2f.

Here, if the number of the inverted detected regions is one, the concrete neutralization region can be detected even if only the first detection step is performed. However, if the number of the inverted detected regions is two or more, You can do more. That is, if the number of detected regions is one, the detection result can be confirmed through the confirmation step immediately without additional processing. However, if the number of detected regions is two or more, This is because there is a part to be detected and an additional detection step is necessary. In this case, as shown in FIG. 2F, there is a part that is erroneously detected, and since the number of objects is 12, the secondary detection step is additionally performed as described later.

(3) Secondary detection step

Considering the concept of the outermost polygon formed by the set of points shown in FIG. 3A, the outermost polygon formed by the white pixels is calculated by a known method (the quickhull method proposed by Barber et al.) In the image shown in FIG. 2D. On the other hand, when an object in the inverted image exists inside the outermost polygon of the detected region in the first detection, it is misdetected that carbonation has progressed in the first detection, And the results shown in Fig. 3B were obtained.

(4) Identification step

This step is a step of confirming the neutralization region. Since the region where carbonation has not progressed in the first detection step and / or the second detection step is detected, the step of reversing the image to detect the carbonation- The results shown are obtained. FIG. 4A is obtained by reversing the image shown in FIG. 3B to indicate the portion where carbonation proceeds. Then, as shown in FIG. 4B, the outermost pixels of the detected neutralized region, which has undergone carbonation in the color image, are displayed in black, thereby confirming the concrete neutralization region detection result.

Examples 2 to 5

The concrete neutralization region was detected in the same manner as in Example 1, except that the outermost pixels of the neutralization region were indicated as white in the point where the measurement specimen was changed and / or the confirmation step, and the results are shown in Figs. 5A to 8B Respectively.

Here, FIGS. 5A, 6A, 7A and 8A show color images obtained in the photographing step, and FIGS. 5B, 6B, 7B and 8B show images obtained after the image processing step.

FIG. 5B, FIG. 6B, FIG. 7B and FIG. 8B clearly show the precise boundary where carbonation proceeds, and thus the accuracy of the concrete neutralization region detection method of the present invention is excellent.

Experimental Example

In order to determine the appropriate brightness for the gray image acquisition in a color image consisting of R (red), G (green) and B (blue) images, images are extracted for each brightness and the results are shown in 9a to 9c, respectively.

As shown in FIGS. 9A and 9C, a gray image formed only by the brightness of each of R (red) and B (blue) can not distinguish between the area where the carbonation has progressed and the area where the carbonation is not progressed. It is possible to distinguish between the area where the carbonation proceeds and the area where the carbonation is not proceeded.

These results suggest that green (G) is closely related to purple and complementary colors, and that G image is not carbonated during phenolphthalein treatment compared to other images, resulting in darkness of purple color.

From the above experimental results, it can be seen that the present invention extracts the image from the color image composed of R, G, and B for the gray image only.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be taken by way of limitation, Various changes and modifications will be possible.

Claims (8)

Obtaining a measurement specimen from a concrete structure to detect a neutralization region;
Treating the obtained measurement specimen with a phenolphthalein solution;
A photographing step of photographing the entire surface of the specimen including the discolored area by the phenolphthalein to obtain a color image; And
And an image processing step of detecting a neutralization area from the color image,
The image processing step
A gray image obtaining step of obtaining a gray image from the color image; And
And a primary detection step of processing the obtained gray image to obtain a primary color change area,
The gray image acquiring step may include extracting an image having a brightness of only G (green) from the color image,
The first detecting step may include converting the gray image into a monochrome image through a binarization method, inverting the monochrome image to obtain a first inverted monochrome image, removing a wrongly detected portion of the first inverted monochrome image And calculating the number of erroneously detected portions that are not removed in the second-order inverted black-and-white image obtained by second-order reversing the entire image from which the erroneously detected portion has been removed. Way. delete 2. The method of claim 1,
And a secondary detection step of calculating a convex hull of the primary color change area to obtain a secondary color change area.
delete delete The method of claim 3,
Wherein the second detecting step comprises the steps of: calculating an outermost polygon (convex hull) formed by the white pixels in the second-order inverted monochrome image obtained in the first-order detecting step; And determining whether or not the polygon is present inside an outer polygon.
The image processing method according to any one of claims 1, 3, and 6, wherein the image processing step
Further comprising a confirmation step of confirming a neutralization region from the primary color change area obtained in the primary detection step or the secondary color change area obtained in the secondary detection step.
8. The method of claim 7,
Wherein the checking step includes a third step of inverting the image including the first color change area or the second color change area to obtain a third inverse monochrome image, a step of converting the third inverse monochrome image into a color image, And displaying the outermost pixels of the primary color change area or the secondary color change area in black or white.

Images