Rail transit station architectural drawing matrix compression method and system

Abstract

The invention discloses a rail transit station building drawing matrix compression method and system, and the method comprises the steps: extracting line segment information of building walls and structural columns in a station building drawing, and the line segment information comprises straight line segment information and arc line segment information; all arc segments are converted into corresponding straight line segments, and the segment length is calculated according to the radius of a column body of the structural column; extracting head and tail points of all line segments, obtaining X and Y coordinates of each head and tail point, sorting the X and Y coordinates, constructing an image matrix, and taking the X and Y coordinates as a horizontal axis and a longitudinal axis of the image matrix; the image matrix is filled with geometric information and attribute information of building elements, and the edge of the image matrix is filled with negative numbers through an edge filling technology to represent peripheral contour information of the rail transit station.

Description

Technical Field

[0001] The present invention belongs to the technical field of architectural drawing processing, and more specifically, relates to a matrix compression method and system for architectural drawings of rail transit stations. Background Art

[0002] With the rapid development of artificial intelligence technology, technologies such as deep learning and image recognition have shown great application potential in various fields. Especially in the field of rail transit, as an important part of urban transportation, the intelligent processing of station design and construction information is of great significance to improving operational efficiency and optimizing resource allocation. Traditional station design relies on tools such as CAD or BIM. Although these tools can provide accurate architectural design drawings, the data they generate is often unstructured and difficult to be directly used in intelligent algorithms such as deep learning.

[0003] Currently, the design drawings of rail transit stations are mainly generated through CAD or BIM software, which can create vector graphics containing rich architectural elements. However, these graphic data face challenges when converted into a matrix form that can be used for deep learning. Since the coordinate information of architectural elements has different precision units, such as millimeters, centimeters, meters, etc., directly converting the drawings into image matrices will result in the generation of an extremely large sparse matrix. This matrix not only consumes huge computing resources, but also makes it difficult to effectively express all the design details in the drawings.

[0004] Although CAD and BIM technologies have unparalleled advantages in the field of architectural design, such as high precision, flexibility, and rich expression of design elements, they have limitations in data structuring and intelligent application. The main disadvantages include the difficulty of directly converting data into a format suitable for machine learning algorithm processing and the high demand for computing resources when processing large-scale data. In addition, the mixed use of different precision units increases the complexity of data preprocessing.

[0005] In summary, although the existing CAD and BIM technologies have significant advantages in the field of architectural design, there are still challenges in intelligent processing and deep learning applications. Therefore, it is necessary to develop a new method that can maintain the integrity of station element information, adapt to the characteristics of units of different sizes, and reduce the demand for computing resources to achieve efficient and intelligent processing of station drawing information. Summary of the invention

[0006] In order to solve the above technical problems, the present invention proposes a matrix compression method for rail transit station architectural drawings, comprising:

[0007] Extracting line segment information of building walls and structural columns in the station building drawings, wherein the line segment information includes straight line segment information and arc segment information;

[0008] Convert all arc segments into corresponding straight line segments, and calculate the segment length according to the column radius of the structural column;

[0009] Extract the first and last points of all line segments, obtain the X and Y coordinates of each first and last point, sort the X and Y coordinates, and construct an image matrix, using the X and Y coordinates as the horizontal and vertical axes of the image matrix;

[0010] The geometric information and attribute information of the building elements are filled in the image matrix, and negative numbers are filled in the edge of the image matrix through edge filling technology to represent the peripheral contour information of the rail transit station.

[0011] Furthermore, converting all arc segments into corresponding straight line segments includes: adjusting the number of segments of the straight line segments according to the accuracy requirement.

[0012] Furthermore, it includes: dividing the arc segment of each structural column into 16 straight line segments.

[0013] Furthermore, it includes: the horizontal axis and the vertical axis of the image matrix are arranged according to the sorted X and Y coordinate serial numbers, and the actual physical coordinates of the midpoint of the image matrix are restored through the corresponding relationship between the serial number and the actual coordinates.

[0014] Furthermore, it includes: filling negative numbers at the edge of the image matrix, and coloring through the connection relationship between negative numbers and 0 values ​​to represent the surrounding contour information of the rail transit station.

[0015] The present invention also provides a matrix compression system for rail transit station architectural drawings, comprising:

[0016] An information extraction module is used to extract line segment information of building walls and structural columns in the station building drawings, wherein the line segment information includes straight line segment information and arc segment information;

[0017] The line segment conversion module is used to convert all arc segments into corresponding straight line segments and calculate the segment length according to the column radius of the structural column;

[0018] Generate a matrix module, which is used to extract the starting and ending points of all line segments, obtain the X and Y coordinates of each starting and ending point, sort the X and Y coordinates, and construct an image matrix, using the X and Y coordinates as the horizontal and vertical axes of the image matrix;

[0019] The filling module is used to fill the geometric information and attribute information of the building elements in the image matrix, and fill the edge of the image matrix with negative numbers through edge filling technology to represent the surrounding contour information of the rail transit station.

[0020] Furthermore, converting all arc segments into corresponding straight line segments includes: adjusting the number of segments of the straight line segments according to the accuracy requirement.

[0021] Furthermore, it includes: dividing the arc segment of each structural column into 16 straight line segments.

[0022] Furthermore, it includes: the horizontal axis and the vertical axis of the image matrix are arranged according to the sorted X and Y coordinate serial numbers, and the actual physical coordinates of the midpoint of the image matrix are restored through the corresponding relationship between the serial number and the actual coordinates.

[0023] Furthermore, it includes: filling negative numbers at the edge of the image matrix, and coloring through the connection relationship between negative numbers and 0 values ​​to represent the surrounding contour information of the rail transit station.

[0024] In general, the above technical solution conceived by the present invention has the following beneficial effects compared with the prior art:

[0025] The technical solution proposed in the present invention converts the architectural drawings of rail transit stations into efficient and high-precision matrix representations through an innovative method, and has the following significant technical effects:

[0026] 1. Significant improvement in productivity:

[0027] Through the automated data conversion process, the time for manual drawing and data processing is reduced, and the conversion efficiency from architectural drawings to data matrices is greatly improved. This not only speeds up the work in the design and planning stages, but also provides a rapid response capability for subsequent construction and operation management.

[0028] 2. Improvement of quality and precision:

[0029] The invention ensures high-precision conversion of architectural drawing information through accurate coordinate point extraction and matrix construction. Compared with traditional methods, the invention can more accurately reflect the spatial relationship and size information of architectural elements, thereby improving design quality and construction accuracy.

[0030] 3.Simplification of intelligent design process:

[0031] Converting complex architectural drawing information into structured matrix data simplifies the subsequent data processing and analysis process. This simplification not only reduces the complexity of the design and construction process, but also reduces the possibility of errors and improves the reliability of the entire project.

[0032] 4. Beneficial expansion of the value of drawing information:

[0033] The matrix data of the present invention not only contains the geometric information of the building elements, but also represents the attribute information of the elements through different numerical values, such as wall type, column type, etc. This rich information representation provides more useful features for deep learning and image recognition, enabling machines to better understand and analyze architectural drawings.

[0034] In summary, the technical solution of the present invention has shown remarkable beneficial effects in improving productivity, ensuring quality and precision, simplifying intelligent design processes, favorably expanding information value, demonstrating innovation and foresight, and improving economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flow chart of the method of embodiment 1 of the present invention;

[0036] Figure 2 System structure diagram of embodiment 2 of the present invention. DETAILED DESCRIPTION

[0037] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0038] The method provided by the present invention can be implemented in the following terminal environment, and the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method described in the following embodiment.

[0039] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts in the entire terminal, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and calling data stored in the storage medium.

[0040] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets or instructions.

[0041] The display screen is used to display the user interface of each application.

[0042] In addition, those skilled in the art can understand that the structure of the above terminal does not constitute a limitation on the terminal, and the terminal may include more or fewer components, or combine certain components, or arrange the components differently. For example, the terminal also includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, and a power supply, which will not be described in detail here.

[0043] Example 1

[0044] like Figure 1 As shown, an embodiment of the present invention provides a method for matrix compression of rail transit station architectural drawings, comprising:

[0045] Extracting line segment information of building walls and structural columns in the station building drawings, wherein the line segment information includes straight line segment information and arc segment information;

[0046] Convert all arc segments into corresponding straight line segments, and calculate the segment length according to the column radius of the structural column;

[0047] Extract the first and last points of all line segments, obtain the X and Y coordinates of each first and last point, sort the X and Y coordinates, and construct an image matrix, using the X and Y coordinates as the horizontal and vertical axes of the image matrix;

[0048] The geometric information and attribute information of the building elements are filled in the image matrix, and negative numbers are filled in the edge of the image matrix through edge filling technology to represent the peripheral contour information of the rail transit station.

[0049] Specifically, converting all arc segments into corresponding straight line segments includes: adjusting the number of segments of the straight line segments according to the accuracy requirement.

[0050] Specifically, it includes: dividing the arc segment of each structural column into 16 straight line segments.

[0051] Specifically, the horizontal axis and the vertical axis of the image matrix are arranged according to the sorted X and Y coordinate serial numbers, and the actual physical coordinates of the midpoints of the image matrix are restored through the corresponding relationship between the serial numbers and the actual coordinates.

[0052] Specifically, it includes: filling negative numbers at the edge of the image matrix, and coloring through the connection relationship between negative numbers and 0 values ​​to represent the surrounding contour information of the rail transit station.

[0053] Specifically, it also includes setting a coordinate point compression model, and further compressing the image matrix through the coordinate point compression model to reduce the complexity of the image matrix, and the coordinate point compression model includes:

[0054]

[0055] Where C(x, y) is the new image matrix containing all points (x, y), N is the number of compression layers, each layer compresses different architectural elements, g is a multi-dimensional adaptive compression function used to increase the capture details of architectural drawing elements, ρ is a dynamic weight adjustment function used to adaptively adjust the compression according to position changes, and L k The constraint function is connected to the k-th layer of multi-level architectural elements, which is used to make nonlinear adjustments for each layer compression of architectural drawing elements, while ensuring that the geometric distance and complexity relationship between elements are effectively compressed.

[0056] The multi-dimensional adaptive compression function g is:

[0057]

[0058] Among them, x i is the horizontal coordinate of the i-th point, y i is the ordinate of the i-th point, ∈ is the adaptive first adjustment factor, α is the adaptive second adjustment factor, θ is the adaptive third adjustment factor, λ is the adaptive fourth adjustment factor, and μ is the adaptive fifth adjustment factor.

[0059] The dynamic weight adjustment function ρ is:

[0060]

[0061] Among them, ζ is the first adjustment factor of dynamic weight, x j is the horizontal coordinate of the jth point, y j is the ordinate of the jth point, and η is the second adjustment factor of the dynamic weight.

[0062] The connection constraint function L of the k-th layer of multi-level building elements k for:

[0063]

[0064] Among them, γ k is the first adjustment factor of the kth layer, n k is the second adjustment factor of the kth layer, β k is the third adjustment factor of the kth layer.

[0065] In order to make this embodiment clearer, the following describes embodiment 1 in detail, as shown below:

[0066] The architectural drawings of rail transit stations are composed of building walls and structural columns, which are in turn composed of line segments and arcs. We obtain all the line segments and arcs (generally complete circles) belonging to the building walls and structural columns through the CAD interface.

[0067] Since arc segments are generally used for station bearing structure columns, that is, a complete circle, we need to convert all arc segments into corresponding straight line segments. The length of each decomposed segment is calculated according to the radius of the column. Under normal accuracy, the arc required for each column is divided into about 16 segments to meet the conversion requirements. The number of segments can also be adjusted according to actual needs. The higher the number of segments, the higher the accuracy. We sample the arc segment according to the number of segments. The number of segments is consistent with the number of sampling points. In the clockwise direction, each adjacent sampling point constitutes a line segment, realizing the conversion of arc segments into straight line segments.

[0068] So far, we have obtained all the line segments representing the building drawings. Since each line segment is composed of two points at the beginning and the end, we extract the points of all the line segments and obtain the X and Y coordinates of each point.

[0069] If at this time, we directly construct a matrix based on all X and Y coordinates, fill in the relevant information of each point in the matrix, and the position of the point in the matrix is ​​represented by 1. Our method is to divide the matrix into equal parts. If we want to ensure accuracy, we will represent the accuracy as 10mm. Generally, a single-layer station is 200 meters long and 25 meters wide. The matrix is ​​200000x25000 elements in size, which means there is a lot of useless data and it is difficult to get actual calculations.

[0070] Therefore, we improved the traditional method and no longer used the X and Y coordinates of the points to directly represent the matrix, but formed the matrix through the relative relationship of the coordinate points. Generally, the concourse layer of a station is the most complex and contains the most information. The number of line segments that make up the architectural element information is about 3,000. After extracting the first point of the line segment and removing the duplicate points (the two end line segments are connected, and their respective connection points are actually one point), the actual number of points is about 2,000.

[0071] We extract and sort the X and Y axis data of all points respectively, and round off or discard the remainder with an accuracy of 10mm (the accuracy can be set freely). Arrange the sequence numbers of all points on the X axis after sorting as the horizontal axis of the matrix, and arrange the sequence numbers of all points on the Y axis after sorting as the vertical axis of the matrix to construct the matrix. All positions of the initial matrix are represented by 0, and the position where the point sorting sequence number exists is represented by 1. For example, in 1-dimensional data, considering only the X axis, I have three points of data 0, 10, and 100. The traditional method: its sequence size is 11, and the content is [1,1,0,0,0,0,0,0,0,0,1]. The improved method: its sequence size is 3, and the content is [1,1,1], which respectively represents the arrangement order of [0,10,100] 1, 2, and 3.

[0072] When we arrange the points according to their sorted serial numbers as the horizontal and vertical axes of the matrix, although the size of the matrix can be greatly reduced, the matrix actually represents only the sorting information of the point in all the data, rather than the real physical coordinate information, so we need to design a method to restore the position of the actual coordinate point through the matrix. Using the example in the previous step, if the element serial numbers of [1,1,1] are 0, 1, and 2 respectively, when we want to get the actual data of [1,1,1] with serial number 2 (that is, 100), we know that the target serial number is 2. At the same time, because we have sorted the actual data of the X-axis, we also store the sorted queue [0, 10, 100] (serial numbers are 0, 1, and 2 respectively). At this time, we take out the data with serial number 2 in the sorted queue of the actual data of the X-axis, that is, 100, which is the actual data represented by the target object.

[0073] At the same time, this method can also be reversed. When we want to get the position of the data 100 in the matrix, we can also get its serial number through the position of 100 in the series and bring its serial number into the matrix position.

[0074] So far, through the conversion of the serial number, we have used a matrix and two sorted series to represent the high-precision matrix information of the station building map. Generally, the matrix size is 600x300 elements, the X-axis sequence is 600 elements, and the Y-axis is 300 elements, which greatly reduces the matrix size of the station building element information. The size of the matrix is ​​mainly determined by the relative connection relationship of the building element line segments and is less affected by the accuracy.

[0075] At the same time, since we have the connection relationship between all the points of the line segment, our current matrix only fills the relevant information of the point, and does not contain the line segment information. Therefore, we need to infer the horizontal and vertical axis serial numbers of the matrix related points through the actual position of the line segment point, and then fill the data between the connected points in the matrix with 1 to represent the line segment. Similarly, for example, in 1-dimensional data, the data is [0,1,0,0,1,0]. When we know that the points of sequence 1 and sequence 4 form a line segment, we modify the sequence content and turn it into [0,1,1,1,1,0]. So far, we have represented the high-precision data of the station through the optimized dynamic matrix and two sequences.

[0076] Through the above construction, although we have used the matrix to represent the high-precision data of the station, in order to use the matrix for subsequent applications such as spatial contour recognition, graphic detection, and data classification, we still need to optimize the matrix.

[0077] Optimization 1-Spatial Contour Recognition: In order to achieve that the matrix can represent the spatial contour of the civil engineering room, if the matrix is ​​closely arranged, for example, in a very simple rectangular room, the matrix may become [[1,1], [1,1]], that is, the space is dynamically optimized to 0 area, and the matrix loses some spatial information. Therefore, we adjust the relationship between the previous sorting sequence number and the matrix number, and adjust the corresponding relationship by multiples. For example, the previous data 0, 10, 100 points, the original one-to-one correspondence sequence is [1,1,1]. We multiply the corresponding sequence by the coefficient 2, and the converted sequence is [1,0,1,0,1], so that the adjacent points maintain a certain distance, which can avoid the problem of spatial information loss by enlarging the matrix size. At the same time, the matrix magnification is related to the corresponding coefficient. According to the current station dynamic optimization matrix multiplied by the coefficient is generally 1200x600 elements in size, which can still be perfectly used in feature recognition, spatial contour recognition, and graphic detection. For example, the matrix of the rectangular room mentioned earlier becomes [[1,1,1],[1,0,1],[1,1,1]], which retains its spatial information.

[0078] Optimization 2- Representation of attribute information: Previously, we simply used 1 and 0 to represent the architectural element information in the matrix. However, through the line segments we obtained on CAD, we can know the layer information of the wall or column to which the line segment belongs, as well as other information such as wall type and column type. This information can be represented by line segment layers, colors, linearity, etc. in CAD. Therefore, we can define the relevant architectural element attributes that we are concerned about and need, and represent the architectural element information in the matrix through different values ​​such as 1, 2, 3, or different magnitudes of 1, 100, 1000, etc., so that the matrix not only stores the geometric information of the architectural elements, but also stores the non-geometric information.

[0079] Optimization 3- Filling of edge information: According to the previous method, the edge of the matrix represents the information of the outermost contour line around the building, but lacks the relevant information of the outer contour line and the outer contour space. Therefore, referring to the convolutional neural network, we use the filling technology to expand the edge of the matrix and fill it with negative numbers such as -1. For example, the original matrix [[1,0],[1,1]] becomes [-1,-1,-1,-1],[-1,1,0,-1],[-1,1,1,-1],[-1,-1,-1,-1], and then through the coloring method, all 0 values ​​connected to negative numbers are changed to -1, and the matrix becomes [-1,-1,-1,-1],[-1,1,-1,-1],[-1,1,1,-1],[-1,-1,-1,-1],[-1,-1,-1,-1]. In this way, negative numbers can be used to represent the relevant information of the contours around all buildings. At the same time, because the information of the surrounding contours is filled, the matrix can be directly used for graph convolution deep learning. The size of the fill, that is, the amount of edge fill, can be adjusted according to actual project use. Generally, a fill size of 2 is sufficient.

[0080] Example 2

[0081] like Figure 2 As shown, an embodiment of the present invention further provides a matrix compression system for rail transit station architectural drawings, comprising:

[0082] An information extraction module is used to extract line segment information of building walls and structural columns in the station building drawings, wherein the line segment information includes straight line segment information and arc segment information;

[0083] The line segment conversion module is used to convert all arc segments into corresponding straight line segments and calculate the segment length according to the column radius of the structural column;

[0084] Generate a matrix module, which is used to extract the starting and ending points of all line segments, obtain the X and Y coordinates of each starting and ending point, sort the X and Y coordinates, and construct an image matrix, using the X and Y coordinates as the horizontal and vertical axes of the image matrix;

[0085] The filling module is used to fill the geometric information and attribute information of the building elements in the image matrix, and fill the edge of the image matrix with negative numbers through edge filling technology to represent the surrounding contour information of the rail transit station.

[0086] Specifically, converting all arc segments into corresponding straight line segments includes: adjusting the number of segments of the straight line segments according to the accuracy requirement.

[0087] Specifically, it includes: dividing the arc segment of each structural column into 16 straight line segments.

[0088] Specifically, the horizontal axis and the vertical axis of the image matrix are arranged according to the sorted X and Y coordinate serial numbers, and the actual physical coordinates of the midpoints of the image matrix are restored through the corresponding relationship between the serial numbers and the actual coordinates.

[0089] Specifically, it includes: filling negative numbers at the edge of the image matrix, and coloring through the connection relationship between negative numbers and 0 values ​​to represent the surrounding contour information of the rail transit station.

[0090] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0091] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0092] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0094] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0096] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A matrix compression method for rail transit station architectural drawings, characterized in that: include: Extracting line segment information of building walls and structural columns in the station building drawings, wherein the line segment information includes straight line segment information and arc segment information; Convert all arc segments into corresponding straight line segments, and calculate the segment length according to the column radius of the structural column; Extract the first and last points of all line segments, obtain the X and Y coordinates of each first and last point, sort the X and Y coordinates, and construct an image matrix, using the X and Y coordinates as the horizontal and vertical axes of the image matrix; The geometric information and attribute information of the building elements are filled in the image matrix, and negative numbers are filled in the edge of the image matrix through edge filling technology to represent the peripheral contour information of the rail transit station.

2. A method for matrix compression of rail transit station architectural drawings as claimed in claim 1, characterized in that: Converting all arc segments into corresponding straight line segments includes: the number of segments of the straight line segment is adjusted according to the accuracy requirements.

3. A matrix compression method for rail transit station architectural drawings as claimed in claim 2, characterized in that: include: Divide the arc segment of each structural column into 16 straight line segments.

4. A matrix compression method for rail transit station architectural drawings as claimed in claim 1, characterized in that: include: The horizontal axis and the vertical axis of the image matrix are arranged according to the sorted X and Y coordinate serial numbers, and the actual physical coordinates of the midpoint of the image matrix are restored through the corresponding relationship between the serial numbers and the actual coordinates.

5. A method for matrix compression of rail transit station architectural drawings as claimed in claim 1, characterized in that: include: Negative numbers are filled at the edge of the image matrix, and the surrounding contour information of the rail transit station is represented by coloring through the connection relationship between the negative numbers and the 0 value.

6. A matrix compression system for rail transit station architectural drawings, characterized in that: include: An information extraction module is used to extract line segment information of building walls and structural columns in the station building drawings, wherein the line segment information includes straight line segment information and arc segment information; The line segment conversion module is used to convert all arc segments into corresponding straight line segments and calculate the segment length according to the column radius of the structural column; Generate a matrix module, which is used to extract the starting and ending points of all line segments, obtain the X and Y coordinates of each starting and ending point, sort the X and Y coordinates, and construct an image matrix, using the X and Y coordinates as the horizontal and vertical axes of the image matrix; The filling module is used to fill the geometric information and attribute information of the building elements in the image matrix, and fill the edge of the image matrix with negative numbers through edge filling technology to represent the surrounding contour information of the rail transit station.

7. A rail transit station architectural drawing matrix compression system as claimed in claim 6, characterized in that: Converting all arc segments into corresponding straight line segments includes: the number of segments of the straight line segment is adjusted according to the accuracy requirements.

8. A rail transit station architectural drawing matrix compression system as claimed in claim 7, characterized in that: include: Divide the arc segment of each structural column into 16 straight line segments.

9. A rail transit station architectural drawing matrix compression system as claimed in claim 6, characterized in that: include: The horizontal axis and the vertical axis of the image matrix are arranged according to the sorted X and Y coordinate serial numbers, and the actual physical coordinates of the midpoint of the image matrix are restored through the corresponding relationship between the serial numbers and the actual coordinates.

10. A rail transit station architectural drawing matrix compression system as claimed in claim 6, characterized in that: include: Negative numbers are filled at the edge of the image matrix, and the surrounding contour information of the rail transit station is represented by coloring through the connection relationship between the negative numbers and the 0 value.

Images