A landscape road monitoring method based on image processing

Abstract

The present invention discloses a landscape road monitoring method based on image processing, which relates to the field of landscape road monitoring. The present invention includes identifying patterns and shapes in landscape road images; analyzing the arrangement of graphic shapes in the image to be tested for matching a preset model, wherein the preset model includes an array arrangement model and a line arrangement model; selecting the preset model and generating a simulated image of the landscape road based on the pattern and shape; comparing and analyzing the difference between the simulated image and the actual landscape road image and marking the difference type. The present invention can realize precise maintenance in cooperation with maintenance personnel, reduce communication time and human communication errors, distinguish different types of landscape roads through models, improve recognition accuracy, expand the universality of the application of the monitoring method, and improve communication effectiveness.

Description

Technical Field

[0001] The invention relates to the field of landscape road monitoring, and in particular to a landscape road monitoring method based on image processing. Background Art

[0002] At present, in order to be more harmonious and natural with the surrounding environment, landscape roads will use natural materials such as wood and bamboo. However, landscape roads in cities and between green plants in parks are mostly paved with stones, and the stones are mostly installed manually based on the workers' experience, resulting in uneven tilt, offset, damage, etc.

[0003] The existing technology for monitoring urban landscape roads also uses manual patrols to roughly estimate the damaged area and damage type. The landscape road repair information transmitted to maintenance personnel is unclear, resulting in low maintenance efficiency. It is also inconvenient for maintenance personnel to locate damaged landscape roads and carry adapter tools and corresponding auxiliary materials.

[0004] Taking into account the current problems of incomplete information and low efficiency in monitoring landscape roads in parks, the present invention proposes a landscape road monitoring method based on image processing, which is used to achieve background maintenance, customization, and rapid repair, and provide data for the life status of landscape roads. Summary of the invention

[0005] The present application invents a landscape road monitoring method based on image processing to solve the problems of the prior art.

[0006] In a first aspect, a landscape road monitoring method based on image processing comprises:

[0007] Recognize patterns and shapes in landscape road images;

[0008] Analyzing the arrangement of graphic shapes in the image to be tested for matching a preset model, wherein the preset model includes an array arrangement model and a line arrangement model; analyzing the image to be tested includes: judging based on the dot matrix lines formed by the center points of the identified unit graphics, and when it is judged that the dot matrix forms an image as a line, matching the line arrangement model; when it is judged that the dot matrix forms an image as a surface, matching the array arrangement model;

[0009] Select the preset model and generate a simulated picture of the landscape road according to the pattern and shape;

[0010] Compare and analyze the differences between the simulated pictures and the real landscape road images and mark the types of differences.

[0011] Furthermore, the identifying of patterns and shapes in the landscape road image includes:

[0012] Obtain the unit graphics of the landscape road, and separate the basic graphics with regular shapes after analysis;

[0013] The results of manual verification are used as a verification set and input into the model used to recognize images until the recognition rate reaches a threshold value, and the types of basic graphics detected are numbered;

[0014] Number and sort multiple or one same basic graphics in an image.

[0015] Furthermore, the method also includes: pixelating the basic graphics into graphics including pixel points, calculating the center points of the graphics pixels, and connecting the pixel center points of the same basic graphics; outputting a center point trajectory of a class of basic graphics, and recording the position information of the trajectory corresponding to the landscape road image.

[0016] Furthermore, the acquisition of the landscape road unit graphics and the separation of basic graphics with regular shapes after analysis include:

[0017] Performing perspective transformation on the graphics on the landscape road image into graphics on a two-dimensional plane, and recording perspective transformation information of the graphics corresponding to the position information;

[0018] When the preset model is selected and a simulated picture of a landscape road is generated according to the pattern and shape, it includes:

[0019] According to the perspective transformation information of the graphics recording the corresponding position information, a reverse operation is performed, and the separated basic graphics are reversely perspective transformed based on the position information to generate graphics corresponding to the position of the simulated image.

[0020] Further, the arrangement of the graphic shapes in the image to be tested is analyzed for matching a preset model, and the preset model includes an array arrangement model and a line arrangement model; analyzing the image to be tested includes: judging based on the dot matrix lines formed by the center points of the identified unit graphics, when it is judged that the dot matrix forms an image as a line, matching the line arrangement model, when it is judged that the dot matrix forms an image as a surface, matching the array arrangement model, and specifically including:

[0021] Calculate the number of adjacent center points of each center point connection line. If the center point count of the total connection line is greater than 3 times the number of center points, the dot matrix connection line is judged as a surface and matches the array arrangement model. Otherwise, the dot matrix connection line is a line and matches the line arrangement model.

[0022] Furthermore, the pixelization of the basic graphic into a graphic including pixel points, calculating the pixel center point of the graphic, and connecting the pixel center points of the same basic graphic further specifically includes:

[0023] When there are multiple groups of one or more patterns covering a basic graphic, the pixelation processing target is determined to be a unit graphic including one or more patterns, the shape of the unit graphic is used as the basic graphic content to be framed, and the pixelation processing is performed;

[0024] When the pattern covers multiple basic graphics, the pixel processing target is determined to be a basic graphic, and pixel processing is performed after frame selection according to the graphic boundary.

[0025] Furthermore, the step of selecting the preset model and generating a simulated picture of the landscape road according to the pattern and shape further specifically includes:

[0026] Generate basic graphics at corresponding positions based on the center point trajectory to obtain simulated negatives;

[0027] The generated basic graphics are adaptively adjusted according to the edge position data of the basic graphics in the image corresponding to the center point, and the adjustment includes enlargement, reduction, and perspective transformation;

[0028] When a pattern is included, the pattern is generated on an analog film to obtain an analog picture;

[0029] When multiple patterns are included, the multiple patterns are sequentially generated on the analog film according to the hierarchical relationship of the patterns to obtain the analog picture.

[0030] Furthermore, the comparative analysis of the differences between the simulated image and the real landscape road image and marking the difference types include:

[0031] Grayscale processing is used to compare the grayscale value differences of pixels, and to determine whether they belong to basic graphic pixels or pattern pixels, and to mark the position information of connected pixels;

[0032] Alternatively, directly compare the basic graphics and patterns at corresponding positions, calculate the pattern or basic graphics to which the missing part belongs, and mark the position information.

[0033] Furthermore, classification marking is performed according to the graphic pattern conditions, including marking according to different types and marking according to different monitoring conditions. Specifically, the position difference and size difference of the basic graphic are marked, and the missing or stained patterns are marked.

[0034] In a second aspect, the present invention provides a landscape road monitoring system based on image processing, which is used to implement a landscape road monitoring method based on image processing as described in any one of the first aspects, including a collection end, a host and a display end;

[0035] The collecting end is used to collect patterns and shapes in the landscape road image.

[0036] The acquisition end sends data to the host and display end;

[0037] The host is used to identify patterns and shapes in the landscape road image, and is also used to analyze the arrangement of graphic shapes in the image to be tested for matching with a preset model. The preset model includes an array arrangement model and a line arrangement model. The analysis of the image to be tested includes: judging based on the dot matrix connection formed by the center point of the identified unit figure: when the dot matrix forms an image as a line, matching the line arrangement model; when the dot matrix forms an image as a surface, matching the array arrangement model; selecting the preset model and generating a simulated image of the landscape road based on the pattern and shape, comparing and analyzing the difference between the simulated image and the actual landscape road image and marking the difference type;

[0038] The display end is used to receive the host analysis results, display the differences and annotate the contents.

[0039] The present invention provides a landscape road monitoring method based on image processing, which uses image recognition and processing technology to quickly monitor the landscape road conditions;

[0040] The present invention can distinguish various types of maintenance conditions and provide valuable reference data for landscape road construction.

[0041] The present invention cooperates with maintenance personnel to achieve precise maintenance, reduce communication time and human communication errors, distinguish different types of landscape roads through models, improve recognition accuracy, expand the universality of monitoring method application, and improve communication effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0043] Figure 1 A flow chart of a landscape road monitoring method based on image processing is provided as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0044] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0045] In the existing technology, when it comes to landscape road maintenance, there are always problems such as incomplete maintenance and wrong maintenance issues. This may be caused by communication problems or omissions of maintenance issues. At the same time, since the data is scattered and unsystematic, it is difficult to provide valuable data for subsequent landscape road construction;

[0046] There are many inconveniences in using conventional road maintenance methods for landscape roads. Since landscape roads are located in different locations, monitoring methods are not applicable and monitoring is difficult. Therefore, the concept of the present invention is applied to this field through mature technology to process relevant images and obtain simulated generated pictures after analysis, and then use image comparison technology to obtain difference annotation information.

[0047] The specific application scenario of the present invention is the maintenance and monitoring of landscape roads.

[0048] The present invention provides a landscape road monitoring method based on image processing, aiming to solve the above technical problems in the prior art.

[0049] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0050] Embodiment 1: This exemplary embodiment provides a landscape road monitoring method based on image processing, including the following specific steps: Figure 1 As shown,

[0051] s1. Collecting patterns and shapes in landscape road images;

[0052] s2, identifying patterns and shapes in landscape road images;

[0053] s3. Analyze the arrangement of graphic shapes in the image to be tested to match the preset model;

[0054] s4, selecting the preset model and generating a simulated picture of the landscape road according to the pattern and shape;

[0055] s5. Compare and analyze the differences between the simulated pictures and the real landscape road images and mark the types of differences.

[0056] Among them, s2 specifically includes:

[0057] s21, obtaining the unit graphics of the landscape road, and separating the basic graphics with regular shapes after analysis;

[0058] s22, manually verify the recognition results as a verification set and input them into the model for image recognition until the recognition rate reaches above the threshold, and the types of basic graphics detected are numbered;

[0059] s23. Number and sort the number of multiple or one identical basic graphics in an image.

[0060] Among them, s3 specifically includes:

[0061] The preset models include an array arrangement model and a line arrangement model; analyzing the image to be tested includes: judging based on the dot matrix lines formed by the center points of the identified unit figures, and when it is judged that the dot matrix forms an image as a line, matching the line arrangement model; when it is judged that the dot matrix forms an image as a surface, matching the array arrangement model;

[0062] In this embodiment, the number of adjacent center points of each center point connection line can be calculated. If the center point count of the total connection line is greater than 3 times the number of center points, the dot matrix connection line is judged to be a surface and matches the array arrangement model. Otherwise, the dot matrix connection line is a line and matches the line arrangement model.

[0063] Among them, s4 specifically includes:

[0064] s41, pixelate the basic graphic into a graphic including pixel points, calculate the pixel center point of the graphic, and connect the pixel center points of the same basic graphic; combined with the specific steps of s3, the pixelation processing details are as follows:

[0065] When there are multiple groups of one or more patterns covering a basic graphic, the pixel processing target is judged to be a unit graphic including one or more patterns, the shape of the unit graphic is used as the basic graphic content for frame selection, and pixel processing is performed; when the pattern covers multiple basic graphics, the pixel processing target is judged to be a basic graphic, and pixel processing is performed after frame selection according to the graphic boundary.

[0066] s42, output the center point trajectory of a type of basic graphics, and record the position information of the trajectory corresponding to the landscape road image;

[0067] s421, performing perspective transformation on the graphics on the landscape road image into graphics on a two-dimensional plane, and recording perspective transformation information of the graphics corresponding to the position information;

[0068] s422. Perform a reverse operation based on the perspective transformation information of the graphics recording the corresponding position information, and perform a reverse perspective transformation on the separated basic graphics based on the position information to generate a graphics corresponding to the position of the simulated image.

[0069] S422 specifically includes the following steps:

[0070] s4221, generating a basic graphic at a corresponding position based on the center point trajectory, and obtaining a simulated film;

[0071] The generated basic graphics are adaptively adjusted according to the edge position data of the basic graphics in the image corresponding to the center point, and the adjustment includes enlargement, reduction, and perspective transformation;

[0072] s4222. When one pattern is included, a pattern is generated on an analog film to obtain a simulated image; when multiple patterns are included, multiple patterns are sequentially generated on an analog film according to the hierarchical relationship of the patterns to obtain a simulated image.

[0073] Among them, s5 specifically includes:

[0074] s51, using grayscale processing to compare the grayscale value differences of pixels, and determine whether they belong to basic graphic pixels or pattern pixels, and connect pixel mark position information;

[0075] Among them, s5 can also be processed in the following ways:

[0076] a51. Directly compare the basic graphics and patterns at corresponding positions, calculate the pattern or basic graphics to which the missing part belongs, and mark the position information.

[0077] a51 or s51, classification and marking are carried out according to the graphic pattern conditions, including marking according to different types and marking according to different monitoring conditions. Specifically, the position and size differences of the basic graphics are marked, and the missing patterns or stains are marked.

[0078] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0079] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0080] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0081] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0082] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods or systems. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects.

[0083] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0084] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

[0085] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The description and examples are to be considered exemplary only, and the true scope and spirit of the present invention is indicated by the claims above.

[0086] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A landscape road monitoring method based on image processing, characterized in that: include: Identify basic shapes in landscape road images; including: Obtain the unit graphics of landscape roads, and separate the basic graphics with regular shapes after analysis; The results of manual verification are used as a verification set and input into the model for image recognition until the recognition rate reaches a threshold. The types of basic graphics detected are numbered, and the number of multiple or one identical basic graphics in an image is numbered and sorted. Pixelate the basic graphic into a graphic including pixel points, calculate the pixel center point of the graphic, and connect the pixel center points of the same basic graphic; Output a center point trajectory of a type of basic graphics, record the location information of the trajectory corresponding to the landscape road image, perform perspective transformation on the graphics on the landscape road image into graphics on a two-dimensional plane, and record the perspective transformation information of the graphics corresponding to the location information; Analyzing the arrangement of graphic shapes in the image to be tested for matching a preset model, wherein the preset model includes an array arrangement model and a line arrangement model; analyzing the image to be tested includes: judging based on the dot matrix lines formed by the center points of the identified unit graphics, and when it is judged that the dot matrix forms an image as a line, matching the line arrangement model; and when it is judged that the dot matrix forms an image as a surface, matching the array arrangement model; and further specifically including: calculating the number of adjacent center points of each center point connection line, and when the center point count of the total connection line is greater than 3 times the number of center points, the dot matrix connection line is judged to be a surface, and the array arrangement model is matched; otherwise, the dot matrix connection line is a line, and the line arrangement model is matched; Selecting the preset model and generating a simulated picture of the landscape road according to the basic graphics; specifically including: According to the perspective transformation information of the graphics recording the corresponding position information, a reverse operation is performed, and the separated basic graphics are reversely perspective transformed based on the position information to generate graphics corresponding to the position of the simulated image; Generate basic graphics at corresponding positions based on the center point trajectory to obtain simulated negatives; The generated basic graphics are adaptively adjusted according to the edge position data of the basic graphics in the image corresponding to the center point, and the adjustment includes enlargement, reduction, and perspective transformation; When a pattern is included, the pattern is generated on an analog film to obtain an analog picture; When multiple patterns are included, multiple patterns are sequentially generated on the simulated film according to the hierarchical relationship of the patterns to obtain a simulated image; Compare and analyze the differences between the simulated pictures and the real landscape road images and mark the types of differences.

2. The landscape road monitoring method based on image processing according to claim 1, characterized in that: The pixelization of the basic graphic into a graphic including pixel points, calculating the center point of the graphic pixel, and connecting the center points of the pixels of the same basic graphic further specifically includes: When there are multiple groups of one or more patterns covering a basic graphic, the pixelation processing target is determined to be a unit graphic including one or more patterns, the shape of the unit graphic is used as the basic graphic content to be framed, and the pixelation processing is performed; When the pattern covers multiple basic graphics, the pixel processing target is determined to be a basic graphic, and pixel processing is performed after frame selection according to the graphic boundary.

3. The landscape road monitoring method based on image processing according to claim 2 is characterized in that: The comparative analysis of the differences between the simulated image and the real landscape road image and the marking of the difference types include: Grayscale processing is used to compare the grayscale value differences of pixels, and to determine whether they belong to basic graphic pixels or pattern pixels, and to mark the position information of connected pixels; Alternatively, directly compare the basic graphics and patterns at corresponding positions, calculate the pattern or basic graphics to which the missing part belongs, and mark the position information.

4. The landscape road monitoring method based on image processing according to claim 3 is characterized in that: Classification and marking are carried out according to the graphics and patterns, including marking according to different types and marking according to different monitoring conditions. Specifically, the position and size differences of the basic graphics are marked, and the missing patterns or stains are marked.

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