A method and system for analyzing the uniformity of recycled asphalt mixing based on image recognition

Abstract

The present invention discloses a method and system for analyzing the uniformity of recycled asphalt mix based on image recognition. The method comprises: determining whether the image size difference between any two first sub-images is greater than a preset size threshold; if not, clustering the aggregate pixels in the at least one first sub-image according to a preset pixel clustering strategy to obtain at least one target aggregate pixel set; determining whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixels from two different target aggregate pixel sets; if greater than the preset first number threshold, generating a recycled asphalt mix uniformity analysis result corresponding to the recycled asphalt image. This method can minimize human subjectivity and aggregate distribution factors within a single particle size range, and can conveniently and quickly detect the uniformity of recycled asphalt mix.

Description

Technical Field

[0001] The present invention belongs to the technical field of recycled asphalt analysis, and in particular relates to a recycled asphalt mixing uniformity analysis method and system based on image recognition. Background Art

[0002] During the paving process, hot-mix recycled asphalt mixtures are prone to segregation due to uneven distribution of coarse and fine aggregates. This segregation can cause the actual gradation and asphalt content of the recycled asphalt mixture to deviate significantly from the designed values, resulting in uneven overall asphalt pavement quality. This not only induces various types of early damage to the asphalt pavement but also significantly impacts the pavement's long-term performance. Therefore, analyzing the uniformity of recycled asphalt mixes is of great significance.

[0003] Existing methods for analyzing the uniformity of recycled asphalt mixes typically rely on manual judgment based on aggregate distribution or by comparing real-time aggregate distribution images with aggregate distribution image templates. While these methods offer high speeds, they suffer from low accuracy due to the varying distribution of aggregates of varying particle sizes. Summary of the Invention

[0004] The present invention provides a method and system for analyzing the uniformity of recycled asphalt mixture based on image recognition, which is used to solve the technical problem that the distribution of aggregates of various particle sizes may be different, resulting in low accuracy of existing uniformity analysis methods.

[0005] In a first aspect, the present invention provides a method for analyzing the uniformity of recycled asphalt mixing based on image recognition, comprising:

[0006] Acquire images of recycled asphalt;

[0007] According to different aggregate particle size ranges, a preset processing strategy is used to perform binarization processing on the recycled asphalt image to obtain a recycled asphalt binary image corresponding to the different particle size ranges;

[0008] Dividing each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set, wherein one image region set includes at least one regenerated asphalt binary image region obtained by dividing one regenerated asphalt binary image;

[0009] Determine a minimum aggregate area in a first recycled asphalt binary image area in each image area set, and intercept at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is a recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is a minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area;

[0010] Determine whether the image size difference between any two first sub-images is greater than a preset size threshold;

[0011] If the size is not greater than a preset size threshold, the aggregate pixel points in the at least one first sub-image are aggregated according to a preset pixel point aggregation strategy to obtain at least one target aggregate pixel point set, wherein each target aggregate pixel point in a target aggregate pixel point set belongs to the same first sub-image;

[0012] Determining whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets;

[0013] If it is greater than a preset first quantity threshold, an analysis result indicating that the recycled asphalt is evenly mixed corresponding to the recycled asphalt image is generated.

[0014] In a second aspect, the present invention provides a recycled asphalt mixing uniformity analysis system based on image recognition, comprising:

[0015] an acquisition module configured to acquire an image of the recycled asphalt;

[0016] a pre-processing module configured to perform binarization processing on the recycled asphalt image according to different aggregate particle size ranges using a preset processing strategy to obtain a binarized image of the recycled asphalt corresponding to the different particle size ranges;

[0017] a division module configured to divide each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set, wherein one image region set includes at least one regenerated asphalt binary image region obtained by dividing one regenerated asphalt binary image;

[0018] a capture module configured to determine a minimum aggregate area in a first recycled asphalt binary image area of each image area set, and capture at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is a recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is a minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area;

[0019] A first judgment module is configured to judge whether the image size difference between any two first sub-images is greater than a preset size threshold;

[0020] an aggregation module configured to aggregate the aggregate pixels in the at least one first sub-image according to a preset pixel aggregation strategy if the size is not greater than a preset size threshold, to obtain at least one target aggregate pixel set, wherein each target aggregate pixel in a target aggregate pixel set belongs to the same first sub-image;

[0021] A second judgment module is configured to judge whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets;

[0022] The generation module is configured to generate an analysis result indicating that the recycled asphalt is evenly mixed, corresponding to the recycled asphalt image, if the amount is greater than a preset first quantity threshold.

[0023] According to a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the recycled asphalt mixing uniformity analysis method based on image recognition according to any embodiment of the present invention.

[0024] In a fourth aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon. When the program instructions are executed by a processor, the processor executes the steps of the recycled asphalt mixing uniformity analysis method based on image recognition according to any embodiment of the present invention.

[0025] The image recognition-based recycled asphalt mixing uniformity analysis method and system of the present application divides each recycled asphalt binary image into at least one image area set through a preset two-dimensional coordinate system, and can perform partition analysis on the recycled asphalt image, determine the minimum asphalt area in the first recycled asphalt binary image area of each image area set, and intercept at least one first sub-image containing only the minimum asphalt area, and judge whether the image size difference between any two first sub-images is greater than a preset size threshold. If it is greater than the preset size threshold, it means that the aggregate distribution in each particle size range is uneven, which can indicate that the recycled asphalt corresponding to the recycled asphalt image at this time is unevenly mixed, effectively improving the efficiency of identifying uneven recycled asphalt mixing, and according to a preset pixel point aggregation strategy, the aggregate pixels in the at least one first sub-image are aggregated to obtain at least one target aggregate pixel point set, and it is judged whether the number of target pixel pairs that meet the preset conditions is greater than a preset first number threshold, thereby realizing the determination of whether the recycled asphalt mixing is uniform based on the aggregate tracking situation in different aggregate particle size ranges, thereby avoiding human subjective factors and aggregate distribution factors in a single particle size range as much as possible, and being able to conveniently and quickly detect the uniformity of the re-asphalt mixing. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0027] Figure 1 A flowchart of a method for analyzing recycled asphalt mixing uniformity based on image recognition provided by one embodiment of the present invention;

[0028] Figure 2 A schematic diagram of sliding a dynamic sliding window according to a specific embodiment of the present invention is provided;

[0029] Figure 3 A structural block diagram of a recycled asphalt mixing uniformity analysis system based on image recognition provided by one embodiment of the present invention;

[0030] Figure 4 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0032] See also Figure 1 , which shows a flow chart of a recycled asphalt mixing uniformity analysis method based on image recognition in this application.

[0033] like Figure 1 As shown in FIG, the method for analyzing the uniformity of recycled asphalt mixture based on image recognition specifically includes the following steps:

[0034] Step S101, obtaining a recycled asphalt image.

[0035] Step S102 : binarizing the regenerated asphalt image according to different aggregate particle size ranges using a preset processing strategy to obtain binarized images of the regenerated asphalt corresponding to the different particle size ranges.

[0036] In this step, the regenerated asphalt image is grayscaled to obtain a regenerated asphalt grayscale image, and the regenerated asphalt grayscale image is binarized to obtain a first regenerated asphalt binarized image, wherein the grayscale levels in the first regenerated asphalt binarized image that are lower than the threshold are set as asphalt features, and those that are not lower than the threshold are set as aggregate features; different aggregate particle size ranges are set, and aggregate features outside a certain aggregate particle size range are removed from the first regenerated asphalt binarized image to obtain a regenerated asphalt binarized image corresponding to the certain aggregate particle size range, wherein the certain aggregate particle size range is any range among the different aggregate particle size ranges. For example, Figure 2 Binarized image of recycled asphalt with particle size of 9.5 to 16.5 mm.

[0037] Step S103, dividing each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image area set, wherein an image area set includes at least one regenerated asphalt binary image area obtained by dividing a regenerated asphalt binary image.

[0038] In this step, the center point of a certain recycled asphalt binary image is obtained; the certain recycled asphalt binary image is placed in the two-dimensional coordinate system, and the center point is aligned with the origin of the two-dimensional coordinate system. The edge line of the certain recycled asphalt binary image is parallel to the X-axis or the Y-axis, and the image is divided into a first recycled asphalt binary image area in the first quadrant, a second recycled asphalt binary image area in the second quadrant, a third recycled asphalt binary image area in the third quadrant, and a fourth recycled asphalt binary image area in the fourth quadrant.

[0039] Step S104, determining the minimum aggregate area in the first recycled asphalt binary image area of each image area set, and intercepting at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is the recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is the minimum rectangular area containing all aggregate pixel points in the first recycled asphalt binary image area.

[0040] In this step, the minimum aggregate area is determined in the second recycled asphalt binary image area, the third recycled asphalt binary image area, and the fourth recycled asphalt binary image area in each image area set, and at least one second sub-image, at least one third sub-image, and at least one fourth sub-image containing only the minimum aggregate area are respectively intercepted.

[0041] It should be noted that the subsequent steps performed by at least one second sub-image, at least one third sub-image and at least one fourth sub-image are the same as the steps performed by at least one first sub-image, so they will not be described in detail here.

[0042] Step S105 , determining whether the image size difference between any two first sub-images is greater than a preset size threshold.

[0043] In a specific embodiment, after determining whether the image size difference between any two first sub-images is greater than a preset size threshold, if it is greater than the preset size threshold, a warning message of uneven mixing of recycled asphalt corresponding to the recycled asphalt image is directly generated.

[0044] Step S106: If it is not greater than the preset size threshold, the aggregate pixel points in the at least one first sub-image are aggregated according to the preset pixel point aggregation strategy to obtain at least one target aggregate pixel point set, wherein each target aggregate pixel point in a target aggregate pixel point set belongs to the same first sub-image.

[0045] In this step, see Figure 2, a dynamic sliding window of an initial size is slid along the edge of a first sub-image for the first time, and during each sliding, it is determined whether the number of aggregate pixel points in the dynamic sliding window is greater than a preset second number threshold, wherein the next sliding interval of the dynamic sliding window is the size of the current dynamic sliding window; if it is not greater than the preset second number threshold, the size of the dynamic sliding window is temporarily expanded along the sliding direction until the number of aggregate pixel points in the dynamic sliding window after the temporary expansion is greater than the preset second number threshold, wherein the temporary expansion means that after the size of the dynamic sliding window is expanded at the current sliding position, the size of the expanded dynamic sliding window is restored to the initial size at the next sliding position; based on The center position of the pixel point is determined according to the position of each aggregate pixel point in the briefly expanded dynamic sliding window, and the aggregate pixel point closest to the center position of the pixel point among the aggregate pixel points is used as the target aggregate pixel point; the dynamic sliding window of the initial size is slid for a second time in the first sub-image along the edge of the second area until the sliding trajectory of the dynamic sliding window covers all areas of the first sub-image, wherein the second area is the area of the first sub-image minus the area covered by the dynamic sliding window during the first sliding; the target aggregate pixel points obtained during each sliding are divided into a target aggregate pixel point set corresponding to the first sub-image.

[0046] It should be noted that if it is not greater than the preset second quantity threshold, the size of the dynamic sliding window is temporarily expanded along the sliding direction. This method of temporarily expanding the size can obtain sufficient aggregate pixel points while reducing the occurrence of irregular formation of the subsequent second area due to the simultaneous expansion of the length and width of the dynamic sliding window, thereby facilitating the dynamic sliding window to traverse all aggregate features.

[0047] In this embodiment, a pixel clustering strategy is adopted so that all aggregate pixels can participate in the process of determining the center position, thereby maximizing the accuracy of the defined target aggregate pixels compared to other clustering algorithms that discard edge aggregate pixels for clustering to obtain the center pixel. It can better represent the distribution of aggregate pixels after clustering.

[0048] Specifically, determining the center position of the pixel point based on the position of each aggregate pixel point in the briefly expanded dynamic sliding window includes but is not limited to placing the dynamic sliding window in a two-dimensional coordinate system, and coinciding a vertex of the dynamic sliding window with the coordinate origin, thereby obtaining the coordinate position of each aggregate pixel point, and determining a center position closest to each aggregate pixel point based on the coordinate position of each aggregate pixel point, that is, obtaining the center position of the pixel point.

[0049] Step S107 , determining whether the number of target pixel pairs meeting a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets.

[0050] In this step, a first target aggregate pixel point in the first target aggregate pixel point set and a second target aggregate pixel point in the second target aggregate pixel point set are obtained, wherein the first target aggregate pixel point set and the second target aggregate pixel point set are any two sets in at least one target aggregate pixel point set;

[0051] Determine whether the distance between a first target aggregate pixel point and a second target aggregate pixel point is greater than a preset distance threshold, wherein the first target aggregate pixel point and the second target aggregate pixel point are any pixel points in the first target aggregate pixel point set and the second target aggregate pixel point set respectively;

[0052] If it is greater than the preset distance threshold, a certain first target aggregate pixel point and a certain second target aggregate pixel point are not defined as a target pixel point pair, and the distance between a certain first target aggregate pixel point and other second target aggregate pixel points is further determined to be greater than the preset distance threshold, wherein the other second target aggregate pixel points are any pixel points in the second target aggregate pixel point set excluding a certain second target aggregate pixel point;

[0053] If the distance is not greater than the preset distance threshold, a first target aggregate pixel point and a second target aggregate pixel point are defined as a target pixel point pair;

[0054] Determine whether the number of target pixel pairs is greater than a preset first number threshold.

[0055] In a specific embodiment, after determining whether the number of target pixel pairs that meet the preset conditions is greater than a preset first number threshold, if it is not greater than the preset first number threshold, a warning message of uneven mixing of recycled asphalt corresponding to the recycled asphalt image is directly generated.

[0056] Step S108: If the number is greater than a preset first quantity threshold, an analysis result indicating that the recycled asphalt is evenly mixed corresponding to the recycled asphalt image is generated.

[0057] In summary, the method of the present application divides each recycled asphalt binary image by a preset two-dimensional coordinate system to obtain at least one image area set, which can perform partition analysis on the recycled asphalt image, determine the minimum asphalt area in the first recycled asphalt binary image area of each image area set, and intercept at least one first sub-image containing only the minimum asphalt area, and judge whether the image size difference between any two first sub-images is greater than a preset size threshold. If it is greater than the preset size threshold, it means that the aggregate distribution of each particle size range is uneven, which means that the recycled asphalt corresponding to the recycled asphalt image at this time is unevenly mixed, effectively improving the efficiency of identifying uneven recycled asphalt mixing, and according to the preset pixel point aggregation strategy, the aggregate pixel points in the at least one first sub-image are aggregated to obtain at least one target aggregate pixel point set, and it is judged whether the number of target pixel pairs that meet the preset conditions is greater than the preset first number threshold, thereby realizing the determination of whether the recycled asphalt mixing is uniform according to the aggregate tracking situation in different aggregate particle size ranges, thereby avoiding human subjective factors and aggregate distribution factors in a single particle size range as much as possible, and being able to conveniently and quickly detect the uniformity of the re-asphalt mixing.

[0058] See also Figure 3 , which shows a structural block diagram of a recycled asphalt mixing uniformity analysis system based on image recognition in this application.

[0059] like Figure 3 As shown, the recycled asphalt mixing uniformity analysis system 200 includes an acquisition module 210, a preprocessing module 220, a division module 230, an interception module 240, a first judgment module 250, an aggregation module 260, a second judgment module 270 and a generation module 280.

[0060] Among them, the acquisition module 210 is configured to acquire the recycled asphalt image; the preprocessing module 220 is configured to binarize the recycled asphalt image according to different aggregate particle size ranges using a preset processing strategy to obtain recycled asphalt binary images corresponding to the different particle size ranges; the division module 230 is configured to divide each recycled asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image area set, wherein an image area set contains at least one recycled asphalt binary image area obtained by dividing a recycled asphalt binary image; the interception module 240 is configured to determine the minimum aggregate area in the first recycled asphalt binary image area of each image area set, and intercept at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is the recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area. The minimum aggregate area is the minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area; the first judgment module 250 is configured to judge whether the image size difference between any two first sub-images is greater than a preset size threshold; the aggregation module 260 is configured to aggregate the aggregate pixels in the at least one first sub-image according to a preset pixel aggregation strategy if it is not greater than the preset size threshold, to obtain at least one target aggregate pixel set, wherein each target aggregate pixel in a target aggregate pixel set belongs to the same first sub-image; the second judgment module 270 is configured to judge whether the number of target pixel pairs that meet the preset conditions is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixels from two different target aggregate pixel sets; the generation module 280 is configured to generate an analysis result of the uniformity of the recycled asphalt mixing corresponding to the recycled asphalt image if it is greater than the preset first number threshold.

[0061] It should be understood that Figure 3 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects also apply to Figure 3 The modules in it will not be described in detail here.

[0062] In other embodiments, embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor is caused to execute the recycled asphalt mixing uniformity analysis method based on image recognition in any of the above method embodiments;

[0063] As an embodiment, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:

[0064] Acquire images of recycled asphalt;

[0065] According to different aggregate particle size ranges, a preset processing strategy is used to perform binarization processing on the recycled asphalt image to obtain a recycled asphalt binary image corresponding to the different particle size ranges;

[0066] Dividing each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set, wherein one image region set includes at least one regenerated asphalt binary image region obtained by dividing one regenerated asphalt binary image;

[0067] Determine a minimum aggregate area in a first recycled asphalt binary image area in each image area set, and intercept at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is a recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is a minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area;

[0068] Determine whether the image size difference between any two first sub-images is greater than a preset size threshold;

[0069] If the size is not greater than a preset size threshold, the aggregate pixel points in the at least one first sub-image are aggregated according to a preset pixel point aggregation strategy to obtain at least one target aggregate pixel point set, wherein each target aggregate pixel point in a target aggregate pixel point set belongs to the same first sub-image;

[0070] Determining whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets;

[0071] If it is greater than a preset first quantity threshold, an analysis result indicating that the recycled asphalt is evenly mixed corresponding to the recycled asphalt image is generated.

[0072] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the image recognition-based recycled asphalt mix uniformity analysis system, etc. Furthermore, the computer-readable storage medium may include high-speed random access memory and may also include memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some embodiments, the computer-readable storage medium may optionally include memory remotely located relative to the processor, and these remote memories may be connected to the image recognition-based recycled asphalt mix uniformity analysis system via a network. Examples of the aforementioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0073] Figure 4 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 4 The example of a bus connection is shown. Memory 320 is the aforementioned computer-readable storage medium. Processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in memory 320, thereby implementing the above-mentioned method embodiment of the recycled asphalt mixing uniformity analysis method based on image recognition. Input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the recycled asphalt mixing uniformity analysis system based on image recognition. Output device 340 may include a display device such as a display screen.

[0074] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0075] As an embodiment, the electronic device is applied to a recycled asphalt mixing uniformity analysis system based on image recognition and is used for a client, and includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0076] Acquire images of recycled asphalt;

[0077] According to different aggregate particle size ranges, a preset processing strategy is used to perform binarization processing on the recycled asphalt image to obtain a recycled asphalt binary image corresponding to the different particle size ranges;

[0078] Dividing each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set, wherein one image region set includes at least one regenerated asphalt binary image region obtained by dividing one regenerated asphalt binary image;

[0079] Determine a minimum aggregate area in a first recycled asphalt binary image area in each image area set, and intercept at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is a recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is a minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area;

[0080] Determine whether the image size difference between any two first sub-images is greater than a preset size threshold;

[0081] If the size is not greater than a preset size threshold, the aggregate pixel points in the at least one first sub-image are aggregated according to a preset pixel point aggregation strategy to obtain at least one target aggregate pixel point set, wherein each target aggregate pixel point in a target aggregate pixel point set belongs to the same first sub-image;

[0082] Determining whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets;

[0083] If it is greater than a preset first quantity threshold, an analysis result indicating that the recycled asphalt is evenly mixed corresponding to the recycled asphalt image is generated.

[0084] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods of each embodiment or certain portions of the embodiments.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for analyzing the uniformity of recycled asphalt mixing based on image recognition, characterized in that: include: Acquire images of recycled asphalt; According to different aggregate particle size ranges, a preset processing strategy is used to perform binarization processing on the recycled asphalt image to obtain a recycled asphalt binary image corresponding to the different particle size ranges; Dividing each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set, wherein one image region set includes at least one regenerated asphalt binary image region obtained by dividing one regenerated asphalt binary image; Determine a minimum aggregate area in a first recycled asphalt binary image area in each image area set, and intercept at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is a recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is a minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area; Determine whether the image size difference between any two first sub-images is greater than a preset size threshold; If the size is not greater than a preset size threshold, the aggregate pixel points in the at least one first sub-image are aggregated according to a preset pixel point aggregation strategy to obtain at least one target aggregate pixel point set, wherein each target aggregate pixel point in a target aggregate pixel point set belongs to the same first sub-image; Determining whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets; If it is greater than a preset first quantity threshold, an analysis result indicating that the recycled asphalt is evenly mixed corresponding to the recycled asphalt image is generated.

2. The method for analyzing the uniformity of recycled asphalt mixing based on image recognition according to claim 1, characterized in that: The binarization processing of the regenerated asphalt image using a preset processing strategy according to different aggregate particle size ranges to obtain the binarized regenerated asphalt images corresponding to the different particle size ranges includes: Grayscale processing is performed on the regenerated asphalt image to obtain a regenerated asphalt grayscale image, and binarization is performed on the regenerated asphalt grayscale image to obtain a first regenerated asphalt binary image, wherein grayscale levels in the first regenerated asphalt binary image that are lower than a threshold are set as asphalt features, and grayscale levels that are not lower than the threshold are set as aggregate features; Different aggregate particle size ranges are set, and aggregate features outside a certain aggregate particle size range are removed from the first regenerated asphalt binary image to obtain a regenerated asphalt binary image corresponding to the certain aggregate particle size range, wherein the certain aggregate particle size range is any range among the different aggregate particle size ranges.

3. The method for analyzing the uniformity of recycled asphalt mixing based on image recognition according to claim 1, characterized in that: The step of dividing each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set includes: Get the center point of a binary image of recycled asphalt; The binary image of a certain recycled asphalt is placed in the two-dimensional coordinate system, and the center point is aligned with the origin of the two-dimensional coordinate system. The edge line of the binary image of a certain recycled asphalt is parallel to the X-axis or the Y-axis, and the image is divided into a first recycled asphalt binary image area in the first quadrant, a second recycled asphalt binary image area in the second quadrant, a third recycled asphalt binary image area in the third quadrant, and a fourth recycled asphalt binary image area in the fourth quadrant.

4. The method for analyzing the uniformity of recycled asphalt mixing based on image recognition according to claim 1, characterized in that: After determining whether the image size difference between any two first sub-images is greater than a preset size threshold, the method further includes: If it is larger than a preset size threshold, a warning message of uneven mixing of the recycled asphalt corresponding to the recycled asphalt image is directly generated.

5. The method for analyzing the uniformity of recycled asphalt mixing based on image recognition according to claim 1, characterized in that: Aggregating the aggregate pixel points in the at least one first sub-image according to a preset pixel point aggregation strategy to obtain at least one target aggregate pixel point set includes: Sliding a dynamic sliding window of an initial size along an edge of a first sub-image for the first time, and determining during each sliding operation whether the number of aggregate pixels in the dynamic sliding window is greater than a preset second number threshold, wherein the next sliding interval of the dynamic sliding window is the size of the current dynamic sliding window; If it is not greater than a preset second number threshold, the size of the dynamic sliding window is temporarily expanded along the sliding direction until the number of aggregate pixels in the temporarily expanded dynamic sliding window is greater than the preset second number threshold, wherein the temporary expansion means that after the size of the dynamic sliding window is expanded at the current sliding position, the size of the expanded dynamic sliding window is restored to the initial size at the next sliding position; Determine the center position of the pixel point according to the position of each aggregate pixel point in the briefly expanded dynamic sliding window, and take the aggregate pixel point closest to the center position of the pixel point among the aggregate pixel points as the target aggregate pixel point; Sliding a dynamic sliding window of an initial size for a second time along an edge of a second area in the first sub-image until the sliding track of the dynamic sliding window covers all areas of the first sub-image, wherein the second area is the area of the first sub-image minus the area covered by the dynamic sliding window during the first sliding; The target aggregate pixel points obtained during each sliding operation are divided into a target aggregate pixel point set corresponding to the first sub-image.

6. The method for analyzing the uniformity of recycled asphalt mixture based on image recognition according to claim 1, characterized in that: The step of determining whether the number of target pixel pairs meeting a preset condition is greater than a preset first number threshold comprises: Acquire a first target aggregate pixel point in the first target aggregate pixel point set, and a second target aggregate pixel point in the second target aggregate pixel point set; Determine whether the distance between the first target aggregate pixel point and the second target aggregate pixel point is greater than a preset distance threshold; If it is greater than the preset distance threshold, the certain first target aggregate pixel point and the certain second target aggregate pixel point are not defined as a target pixel point pair, and the distance between the certain first target aggregate pixel point and the other second target aggregate pixel point is further determined to be greater than the preset distance threshold, wherein the other second target aggregate pixel point is any pixel point in the second target aggregate pixel point set excluding the certain second target aggregate pixel point; If the distance is not greater than a preset distance threshold, the first target aggregate pixel point and the second target aggregate pixel point are defined as a target pixel point pair; Determine whether the number of the target pixel pairs is greater than a preset first number threshold.

7. The method for analyzing the uniformity of recycled asphalt mixing based on image recognition according to claim 1, characterized in that: After determining whether the number of target pixel pairs that meet the preset condition is greater than a preset first number threshold, the method further includes: If it is not greater than the preset first quantity threshold, a warning message of uneven mixing of the recycled asphalt corresponding to the recycled asphalt image is directly generated.

8. A recycled asphalt mixing uniformity analysis system based on image recognition, characterized in that: include: an acquisition module configured to acquire an image of the recycled asphalt; a pre-processing module configured to perform binarization processing on the recycled asphalt image according to different aggregate particle size ranges using a preset processing strategy to obtain a binarized image of the recycled asphalt corresponding to the different particle size ranges; a division module configured to divide each regenerated asphalt binary image according to a preset two-dimensional coordinate system to obtain at least one image region set, wherein one image region set includes at least one regenerated asphalt binary image region obtained by dividing one regenerated asphalt binary image; a capture module configured to determine a minimum aggregate area in a first recycled asphalt binary image area of each image area set, and capture at least one first sub-image containing only the minimum aggregate area, wherein the first recycled asphalt binary image area is a recycled asphalt binary image area in the first quadrant of the two-dimensional coordinate system in the at least one recycled asphalt binary image area, and the minimum aggregate area is a minimum rectangular area containing all aggregate pixels in the first recycled asphalt binary image area; A first judgment module is configured to judge whether the image size difference between any two first sub-images is greater than a preset size threshold; an aggregation module configured to aggregate the aggregate pixels in the at least one first sub-image according to a preset pixel aggregation strategy if the size is not greater than a preset size threshold, to obtain at least one target aggregate pixel set, wherein each target aggregate pixel in a target aggregate pixel set belongs to the same first sub-image; A second judgment module is configured to judge whether the number of target pixel pairs that meet a preset condition is greater than a preset first number threshold, wherein the target aggregate pixel pairs include target aggregate pixel points from two different target aggregate pixel point sets; The generation module is configured to generate an analysis result indicating that the recycled asphalt is evenly mixed, corresponding to the recycled asphalt image, if the amount is greater than a preset first quantity threshold.

9. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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