CN118485630B - Brick content analysis method based on microscopic image of brick-concrete powder and related equipment - Google Patents
Brick content analysis method based on microscopic image of brick-concrete powder and related equipment Download PDFInfo
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Abstract
The application discloses a brick content analysis method and related equipment based on a brick-concrete powder microscopic image, wherein the method comprises the steps of obtaining a target microscopic image corresponding to each shooting dimension aiming at target brick-concrete powder, wherein the shooting dimension comprises a magnification factor and a shooting area, carrying out background image area processing on the target microscopic image to obtain an image to be analyzed, carrying out color segmentation on the image to be analyzed on bricks and concrete to obtain color segmentation data, and carrying out brick content analysis according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result. The analysis result of the brick content is determined based on the target microscope image of the target brick-concrete powder, the separation of the brick from other powder is not needed, large-scale equipment and complex technology are not needed, the operation flow is simplified, and the speed of detecting the brick content in the brick-concrete aggregate is improved.
Description
Technical Field
The invention relates to the technical fields of image processing and construction waste recycling treatment, in particular to a brick content analysis method based on a microscopic image of brick-concrete powder and related equipment.
Background
The construction waste is converted into the recycled coarse and fine aggregate (namely the brick-concrete aggregate) for the fresh concrete, so that the construction waste can be pushed to be recycled, and the influence on the natural environment caused by the exploitation of the natural aggregate can be reduced. At present, the occupation proportion of red bricks and other bricks in the construction waste is larger, so that the content of the bricks in the brick-concrete aggregate is higher. Related researches show that the higher the proportion of bricks in the brick-concrete aggregate, the worse the performance of recycled concrete prepared from the brick-concrete aggregate, so that the brick content in the brick-concrete aggregate can be used as an important index for evaluating the quality of the brick-concrete aggregate, and the method has important significance for realizing recycling of the brick-concrete aggregate.
In the existing method for detecting the brick content in the brick-concrete aggregate, firstly, random sampling is carried out, then, the bricks in the sample are separated from other particles by adopting a mechanical or manual method, finally, the brick content in the sample is weighed and calculated, and the operation flow is complex, so that the brick content in the brick-concrete aggregate cannot be detected quickly.
Disclosure of Invention
Based on the above, it is necessary to provide a brick content analysis method and related equipment based on a brick-concrete powder microscope image, aiming at the technical problems that the operation flow is complex and the brick content in the brick-concrete aggregate cannot be detected rapidly when the brick content in the brick-concrete aggregate is detected in the prior art.
In a first aspect, a method for analyzing brick content based on a microscopic image of brick-concrete powder is provided, the method comprising:
Aiming at target brick mixed powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the shooting dimensions comprise magnification and shooting areas;
performing background image area processing on the target microscope image to obtain an image to be analyzed;
performing color segmentation on the brick and concrete on the image to be analyzed to obtain color segmentation data;
and carrying out brick content analysis according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result.
Further, the step of acquiring the target microscope image corresponding to each shooting dimension for the target brick mixed powder material comprises the following steps:
acquiring a test shooting microscope image corresponding to the sampled brick-concrete powder;
Judging whether the spacing of the brick-concrete powder materials meets the spacing disqualification condition or whether the brick-concrete powder materials are stacked or not according to the test shooting microscope image;
If any one of the obtained sample brick mixed powder is the sample brick mixed powder, jumping to the step of obtaining the test shooting microscope image corresponding to the sample brick mixed powder based on the adjusted and distributed sample brick mixed powder, and continuing to execute the step;
if not, taking the sampled brick mixed powder as the target brick mixed powder;
and aiming at the target brick-concrete powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the target microscope image is a microscope image obtained by shooting the target brick-concrete powder based on target configuration and the shooting dimension, the target configuration is set by adopting a target light source and a target microscope, the target light source adopts natural light or white light, and the target microscope is set without adding a filter.
Further, the step of performing color segmentation on the image to be analyzed to obtain color segmentation data includes:
Performing color distribution analysis on the image to be analyzed based on a preset color space to obtain color distribution data;
According to preset replacement color data and threshold range data corresponding to the color space type corresponding to the preset color space, performing color segmentation on the color distribution data to obtain initial segmentation data;
And determining the color segmentation data according to the initial segmentation data.
Further, the step of determining the color segmentation data according to the initial segmentation data includes:
Inputting the image to be analyzed into a pre-trained brick segmentation model to segment brick powder, so as to obtain a brick powder mask;
Carrying out segmentation difference data identification on the brick powder mask and the initial segmentation data;
And determining the color segmentation data according to the image to be analyzed, the initial segmentation data and the segmentation difference data.
Further, the preset color space adopts an HSL color space, and the preset replacement color data adopts color data corresponding to black;
The threshold range data corresponding to the color space type corresponding to the HSL color space includes H0,85, S32,255, L68,255.
Further, the step of performing a brick content analysis according to each color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result includes:
Performing tile content analysis on each color segmentation data to obtain a first result;
average value calculation is carried out on each first result corresponding to the same magnification factor, and a second result is obtained;
And carrying out weighted summation on each second result corresponding to the target brick-concrete powder to obtain the brick content analysis result.
Further, the step of calculating an average value of the first results corresponding to the same magnification factor to obtain a second result includes:
Deleting the maximum value and the minimum value of each first result corresponding to the same magnification;
and carrying out average value calculation on the first results corresponding to the same amplification factor after the deletion treatment to obtain the second result.
In a second aspect, there is provided a brick content analysis device based on a brick-concrete powder microscopic image, the device comprising:
The data acquisition module is used for acquiring a target microscope image corresponding to each shooting dimension aiming at the target brick mixed powder, wherein the shooting dimensions comprise magnification and shooting areas;
the background processing module is used for carrying out background image area processing on the target microscope image to obtain an image to be analyzed;
the color segmentation module is used for carrying out color segmentation on the bricks and the concrete on the image to be analyzed to obtain color segmentation data;
and the brick content analysis module is used for carrying out brick content analysis according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result.
In a third aspect, a computer device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the brick content analysis method based on brick and concrete powder microscopy images described above when executing the computer program.
In a fourth aspect, a computer readable storage medium is provided, the computer readable storage medium storing a computer program, which when executed by a processor, implements the steps of the brick content analysis method based on a brick-concrete powder microscopy image described above.
The brick content analysis method and the related equipment based on the brick-concrete powder microscopic image are characterized in that a target microscopic image corresponding to each shooting dimension is obtained according to target brick-concrete powder, wherein the shooting dimension comprises a magnification factor and a shooting area, background image area processing is carried out on the target microscopic image to obtain an image to be analyzed, color segmentation is carried out on the image to be analyzed on bricks and concrete to obtain color segmentation data, and brick content analysis is carried out according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result. According to the application, the brick content analysis result is determined based on the target microscope image of the target brick-concrete powder, the brick is not required to be separated from other powder, large equipment and complex technology are not required, the operation flow is simplified, the speed of detecting the brick content in the brick-concrete aggregate is improved, the brick content analysis of the particles of the brick-concrete aggregate is realized in the prior art, the brick content analysis of the brick-concrete powder is realized, no damage is caused to the brick-concrete powder in the whole process, the nondestructive detection is realized, the shooting dimension comprises the amplification factor and the shooting area, the brick content analysis of the image with at least one view angle is realized, and the accuracy of the brick content analysis is further improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Wherein:
FIG. 1 is a diagram of an application environment of a brick content analysis method based on a brick-concrete powder microscopic image in one embodiment;
FIG. 2 is a flow chart of a method of tile content analysis based on a microscopic image of a powder mix of tiles in one embodiment;
FIG. 3 is a block diagram of a brick content analysis device based on a brick-concrete powder microscopic image in one embodiment;
FIG. 4 is a block diagram of a computer device in one embodiment;
FIG. 5 is another block diagram of a computer device in one embodiment.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The brick content analysis method based on the brick-concrete powder microscopic image provided by the embodiment of the invention can be applied to an application environment as shown in fig. 1, wherein a client 110 communicates with a server 120 through a network.
The server 120 may obtain, through the client 110, a target microscope image corresponding to each shooting dimension, where the shooting dimensions include a magnification factor and a shooting area, for the target brick-concrete powder. The server 120 is configured to perform background image area processing on the target microscope image to obtain an image to be analyzed, perform color segmentation on the brick and concrete on the image to be analyzed to obtain color segmentation data, and perform brick content analysis according to each color segmentation data corresponding to the target brick mixed powder to obtain a brick content analysis result. According to the application, the brick content analysis result is determined based on the target microscope image of the target brick-concrete powder, the brick is not required to be separated from other powder, large equipment and complex technology are not required, the operation flow is simplified, the speed of detecting the brick content in the brick-concrete aggregate is improved, the brick content analysis of the particles of the brick-concrete aggregate is realized in the prior art, the brick content analysis of the brick-concrete powder is realized, no damage is caused to the brick-concrete powder in the whole process, the nondestructive detection is realized, the shooting dimension comprises the amplification factor and the shooting area, the brick content analysis of the image with at least one view angle is realized, and the accuracy of the brick content analysis is further improved.
In another embodiment of the present application, the server 120 obtains, from a preset storage space, a target microscope image corresponding to each shooting dimension, for a target brick-concrete powder, where the shooting dimension includes a magnification factor and a shooting area, performs background image area processing on the target microscope image to obtain an image to be analyzed, performs color segmentation on a brick and concrete on the image to be analyzed to obtain color segmentation data, and performs brick content analysis according to each color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result.
In yet another embodiment of the present application, the client 110 obtains, from a preset storage space, a target microscope image corresponding to each shooting dimension, for a target brick-concrete powder, where the shooting dimension includes a magnification factor and a shooting area, performs background image area processing on the target microscope image to obtain an image to be analyzed, performs color segmentation on a brick and concrete on the image to be analyzed to obtain color segmentation data, and performs brick content analysis according to each color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result.
Among other things, the client 110 may be, but is not limited to, various personal computers, notebook computers, smartphones, tablet computers, and portable wearable devices. The server 120 may be implemented by a stand-alone server or a server cluster formed by a plurality of servers.
The present invention will be described in detail with reference to specific examples.
Referring to fig. 2, fig. 2 is a schematic flow chart of a brick content analysis method based on a microscopic image of brick-concrete powder according to an embodiment of the invention, which includes the following steps:
s1, aiming at target brick mixed powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the shooting dimensions comprise magnification and shooting areas;
Specifically, the target microscope image input by the user may be acquired, the target microscope image may be acquired from a preset storage space, and the target microscope image may be acquired from a third party application.
The target brick-concrete powder is the brick-concrete powder for the analysis of the brick content. Optionally, the particle size of the powder particles in the brick-concrete powder is less than 0.15mm.
The target microscope image is a digital image shot on the target brick mixed powder.
It will be appreciated that at least one shot area is provided for the target brick-concrete powder.
Alternatively, the magnification may be 10 times, 20 times, 30 times, 40 times, 50 times, 60 times.
S2, carrying out background image area processing on the target microscope image to obtain an image to be analyzed;
optionally, an image processing tool is called, a background image area in the target microscope image is replaced by a preset background color, and the replaced target microscope image is used as an image to be analyzed.
Optionally, the preset background color is white.
Alternatively, the image processing tool employs Photoshop. Photoshop processes mainly digital images composed of pixels.
Optionally, a pre-trained background segmentation model is adopted to segment the background image of the target microscope image, and according to a mask obtained by segmentation, the background image area in the target microscope image is replaced by a preset background color, so that only the image area corresponding to the brick-concrete powder is reserved, and the target microscope image with the background image area replaced is used as an image to be analyzed.
Optionally, the background segmentation model is a model trained based on the target detection network. The model structure and model training method of the background segmentation model may be selected from the prior art, and will not be described in detail herein.
The background segmentation model outputs a binary mask, wherein the value of a mask point in the binary mask is 1 or 0, if the value of the mask point is 1, the type of the mask point at a pixel point corresponding to the target microscope image is determined to be a background, and if the value of the mask point is 0, the type of the mask point at the pixel point corresponding to the target microscope image is determined to be brick mixed powder.
It will be appreciated that the background image area is processed so as to avoid affecting the accuracy of the color segmentation.
S3, performing color segmentation on the brick and concrete on the image to be analyzed to obtain color segmentation data;
Specifically, the image to be analyzed is drawn in a preset color space, color distribution analysis is further carried out, color segmentation of bricks and concrete is carried out according to the result of the color distribution analysis and threshold range data, and segmented data are used as color segmentation data.
Optionally, a GUI (GRAPHICA L User I NTERFACE, also called a graphic User interface) desktop program applicable to actual engineering is designed through Qt5, so that the distribution of the image to be analyzed in a preset color space is drawn, then the color space of the brick-concrete powder is distinguished according to a default reference threshold (i.e., threshold range data), and color division data is determined according to the data of a brick space formed by each channel threshold (e.g., H channel, S channel and L channel in the HSL color space) (i.e., the distribution area of the color of the brick in the preset color space).
Optionally, determining color segmentation data according to the brick space formed by the channel thresholds may be replaced by marking pixel points in the brick space formed by the channel thresholds as preset replacement color data to facilitate differentiation, and taking the marked brick space data as color segmentation data.
Alternatively, the preset replacement color data is black.
Alternatively, the pixel points in the brick space formed by the channel thresholds are marked as black to facilitate distinguishing, the data of the brick space completed with the marking is used as color segmentation data, and the method can be replaced by marking the pixel points in the brick space formed by the channel thresholds as black to facilitate distinguishing, then obtaining manual fine adjustment of the channel thresholds by a user, distinguishing the color space of the brick-concrete powder again through the adjusted channel thresholds, marking the pixel points in the brick space formed by the channel thresholds as preset replacement color data to facilitate distinguishing, and using the data of the brick space completed with the marking as color segmentation data. The threshold value of each channel is manually and finely adjusted, so that the brick space can cover brick powder, and the accuracy of color segmentation data is improved.
The preset color space may be any one of an HSL color space, an RGB color space, and an HSV color space. HSL is a representation of points in the RGB color model in a cylindrical coordinate system. The RGB color space is defined by the chromaticity of the three primary colors red, green and blue, whereby corresponding color triangles can be defined, generating other colors. HSV (Hue, saturat ion, va l ue) is a color space created from visual properties of colors, also called a hexagonal pyramid model (Hexcone Mode l).
Threshold range data describing channel thresholds corresponding to tiles.
Optionally, the color segmentation data is used for describing the data corresponding to the brick space.
Optionally, the color segmentation data is used for describing data corresponding to the brick space and data of a region corresponding to the powder particles outside the brick space.
Qt5 is a popular c++ framework for developing cross-platform applications.
And S4, performing brick content analysis according to the color segmentation data corresponding to the target brick mixed powder to obtain a brick content analysis result.
The method comprises the steps of calculating the number of pixels of brick powder as a first number according to color segmentation data, calculating the number of pixels in the color segmentation data as a second number, dividing the first number by the second number to obtain a first result, and determining the brick content analysis result according to all first results corresponding to the target brick-concrete powder.
Optionally, carrying out weighted summation on all the first results corresponding to the target brick mixed powder, and taking the data obtained by weighted summation as the brick content analysis result.
Optionally, calculating an average value of all the first results corresponding to the target brick mixed powder, and taking the calculated data as the brick content analysis result.
It will be appreciated that each of the color segmentation data corresponding to the target brick-concrete powder includes at least one of the color segmentation data.
According to the embodiment, the brick content analysis result is determined based on the target microscope image of the target brick-concrete powder, the brick is not required to be separated from other powder, large equipment and complex technology are not required, the operation flow is simplified, the speed of detecting the brick content in the brick-concrete aggregate is improved, the brick content analysis of the particles of the brick-concrete aggregate is realized in the prior art, the brick content analysis of the brick-concrete powder is realized in the whole process, no damage is caused to the brick-concrete powder, nondestructive detection is realized, the shooting dimension comprises the amplification factor and the shooting area, the brick content analysis of the image with at least one view angle is realized, and the accuracy of the brick content analysis is further improved.
In one embodiment, the step of acquiring, for the target brick-concrete powder, a target microscope image corresponding to each shooting dimension includes:
S11, acquiring a test shooting microscope image corresponding to the sampled brick-concrete powder;
Specifically, the sample brick-concrete powder is sampled and used as a sampling brick-concrete powder, the sampling brick-concrete powder is evenly and flatly paved on glass sheets for a microscope, a small amount of gaps can be formed among powder particles, but the stacking is not needed, then a cover slip is covered, the glass sheets, the sampling brick-concrete powder and the cover slip are used as samples to be tested, the samples to be tested are placed under a microscope, a microscope image is obtained through the microscope, and the microscope image is used as a test shooting microscope image.
Optionally, shooting a microscope image of the sampled brick-concrete powder based on the target configuration and the shooting dimension to obtain a test shooting microscope image.
S12, judging whether the spacing of the brick-concrete powder meets the spacing disqualification condition or whether the brick-concrete powder is stacked or not according to the test shooting microscope image;
Specifically, the interval between the powder particles of the brick-concrete powder is not suitable to be too large, the powder with scattered transition is difficult to identify, the powder particles of the brick-concrete powder are not suitable to be stacked, a large number of shadows are generated by the powder particles, negative influence is caused on color identification of the powder particles, and in order to solve the problem, the embodiment judges whether the interval between the brick-concrete powder meets the interval disqualification condition according to the test shooting microscope image, or judges whether the brick-concrete powder is stacked according to the test shooting microscope image.
Optionally, the pitch failure condition is greater than a preset pitch threshold.
And inputting the test shooting microscope image into a pre-trained stacking classification model to conduct classification prediction of whether stacking exists, and determining whether stacking exists according to predicted data.
The pre-trained stacked classification model is a pre-trained bi-classification model.
S13, if any one of the obtained sample brick-concrete powder is yes, jumping to the step of obtaining the test shooting microscope image corresponding to the sample brick-concrete powder based on the adjusted and distributed sample brick-concrete powder, and continuing to execute the step;
Specifically, if any of the samples is yes, that is, the spacing of the brick-concrete powder meets the spacing disqualification condition, or the brick-concrete powder is stacked, which means that the sampled brick-concrete powder does not meet the tiling requirement, so that the distribution of the sampled brick-concrete powder in the sample to be tested is adjusted, and then the step S11 is skipped (that is, the test-shooting microscope image corresponding to the sampled brick-concrete powder is acquired) and the step S11 is continuously executed to re-evaluate whether the sampled brick-concrete powder meets the tiling requirement.
S14, if not, taking the sampled brick mixed powder as the target brick mixed powder;
Specifically, if the samples are not, that is, the spacing of the brick-concrete powder does not meet the spacing failure condition, and the brick-concrete powder is not stacked, this means that the samples are in accordance with the tiling requirement, and therefore, the samples are taken as the target brick-concrete powder.
S15, aiming at the target brick-concrete powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the target microscope image is a microscope image obtained by shooting the target brick-concrete powder based on target configuration and the shooting dimension, the target configuration is set by adopting a target light source and a target microscope, the target light source adopts natural light or white light, and the target microscope is set without adding a filter.
Specifically, for a sample to be detected corresponding to the target brick-concrete powder, acquiring a microscope image corresponding to each shooting dimension through a microscope, and taking the acquired microscope image as a target microscope image.
Optionally, under a certain magnification, shooting different shooting areas of the sample to be detected corresponding to the target brick-concrete powder respectively, taking each shot microscope image as a target microscope image, specifically operating the microscope image as a target microscope image, and changing the identification area in the eyepiece of the microscope by slowly moving the objective table back and forth/left and right, wherein the brick content in the sample can be more comprehensively identified by the images shot for multiple times.
According to the method, the device and the system, natural light or white light is adopted by the target light source, the target microscope is arranged without adding a filter, larger errors in subsequent color recognition are prevented, compared with a camera, the regenerated brick-concrete powder which cannot be clearly displayed by the microscope is amplified to a recognizable size and then shot, and an image of the powder can be shot more accurately.
In one embodiment, the step of performing color segmentation of the tile and the concrete on the image to be analyzed to obtain color segmentation data includes:
S31, carrying out color distribution analysis on the image to be analyzed based on a preset color space to obtain color distribution data;
Specifically, the image to be analyzed is drawn in a preset color space, color distribution analysis is carried out on the drawn result, and data obtained through analysis are used as color distribution data.
S32, performing color segmentation on the color distribution data to obtain initial segmentation data according to preset replacement color data and threshold range data corresponding to the color space type corresponding to the preset color space;
Specifically, the color space of the brick-concrete powder is distinguished according to the threshold range data corresponding to the color space type corresponding to the preset color space, the data of the brick space formed by the thresholds of all channels are replaced or marked into preset replacement color data, and color segmentation data are determined according to the data corresponding to the brick space. The accuracy of the brick content analysis is improved by replacing preset replacement color data.
S33, determining the color segmentation data according to the initial segmentation data.
Optionally, the initial segmentation data is directly used as the color segmentation data.
Optionally, the initial segmentation data and the image to be analyzed are sent to a target checking terminal, and the color segmentation data sent by the target checking terminal is obtained. The user modifies the initial segmentation data according to the image to be analyzed through a target auditing end, click submission is completed through modification, and the target auditing end takes the initial segmentation data modified by the user as the color segmentation data. And through adjustment of the target auditing end, the accuracy of the determined color segmentation data is improved.
Optionally, the initial segmentation data and the image to be analyzed are sent to a target auditing end, the adjusted threshold range data sent by the target auditing end is obtained, the initial segmentation data is regenerated, the initial segmentation data is repeated, the adjusted threshold range data is obtained, the initial segmentation data is regenerated, until the user feels that the initial segmentation data meets the requirements, at the moment, the user clicks and submits the initial segmentation data corresponding to the adjusted threshold range data, and the target auditing end uses the initial segmentation data corresponding to the user clicking and submitting the initial segmentation data as the color segmentation data. By combining with the adjustment of the target auditing end, the accuracy of the determined color segmentation data is improved.
In one embodiment, the step of determining the color segmentation data from the initial segmentation data comprises:
S331, inputting the image to be analyzed into a pre-trained brick segmentation model to segment brick powder, so as to obtain a brick powder mask;
Specifically, the image to be analyzed is input into a pre-trained brick segmentation model to carry out brick powder segmentation, and a binary mask obtained by segmentation is used as a brick powder mask.
Each mask point in the brick powder mask corresponds to one pixel point in the image to be analyzed. The method comprises the steps of setting the value of each mask point in a brick powder mask to be 0 or1, setting the powder particles corresponding to the pixel points corresponding to the mask points to be brick powder if the mask points in the brick powder mask are 1, and setting the powder particles corresponding to the pixel points corresponding to the mask points not to be brick powder if the mask points in the brick powder mask are 0.
S332, carrying out segmentation difference data identification on the brick powder mask and the initial segmentation data;
Specifically, the tile powder mask and the initial segmentation data are subjected to pixel-by-pixel comparison, and data (including at least the positions of the pixels) corresponding to all pixels having differences are used as segmentation difference data. For example, the value of the mask point of the 3 rd row and the 8 th column in the brick powder mask is 1, and the pixel point of the 3 rd row and the 8 th column in the initial segmentation data is the brick powder, and the pixel point is the normal pixel point. For example, the value of the 3 rd row and 8 th column mask points in the brick powder mask is 1, and the 3 rd row and 8 th column pixel points in the initial segmentation data are not brick powder, and are abnormal pixel points.
S333, determining the color segmentation data according to the image to be analyzed, the initial segmentation data and the segmentation difference data.
Specifically, the image to be analyzed, the initial segmentation data and the segmentation difference data are sent to a target auditing end, an auditing result sent by the target auditing end is obtained, the initial segmentation data are corrected according to the auditing result, and the corrected initial segmentation data are used as the color segmentation data.
According to the image to be analyzed, the initial segmentation data and the segmentation difference data, the color segmentation data are determined, so that the accuracy of the color segmentation data is improved, and the accuracy of the brick content analysis is improved.
In one embodiment, the preset color space adopts an HSL color space, and the preset replacement color data adopts black corresponding color data;
The threshold range data corresponding to the color space type corresponding to the HSL color space includes H0,85, S32,255, L68,255.
Specifically, H0,85, which is H channels 0 to 85 of the HSL color space, may be 0,85, or a value between 0 and 85.
Specifically, S32,255, which is the S channels 32 to 255 of the HSL color space, may be 32,255, or a value between 32 and 255.
Specifically, L68,255, which is the L channels 68 to 255 of the HSL color space, may be 68,255, or a value between 68 and 255.
According to the embodiment, through the threshold range data corresponding to the color space type corresponding to the HSL color space, a foundation is provided for mechanical separation of bricks in the brick-concrete powder material from other parts, and therefore time in the process of processing a large amount of image information in batches is reduced.
In one embodiment, the step of performing a brick content analysis according to each color segmentation data corresponding to the target brick-concrete powder material to obtain a brick content analysis result includes:
s41, performing tile content analysis on each color segmentation data to obtain a first result;
Specifically, according to the color segmentation data, the number of pixels of the brick powder is calculated to be a first number, the number of pixels in the color segmentation data is calculated to be a second number, and the first number is divided by the second number to obtain a first result.
S42, carrying out average value calculation on the first results corresponding to the same magnification to obtain a second result;
Specifically, an average value of the first results corresponding to the same magnification is calculated, and the calculated data is used as a second result.
And S43, carrying out weighted summation on the second results corresponding to the target brick mixed powder to obtain the brick content analysis result.
And specifically, carrying out weighted summation on each second result corresponding to the target brick mixed powder, and taking the data obtained by weighted summation as the brick content analysis result.
Optionally, the weight of the weighted sum is determined according to the magnification factor.
In this embodiment, the average value of the first results corresponding to the same magnification factor is calculated to obtain second results, and then the weighted summation is performed on the second results corresponding to the target brick mixed powder to obtain the brick content analysis result, so that adverse effects caused by accidental errors are reduced to the greatest extent through the average value calculation, and the accuracy of brick content analysis is improved.
In one embodiment, the step of calculating an average value of the first results corresponding to the same magnification factor to obtain a second result includes:
s421, deleting the maximum value and the minimum value of the first results corresponding to the same magnification;
And S422, carrying out average value calculation on the first results corresponding to the same magnification after the deletion processing to obtain the second result.
In this embodiment, the average value of the first results corresponding to the same amplification factor after the deletion processing of the maximum value and the minimum value is calculated to obtain the second result, so that the influence of noise data (that is, the maximum value and the minimum value in the first results corresponding to the same amplification factor) is reduced, and the accuracy of the second result is further improved.
Referring to fig. 3, in one embodiment, a brick content analysis device based on a microscopic image of a brick-concrete powder is provided, the device comprising:
the data acquisition module 801 is configured to acquire, for a target brick-concrete powder, a target microscope image corresponding to each shooting dimension, where the shooting dimension includes a magnification factor and a shooting area;
The background processing module 802 is configured to perform background image area processing on the target microscope image to obtain an image to be analyzed;
The color segmentation module 803 is configured to perform color segmentation on the image to be analyzed, so as to obtain color segmentation data;
And the brick content analysis module 804 is configured to perform brick content analysis according to each color segmentation data corresponding to the target brick-concrete powder, so as to obtain a brick content analysis result.
According to the embodiment, the brick content analysis result is determined based on the target microscope image of the target brick-concrete powder, the brick is not required to be separated from other powder, large equipment and complex technology are not required, the operation flow is simplified, the speed of detecting the brick content in the brick-concrete aggregate is improved, the brick content analysis of the particles of the brick-concrete aggregate is realized in the prior art, the brick content analysis of the brick-concrete powder is realized in the whole process, no damage is caused to the brick-concrete powder, nondestructive detection is realized, the shooting dimension comprises the amplification factor and the shooting area, the brick content analysis of the image with at least one view angle is realized, and the accuracy of the brick content analysis is further improved.
In one embodiment, the step of acquiring the target microscope image corresponding to each shooting dimension for the target brick and mortar powder in the data acquisition module 801 includes:
acquiring a test shooting microscope image corresponding to the sampled brick-concrete powder;
Judging whether the spacing of the brick-concrete powder materials meets the spacing disqualification condition or whether the brick-concrete powder materials are stacked or not according to the test shooting microscope image;
If any one of the obtained sample brick mixed powder is the sample brick mixed powder, jumping to the step of obtaining the test shooting microscope image corresponding to the sample brick mixed powder based on the adjusted and distributed sample brick mixed powder, and continuing to execute the step;
if not, taking the sampled brick mixed powder as the target brick mixed powder;
and aiming at the target brick-concrete powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the target microscope image is a microscope image obtained by shooting the target brick-concrete powder based on target configuration and the shooting dimension, the target configuration is set by adopting a target light source and a target microscope, the target light source adopts natural light or white light, and the target microscope is set without adding a filter.
In one embodiment, the step of performing color segmentation on the image to be analyzed in the color segmentation module 803 to obtain color segmentation data includes:
Performing color distribution analysis on the image to be analyzed based on a preset color space to obtain color distribution data;
According to preset replacement color data and threshold range data corresponding to the color space type corresponding to the preset color space, performing color segmentation on the color distribution data to obtain initial segmentation data;
And determining the color segmentation data according to the initial segmentation data.
In one embodiment, the step of determining the color segmentation data according to the initial segmentation data in the color segmentation module 803 includes:
Inputting the image to be analyzed into a pre-trained brick segmentation model to segment brick powder, so as to obtain a brick powder mask;
Carrying out segmentation difference data identification on the brick powder mask and the initial segmentation data;
And determining the color segmentation data according to the image to be analyzed, the initial segmentation data and the segmentation difference data.
In one embodiment, the preset color space adopts an HSL color space, and the preset replacement color data adopts black corresponding color data;
The threshold range data corresponding to the color space type corresponding to the HSL color space includes H0,85, S32,255, L68,255.
In one embodiment, the step of performing the tile content analysis according to the color segmentation data corresponding to the target tile powder mixture in the tile content analysis module 804 to obtain the tile content analysis result includes:
Performing tile content analysis on each color segmentation data to obtain a first result;
average value calculation is carried out on each first result corresponding to the same magnification factor, and a second result is obtained;
And carrying out weighted summation on each second result corresponding to the target brick-concrete powder to obtain the brick content analysis result.
In one embodiment, the step of performing average calculation on each of the first results corresponding to the same magnification factor in the brick content analysis module 804 to obtain a second result includes:
Deleting the maximum value and the minimum value of each first result corresponding to the same magnification;
and carrying out average value calculation on the first results corresponding to the same amplification factor after the deletion treatment to obtain the second result.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes non-volatile and/or volatile storage media and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is for communicating with an external client via a network connection. The computer program, when executed by a processor, performs the functions or steps of a brick content analysis method service side based on a brick-concrete powder microscope image.
In one embodiment, a computer device is provided, which may be a client, the internal structure of which may be as shown in FIG. 5. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is for communicating with an external server via a network connection. The computer program, when executed by a processor, performs the client-side functions or steps of a brick content analysis method based on a brick-concrete powder microscopy image.
In one embodiment, a computer device is presented comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
Aiming at target brick mixed powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the shooting dimensions comprise magnification and shooting areas;
performing background image area processing on the target microscope image to obtain an image to be analyzed;
performing color segmentation on the brick and concrete on the image to be analyzed to obtain color segmentation data;
and carrying out brick content analysis according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result.
According to the embodiment, the brick content analysis result is determined based on the target microscope image of the target brick-concrete powder, the brick is not required to be separated from other powder, large equipment and complex technology are not required, the operation flow is simplified, the speed of detecting the brick content in the brick-concrete aggregate is improved, the brick content analysis of the particles of the brick-concrete aggregate is realized in the prior art, the brick content analysis of the brick-concrete powder is realized in the whole process, no damage is caused to the brick-concrete powder, nondestructive detection is realized, the shooting dimension comprises the amplification factor and the shooting area, the brick content analysis of the image with at least one view angle is realized, and the accuracy of the brick content analysis is further improved.
In one embodiment, a computer readable storage medium is presented, the computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of:
Aiming at target brick mixed powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the shooting dimensions comprise magnification and shooting areas;
performing background image area processing on the target microscope image to obtain an image to be analyzed;
performing color segmentation on the brick and concrete on the image to be analyzed to obtain color segmentation data;
and carrying out brick content analysis according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result.
According to the embodiment, the brick content analysis result is determined based on the target microscope image of the target brick-concrete powder, the brick is not required to be separated from other powder, large equipment and complex technology are not required, the operation flow is simplified, the speed of detecting the brick content in the brick-concrete aggregate is improved, the brick content analysis of the particles of the brick-concrete aggregate is realized in the prior art, the brick content analysis of the brick-concrete powder is realized in the whole process, no damage is caused to the brick-concrete powder, nondestructive detection is realized, the shooting dimension comprises the amplification factor and the shooting area, the brick content analysis of the image with at least one view angle is realized, and the accuracy of the brick content analysis is further improved.
It should be noted that, the functions or steps implemented by the computer readable storage medium or the computer device may correspond to the relevant descriptions of the server side and the client side in the foregoing method embodiments, and are not described herein for avoiding repetition.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCH L I NK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The foregoing embodiments are merely illustrative of the technical solutions of the present invention, and not restrictive, and although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that modifications may still be made to the technical solutions described in the foregoing embodiments or equivalent substitutions of some technical features thereof, and that such modifications or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. A method for analyzing tile content based on a microscopic image of a powder mix of tiles, the method comprising:
Aiming at target brick mixed powder, acquiring a target microscope image corresponding to each shooting dimension, wherein the shooting dimensions comprise magnification and shooting areas;
performing background image area processing on the target microscope image to obtain an image to be analyzed;
performing color segmentation on the brick and concrete on the image to be analyzed to obtain color segmentation data;
Performing tile content analysis according to the color segmentation data corresponding to the target tile mixed powder to obtain a tile content analysis result;
The step of acquiring the target microscope image corresponding to each shooting dimension aiming at the target brick mixed powder comprises the following steps:
acquiring a test shooting microscope image corresponding to the sampled brick-concrete powder;
Judging whether the spacing of the brick-concrete powder materials meets the spacing disqualification condition or whether the brick-concrete powder materials are stacked or not according to the test shooting microscope image;
If any one of the obtained sample brick mixed powder is the sample brick mixed powder, jumping to the step of obtaining the test shooting microscope image corresponding to the sample brick mixed powder based on the adjusted and distributed sample brick mixed powder, and continuing to execute the step;
if not, taking the sampled brick mixed powder as the target brick mixed powder;
Acquiring a target microscope image corresponding to each shooting dimension aiming at the target brick-concrete powder, wherein the target microscope image is a microscope image obtained by shooting the target brick-concrete powder based on target configuration and the shooting dimensions, the target configuration is set by adopting a target light source and a target microscope, the target light source adopts natural light or white light, and the target microscope is set without adding a filter;
the step of performing color segmentation of bricks and concrete on the image to be analyzed to obtain color segmentation data comprises the following steps:
Performing color distribution analysis on the image to be analyzed based on a preset color space to obtain color distribution data;
According to preset replacement color data and threshold range data corresponding to the color space type corresponding to the preset color space, performing color segmentation on the color distribution data to obtain initial segmentation data;
Determining the color segmentation data according to the initial segmentation data;
the step of determining the color segmentation data according to the initial segmentation data comprises the following steps:
Inputting the image to be analyzed into a pre-trained brick segmentation model to segment brick powder, so as to obtain a brick powder mask;
Carrying out segmentation difference data identification on the brick powder mask and the initial segmentation data;
Determining the color segmentation data according to the image to be analyzed, the initial segmentation data and the segmentation difference data;
the preset color space adopts an HSL color space, and the preset replacement color data adopts color data corresponding to black;
The threshold range data corresponding to the color space type corresponding to the HSL color space comprises H [0,85], S [32,255], L [68,255];
the step of analyzing the brick content according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result comprises the following steps:
Performing tile content analysis on each color segmentation data to obtain a first result;
average value calculation is carried out on each first result corresponding to the same magnification factor, and a second result is obtained;
Carrying out weighted summation on each second result corresponding to the target brick-concrete powder to obtain a brick content analysis result;
and the step of calculating the average value of the first results corresponding to the same magnification factor to obtain a second result comprises the following steps:
Deleting the maximum value and the minimum value of each first result corresponding to the same magnification;
and carrying out average value calculation on the first results corresponding to the same amplification factor after the deletion treatment to obtain the second result.
2. A brick content analysis device based on a brick-concrete powder microscopic image, characterized in that the device comprises:
The data acquisition module is used for acquiring a target microscope image corresponding to each shooting dimension aiming at the target brick mixed powder, wherein the shooting dimensions comprise magnification and shooting areas;
the background processing module is used for carrying out background image area processing on the target microscope image to obtain an image to be analyzed;
the color segmentation module is used for carrying out color segmentation on the bricks and the concrete on the image to be analyzed to obtain color segmentation data;
the brick content analysis module is used for carrying out brick content analysis according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result;
The step of acquiring the target microscope image corresponding to each shooting dimension aiming at the target brick mixed powder comprises the following steps:
acquiring a test shooting microscope image corresponding to the sampled brick-concrete powder;
Judging whether the spacing of the brick-concrete powder materials meets the spacing disqualification condition or whether the brick-concrete powder materials are stacked or not according to the test shooting microscope image;
If any one of the obtained sample brick mixed powder is the sample brick mixed powder, jumping to the step of obtaining the test shooting microscope image corresponding to the sample brick mixed powder based on the adjusted and distributed sample brick mixed powder, and continuing to execute the step;
if not, taking the sampled brick mixed powder as the target brick mixed powder;
Acquiring a target microscope image corresponding to each shooting dimension aiming at the target brick-concrete powder, wherein the target microscope image is a microscope image obtained by shooting the target brick-concrete powder based on target configuration and the shooting dimensions, the target configuration is set by adopting a target light source and a target microscope, the target light source adopts natural light or white light, and the target microscope is set without adding a filter;
the step of performing color segmentation of bricks and concrete on the image to be analyzed to obtain color segmentation data comprises the following steps:
Performing color distribution analysis on the image to be analyzed based on a preset color space to obtain color distribution data;
According to preset replacement color data and threshold range data corresponding to the color space type corresponding to the preset color space, performing color segmentation on the color distribution data to obtain initial segmentation data;
Determining the color segmentation data according to the initial segmentation data;
the step of determining the color segmentation data according to the initial segmentation data comprises the following steps:
Inputting the image to be analyzed into a pre-trained brick segmentation model to segment brick powder, so as to obtain a brick powder mask;
Carrying out segmentation difference data identification on the brick powder mask and the initial segmentation data;
Determining the color segmentation data according to the image to be analyzed, the initial segmentation data and the segmentation difference data;
the preset color space adopts an HSL color space, and the preset replacement color data adopts color data corresponding to black;
The threshold range data corresponding to the color space type corresponding to the HSL color space comprises H [0,85], S [32,255], L [68,255];
the step of analyzing the brick content according to the color segmentation data corresponding to the target brick-concrete powder to obtain a brick content analysis result comprises the following steps:
Performing tile content analysis on each color segmentation data to obtain a first result;
average value calculation is carried out on each first result corresponding to the same magnification factor, and a second result is obtained;
Carrying out weighted summation on each second result corresponding to the target brick-concrete powder to obtain a brick content analysis result;
and the step of calculating the average value of the first results corresponding to the same magnification factor to obtain a second result comprises the following steps:
Deleting the maximum value and the minimum value of each first result corresponding to the same magnification;
and carrying out average value calculation on the first results corresponding to the same amplification factor after the deletion treatment to obtain the second result.
3. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the steps of the method for analyzing the tile content based on the image of a tile powder microscope according to claim 1.
4. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the brick content analysis method based on a brick-concrete powder microscopy image according to claim 1.
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