Transmission data processing method for building information issuing system

Abstract

The invention relates to the technical field of data processing, in particular to a transmission data processing method for a building information publishing system, and the method comprises the steps: dividing building monitoring video data of a building area into building image data at a plurality of moments, and determining the picture expression degree of the building image data; determining the building picture expressivity of a building newly-added area in the first difference image at the current moment; according to the building image data at each moment in the continuous video data range of the building image data at the current moment, correcting the building picture expressivity to obtain the corrected building picture expressivity; and determining the transmission priority of the building image data at the current moment, and controlling the building information publishing system to transmit the building image data based on the transmission priority. Therefore, the transmission quality of the building monitoring video data of the building information publishing system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a method for processing transmission data for a building information publishing system. Background Art

[0002] With the advancement of the building informatization process, building monitoring systems play an increasingly important role in ensuring building safety, real-time monitoring of the building environment, and providing building information data support. Building monitoring video data is an essential part of building management. Especially in application scenarios such as building security monitoring, construction site monitoring, and emergency response, the monitoring video data provides crucial visual information.

[0003] In some scenarios, the building information publishing system often transmits data in the order in which the building monitoring video data is generated. It may give priority to transmitting some data that is irrelevant to core information such as building safety and personnel activities, such as environmental noise or irrelevant background information, while some key information containing building changes fails to be transmitted in a timely manner. There is no priority division according to the different importance of the video data, resulting in some key building information not being transmitted in a timely manner. Thus, the transmission quality of the building monitoring video data of the building information publishing system is low, which affects the building management efficiency. Summary of the Invention

[0004] In order to solve the technical problem of the low transmission quality of the building monitoring video data of the building information publishing system, the purpose of the present invention is to provide a method for processing transmission data for a building information publishing system.

[0005] The specific technical solutions adopted to solve the above technical problems are as follows: An embodiment of the present invention provides a method for processing transmission data for a building information publishing system, including: dividing the building monitoring video data of a building area into building image data at multiple moments, and determining the picture performance degree of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data at each moment; determining the building picture performance of the newly added building area in the first difference image at the current moment according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood, where the first difference image is the difference between the gray values of the pixel points at the same position in the building image data at adjacent moments; correcting the building picture performance according to the building image data at each moment in the continuous video data range of the building image data at the current moment to obtain the corrected building picture performance; determining the transmission priority degree of the building image data at the current moment according to the picture performance degree of the building image data, the corrected building picture performance of the building image data at the current moment, and the corrected building picture performance of the building image data at all moments in the continuous video data range, and controlling the building information publishing system to transmit the building image data based on the transmission priority degree.

[0006] Optionally, determining the picture performance degree of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data at each moment includes: calculating the first product between the average gradient value and the number of gray levels in the building image data at each moment, and calculating the absolute value of the first difference between the average gray value and a predetermined value; calculating the first sum value between the absolute value of the first difference and a hyperparameter; determining the first ratio between the first product and the first sum value as the picture performance degree of the building image data.

[0007] Optionally, determining the architectural picture representation of the newly added building area in the first difference image at the current moment based on the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood includes: determining the regional gray consistency of the first change area in the first difference image according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood; using the mapping method to obtain the second change area corresponding to the first change area in the first difference image from the building image data at the current moment and the building image data at the next adjacent moment; taking the ratio of the number between the intersection sequence and the union sequence of the position coordinates of the edge pixel points of the second change area in the building image data at the current moment and the edge pixel points of the second change area in the building image data at the next adjacent moment as the edge position invariance of the second change area; determining the severity of texture change of the second change area according to the first average value of the local binary pattern values of the edge pixel points of the second change area in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixel points of the second change area in the building image data at the next adjacent moment; determining the possibility that the first change area corresponding to the second change area in the first difference image belongs to the newly added building area according to the regional gray consistency, edge position invariance, and severity of texture change; taking the first change area with a possibility greater than or equal to the first threshold as the newly added building area in the first difference image; taking the third average value of the local binary pattern values of all pixel points in the newly added building area in the first difference image at the current moment as the richness of construction details of the newly added building area; determining the architectural picture representation of the building image data at the current moment according to the fourth average value of the richness of construction details of all newly added building areas in the first difference image at the current moment, the area of each newly added building area in the first difference image at the current moment, and the number of newly added building areas in the first difference image at the current moment.

[0008] Optionally, determining the regional gray consistency of the first change area in the first difference image according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood includes: performing inverse proportional normalization on the mean value of the absolute value of the difference between the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood to obtain the gray consistency of the pixel points in the first difference image; clustering the gray consistency of all pixel points in the first difference image to obtain multiple clustering clusters, each clustering cluster being used as a first change area in the first difference image, and taking the mean value of the gray consistency of all pixel points in each first change area as the regional gray consistency of each first change area.

[0009] Optionally, determining the severity of texture change in the second change region based on the first average value of the local binary pattern values of the edge pixels in the second change region in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixels in the second change region in the building image data at the next adjacent moment includes: Calculating the first average value of the local binary pattern values of the edge pixels in the second change region in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixels in the second change region in the building image data at the next adjacent moment; determining the absolute value of the difference between the first average value and the second average value as the severity of texture change in the second change region.

[0010] Optionally, determining the likelihood that the first change region corresponding to the second change region in the first difference image belongs to a newly added building region based on regional gray consistency, edge position invariance, and severity of texture change includes: calculating the second product between regional gray consistency and edge position invariance, and calculating the second ratio between the severity of texture change and the second product; performing normalization processing on the second ratio to obtain the likelihood.

[0011] Optionally, determining the representativeness of the building image data at the current moment based on the fourth average value of the richness of construction details of all newly added building regions in the first difference image at the current moment, the area of each newly added building region in the first difference image at the current moment, and the number of newly added building regions in the first difference image at the current moment includes: adding up the areas of each newly added building region to obtain the superimposed area, and calculating the third product between the superimposed area, the fourth average value, and the number of newly added building regions; performing normalization processing on the third product to obtain the representativeness of the building image.

[0012] Optionally, the building picture expressiveness is corrected according to the building picture data at each moment in the continuous video data range of the building picture data at the current moment. Obtaining the corrected building picture expressiveness includes: taking the building picture data at multiple consecutive moments after the current moment as the continuous video data range; calculating the second difference image between the building picture data at each moment in the continuous video data range of the building picture data at the current moment and the building picture data at the current moment; recording all the newly added building areas in each second difference image as the total newly added building area in each second difference image, obtaining a sequence of total newly added building areas arranged in chronological order, taking the first total newly added building area in the sequence of total newly added building areas as the target area, and other total newly added building areas as the reference areas; taking the intersection area between the target area and the reference areas as the building progress area; taking the normalized value of the area of the non-overlapping area between adjacent building progress areas as the building information change factor of the previous building progress area; taking the normalized value of the number of edge pixel points of the overlapping area between adjacent building progress areas as the non-building equipment information change factor of the previous building progress area; calculating the fourth product between the building information change factor and the non-building equipment information change factor of each building progress area; and superimposing the fourth products of each building progress area to obtain a superimposed value; normalizing the superimposed value to obtain the building information change value at the current moment; determining the fifth product between the building information change value and the building picture expressiveness as the corrected building picture expressiveness.

[0013] Optionally, according to the picture expression degree of the building picture data, the corrected building picture expressiveness of the building picture data at the current moment, and the corrected building picture expressiveness of the building picture data at all moments in the continuous video data range, determining the transmission priority degree of the building picture data at the current moment includes: taking the maximum value of the absolute value of the difference between the picture expression degree of the building picture data at the current moment and the picture expression degrees of the building picture data at all moments in the continuous video data range as the importance factor of the building picture data at the current moment; calculating the sixth product between the importance factor and the corrected building picture expressiveness at the current moment, and performing a normalization process on the sixth product to obtain the building picture importance degree of the building picture data at the current moment; taking the average value of the building picture importance degree of the building picture data at the current moment and the building picture importance degrees of the building picture data at each moment in the continuous video data range of the building picture data at the current moment as the transmission priority degree of the building picture data at the current moment.

[0014] Optionally, controlling the building information publishing system to transmit building image data based on the transmission priority includes: regarding the building image data with a transmission priority greater than or equal to the second threshold as the priority transmission object, and regarding the building image data with a transmission priority less than the second threshold as the object to be transmitted; using the building information publishing system to transmit the priority transmission object to the database after lossless compression, and using the building information publishing system to transmit the object to be transmitted to the database after lossy compression.

[0015] The present invention has the following beneficial effects: First, divide the building monitoring video data of the building area into building image data of multiple moments, and determine the picture performance degree of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data of each moment; Secondly, determine the building picture performance of the newly added building area in the first difference image at the current moment according to the gray value of the pixel point in the first difference image and the gray values of the pixel points in its neighborhood. The first difference image is the difference between the gray values of the pixel points at the same position in the building image data of adjacent moments; Then, correct the building picture performance according to the building image data of each moment in the continuous video data range of the building image data at the current moment to obtain the corrected building picture performance; Finally, determine the transmission priority of the building image data at the current moment according to the picture performance degree of the building image data, the corrected building picture performance of the building image data at the current moment, and the corrected building picture performance of the building image data of all moments in the continuous video data range, and control the building information publishing system to transmit the building image data based on the transmission priority.

[0016] In this way, the embodiment of the present invention can determine the transmission priority of the building image data at each moment according to the picture performance degree of the building image data at each moment and the performance of the building picture within the continuous video data range at each moment during the transmission process of the building monitoring video data. Thus, important and critical building image data can be preferentially transmitted according to the transmission priority, thereby improving the transmission quality of the building monitoring video data of the building information publishing system and improving the building management efficiency. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of a method for processing transmission data for a building information publishing system provided by an embodiment of the present invention; Figure 2 The structural schematic diagram of a transmission data processing device for a building information release system provided by an embodiment of the present invention. Detailed implementation manners

[0019] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following combines the accompanying drawings and preferred embodiments to specifically describe in detail a transmission data processing method for a building information release system according to the present invention, its specific implementation manners, structures, features and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0021] The following specifically describes the specific solution of a transmission data processing method for a building information release system provided by the present invention with reference to the accompanying drawings.

[0022] Embodiment 1: Please refer to Figure 1 , which shows the flowchart of a transmission data processing method for a building information release system provided by an embodiment of the present invention, including: Step S101: Divide the building monitoring video data of the building area into building image data at multiple moments, and determine the picture performance degree of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data at each moment.

[0023] Specifically, in the embodiment of the present invention, a high-definition camera is selected and it is ensured that the high-definition camera can cover the entire building area and monitor at a fixed angle to obtain building monitoring video data. Among them, the installation angle and height of the high-definition camera need to ensure that the entire building area can be clearly captured, and avoid occlusion and blind spots, and avoid direct sunlight, especially when the sun shines directly during the day, which may affect the image clarity. Therefore, in the embodiment of the present invention, a camera with the ability to automatically adjust the light is selected. In the building monitoring video data, every 1 hour is taken as a moment, and the building monitoring video data is divided into building image data at several moments.

[0024] Further, in order to preferentially transmit more important information, it is necessary to determine the importance of the building image data at each moment during the transmission of building monitoring video data. When judging the importance of the building image data at each moment during the data transmission process, the importance of the data during the transmission process can be determined by analyzing the degree of presentation of the single-moment building image data and the presentation of consecutive building video images. For the image of the single-moment building image data, key information presented by the building image data needs to be concerned, but the importance of the current moment's building image data cannot be determined only by the image of the single-moment building image data. For the images of consecutive building video images, the difference in presentation between consecutive building video images also has a certain influencing factor on the importance of the current moment's building image data during the data transmission process. Therefore, it is necessary to further analyze the difference in presentation between consecutive building video images to obtain the importance of the building image data at each moment.

[0025] Further, in the building monitoring video data of the embodiment of the present invention, the time range composed of the subsequent 11 moments of the moment is used as the consecutive video data range of the moment.

[0026] Further, the more the number of gray levels in the building image data, the greater the average gradient value, indicating that the detail level of the building image data is higher and the content presentation is more complex. When the average gray value in the building image data is too small or too large, the building image data will appear very dark or very bright, indicating that the image in the building image data is relatively monotonous. It can be considered that the current image is at night or during the worker's rest time during the day, and no building work is carried out, so the content it presents is not obvious and not important. Therefore, the importance of the image during the transmission process is relatively low. Therefore, the embodiment of the present invention calculates the degree of presentation of the building image data at each moment by using the number of gray levels, gradient, and gray value in the building image data. Among them, as an optional embodiment of the present invention, determining the degree of presentation of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data at each moment includes: calculating the first product between the average gradient value and the number of gray levels in the building image data at each moment, and calculating the absolute value of the first difference between the average gray value and a predetermined value; calculating the first sum value between the absolute value of the first difference and a hyperparameter; determining the first ratio between the first product and the first sum value as the degree of presentation of the building image data.

[0027] Specifically, the predetermined value can be taken as 128. The embodiment of the present invention specifically uses the following formula to calculate the degree of presentation of the building image data: In the above formula, represents the degree of screen representation of the building image data at the th moment. represents the average gradient value in the building image data at the th moment. represents the number of gray levels in the building image data at the th moment. represents the average gray value in the building image data at the th moment. represents a preset hyperparameter, which is preset in the embodiments of the present invention as , and is used to prevent the denominator from being 0.

[0028] Step S102: Determine the building picture representation of the newly added building area in the first difference image at the current moment according to the gray value of the pixel point in the first difference image and the gray values of the pixel points in its neighborhood.

[0029] Among them, the first difference image is the difference between the gray values of the pixel points at the same position in the building image data at adjacent moments.

[0030] Specifically, when there is a change in the screen between the building image data at a single moment and the building image data at a single moment within the range of its continuous video data, it indicates that workers are performing construction work and achieving obvious results in the building monitoring video during the current time period. Compared with the stable video image screen, the rapidly changing video image screen obviously shows more key information, so it is more important during the data transmission process. Therefore, it is necessary to compare the building image data at the current moment with the building image data at a single moment within the range of its continuous video data. If the performance difference between the building image data is large, it means that there is a large change between the building image data at the current moment and the building image data at a certain moment within the range of its continuous video data, and its importance during the data transmission process is higher. Therefore, it is necessary to obtain the importance of the building picture of the building image data at each moment and determine the building picture representation of the building image data based on this.

[0031] Further, as an optional embodiment of the present invention, determining the building picture expressiveness of the newly added building area in the first difference image at the current moment according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood includes: determining the regional gray consistency of the first change area in the first difference image according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood; obtaining the second change area corresponding to the first change area in the first difference image from the building image data at the current moment and the building image data at the next adjacent moment by using the mapping method; taking the ratio of the number between the intersection sequence and the union sequence of the position coordinates of the edge pixel points of the second change area in the building image data at the current moment and the edge pixel points of the second change area in the building image data at the next adjacent moment as the edge position invariance of the second change area; determining the severity of texture change of the second change area according to the first average value of the local binary pattern values of the edge pixel points of the second change area in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixel points of the second change area in the building image data at the next adjacent moment; determining the possibility that the first change area corresponding to the second change area in the first difference image belongs to the newly added building area according to the regional gray consistency, edge position invariance, and severity of texture change; taking the first change area with a possibility greater than or equal to the first threshold as the newly added building area in the first difference image; taking the third average value of the local binary pattern values of all pixel points in the newly added building area in the first difference image at the current moment as the richness of construction details of the newly added building area; determining the building picture expressiveness of the building image data at the current moment according to the fourth average value of the richness of construction details of all newly added building areas in the first difference image at the current moment, the area of each newly added building area in the first difference image at the current moment, and the number of newly added building areas in the first difference image at the current moment.

[0032] Specifically, in the embodiment of the present invention, the gray values of the pixel points at the same positions in the building image data at the th moment and the th moment are subtracted from each other (the th moment minus the th moment) to obtain the first difference image. For the th pixel point in the first difference image, the gray value of the th pixel point represents its gray change under two different moments. If the gray difference between the th pixel point and the pixel points in its eight-neighborhood is smaller, it indicates that the The greater the consistency of the gray-scale changes of the pixels. As an optional embodiment of the present invention, determining the regional gray-scale consistency of the first change region in the first difference image according to the gray-scale value of the pixel in the first difference image and the gray-scale values of the pixels in its neighborhood includes: performing inverse proportional normalization on the mean value of the absolute values of the differences between the gray-scale value of the pixel in the first difference image and the gray-scale values of the pixels in its neighborhood to obtain the gray-scale consistency of the pixels in the first difference image; clustering the gray-scale consistency of all the pixels in the first difference image to obtain a plurality of clustering clusters, and each clustering cluster is used as a first change region in the first difference image, and taking the mean value of the gray-scale consistency of all the pixels in each first change region as the regional gray-scale consistency of each first change region.

[0033] Specifically, in the embodiment of the present invention, the mean value of the absolute values of the differences between the gray-scale value of the th pixel and the gray-scale values of the pixels in its eight-neighborhood is subjected to inverse proportional normalization as the gray-scale consistency of the th pixel in the first difference image. In the first difference image, the K-means clustering algorithm is used to cluster the gray-scale consistency of all the pixels in the first difference image to obtain several clustering clusters, and the area to which each clustering cluster belongs is used as a change region in the first difference image, that is, the first change region. In the embodiment of the present invention, the mean value of the gray-scale consistency of all the pixels in each first change region is used as the regional gray-scale consistency of each first change region. Among them, the value of K in the K-means clustering algorithm can be obtained by the elbow method in the known technology, and the embodiment of the present invention will not elaborate here.

[0034] Furthermore, for the th change region in the first difference image, that is, the first change region, the embodiment of the present invention obtains the th moment and the th moment of the building image data of the th change region, that is, the second change region, through a mapping method.

[0035] Furthermore, in the embodiments of the present invention, in the building monitoring video data, the construction invariant regions generally refer to the background in the building monitoring video data and the static parts of the building (such as walls, windows, floor slabs, etc.), which will have large gray-scale changes at different times affected by the environment, but the gray-scale values of these regions are relatively stable. And because the structures of these regions (such as building walls, door and window frames, etc.) are often static in the monitoring video, their texture and edge features will not change significantly over time. While the construction change regions have large gray-scale changes at different times because these regions will undergo varying degrees of changes during the construction process. For example, the alteration of walls and windows will cause significant changes in the texture and gray-scale of these regions. Therefore, if the edge texture of the th change region remains unchanged in the first difference image and the gray-scale change consistency is greater, it indicates that the th change region belongs to the construction invariant region. If the edge texture of the th change region undergoes drastic changes in the first difference images at two moments and the gray-scale change consistency is smaller, it indicates that the th change region may belong to the newly added area of the building. Therefore, during the building construction process in the embodiments of the present invention, the newly added structures of the building usually cause large changes in the regional edge information, and this change usually manifests as a large number of new edge pixel points appearing in the building image data, resulting in the size of the union being much larger than the size of the intersection. Therefore, in the embodiments of the present invention, if the ratio of the intersection to the union is smaller, it means that the edge information of the change region has undergone large changes, which are caused by construction activities. Then, using the Canny edge detection algorithm, obtain the edge pixel points of the th second change region in the building image data at the th moment and the th moment. Take the ratio of the number between the intersection sequence and the union sequence of the position coordinates of all edge pixel points of the th second change region in the building image data at the th moment and the th moment as the edge position invariance of the th second change region.

[0036] Further, as an optional embodiment of the present invention, determining the texture change severity of the second change region based on the first average value of the local binary pattern values of the edge pixels in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixels in the building image data at the adjacent next moment includes: calculating the first average value of the local binary pattern values of the edge pixels in the second change region in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixels in the second change region in the building image data at the adjacent next moment; determining the absolute value of the difference between the first average value and the second average value as the texture change severity of the second change region.

[0037] Specifically, in the embodiment of the present invention, when the moment and the moment, the absolute value of the difference between the mean values of the local binary pattern (LBP) values of the edge pixels in the second change region is relatively large, which usually indicates that the texture of the second change region has changed significantly. This change may be caused by construction activities because construction often brings significant texture changes, such as wall grinding, adding or removing building materials, etc. Therefore, in the embodiment of the present invention, the absolute value of the difference between the mean value of the LBP values of all edge pixels in the building image data at the th second change region at the moment and the mean value of the LBP values of all edge pixels in the building image data at the moment is denoted as the texture change severity of the th second change region.

[0038] Further, as an optional embodiment of the present invention, determining the possibility that the first change region corresponding to the second change region in the first difference image belongs to a newly added building region based on regional gray consistency, edge position invariance, and texture change severity includes: calculating the second product between regional gray consistency and edge position invariance, and calculating the second ratio between texture change severity and the second product; performing normalization processing on the second ratio to obtain the possibility.

[0039] Specifically, the embodiment of the present invention specifically uses the following formula to calculate the possibility: In the above formula, represents the possibility that the th first change region in the first difference image at the th moment belongs to a newly added building region. represents the th moment in the first difference image, and the The texture change intensity of the first change region. Indicates the regional gray consistency of the first change region in the first difference image at the th moment. Indicates the edge position invariance of the first change region in the first difference image at the th moment. Indicates a normalization function, which is used to normalize .

[0040] Furthermore, in the embodiment of the present invention, the first threshold value is 0.8. If the probability that the th first change region in the first difference image belongs to the newly added building region is greater than or equal to 0.8, then the th first change region is used as the newly added building region in the first difference image. When there are more newly added building regions, the area is larger, and the internal texture complexity is higher, it indicates that the area of the construction region in the building image data at the th moment is larger, the number of construction regions is more, and the internal details of the construction region are richer. Therefore, higher attention should be given, that is, the building picture expressiveness of the building image data at the th moment is greater.

[0041] Furthermore, as an optional embodiment of the present invention, according to the fourth average value of the construction detail richness of all newly added building regions in the first difference image at the current moment, the area of each newly added building region in the first difference image at the current moment, and the number of newly added building regions in the first difference image at the current moment, determining the building picture expressiveness of the building image data at the current moment includes: adding up the areas of each newly added building region to obtain a superimposed area, and calculating the third product among the superimposed area, the fourth average value, and the number of newly added building regions; normalizing the third product to obtain the building picture expressiveness.

[0042] Specifically, in the embodiment of the present invention, the mean value of the LBP values of all pixel points in the first difference images at all moments of the th newly added building region at the th moment is denoted as the construction detail richness of the th newly added building region. Then, the building picture expressiveness of the building image data at the current moment is calculated using the following formula: In the above formula, Indicates the building picture expressiveness of the building image data at the th moment. Indicates the The mean richness of construction details of all newly added building areas in the first difference image at a moment, i.e., the fourth average value. Denote the quantity of all newly added building areas in the first difference image at a moment. Denote the area of the th newly added building area in the first difference image at a moment. Denote the normalization function, which is used to perform normalization processing on

[0043] Step S103, according to the building image data at each moment in the continuous video data range of the building image data at the current moment, correct the expressiveness of the building picture to obtain the corrected expressiveness of the building picture.

[0044] Specifically, since both the movement of workers and the change of construction tools can lead to an increase in the expressiveness of the building picture, it is necessary to further analyze the change characteristics of building information in the building image data at each moment within the continuous video data range at each moment, correct the expressiveness of the building picture, and obtain the corrected expressiveness of the building picture.

[0045] Furthermore, as an optional embodiment of the present invention, correcting the expressiveness of the building picture according to the building image data at each moment in the continuous video data range of the building image data at the current moment to obtain the corrected expressiveness of the building picture includes: taking the building image data at a plurality of consecutive moments after the current moment as the continuous video data range; calculating the second difference image between the building image data at each moment in the continuous video data range of the building image data at the current moment and the building image data at the current moment; denoting all the newly added building areas in each second difference image as the total newly added building areas in each second difference image, obtaining a sequence of total newly added building areas arranged in chronological order, taking the first total newly added building area in the sequence of total newly added building areas as the target area, and other total newly added building areas as the reference areas; taking the intersection area between the target area and the reference areas as the building progress area; taking the normalized value of the area of the non-overlapping area between adjacent building progress areas as the building information change factor of the previous building progress area; taking the normalized value of the number of edge pixel points of the overlapping area between adjacent building progress areas as the non-building equipment information change factor of the previous building progress area; calculating the fourth product between the building information change factor and the non-building equipment information change factor of each building progress area; and superimposing the fourth products of each building progress area to obtain a superimposed value; normalizing the superimposed value to obtain the building information change value at the current moment; determining the fifth product between the building information change value and the expressiveness of the building picture as the corrected expressiveness of the building picture.

[0046] Specifically, the embodiment of the present invention obtains the second difference image between the building image data at all times within the continuous video data at the th moment and the building image data at the th moment. Similarly, all the newly added building areas in each second difference image are obtained, denoted as the total newly added building areas in each second difference image, and a sequence of total newly added building areas is obtained in chronological order. In the sequence of total newly added building areas, the first total newly added building area is used as the target area, and other total newly added building areas are denoted as reference areas. If the building progress of the building with only newly added building areas within the continuous video data range is slow, the intersection area between the target area and each reference area belongs to the important key pictures showing the building progress, and the intersection areas between the target area and each reference area are all denoted as the building progress areas. For any two adjacent building progress areas, there must be non-overlapping areas and overlapping areas between them. Among them, the overlapping area represents the completed building area, and the non-overlapping area represents the new progress area of the building activity. When there are people entering and leaving in the newly added building area or when a building equipment is abandoned after use, non-overlapping edge features will appear in the overlapping area of the building progress area, indicating that there are non-building progress display behaviors in the building progress area, and the lower the building information change value of the building progress area.

[0047] Further, the embodiment of the present invention obtains the normalized value of the area of the non-overlapping area between the th building progress area and the th building progress area, denoted as the building information change factor of the th building progress area. For the overlapping area between the th building progress area and the th building progress area, the normalized value of the number of edge pixel points of the overlapping area between the th building progress area and the th building progress area is obtained, denoted as the non-building equipment information change factor of the th building progress area. When the building information change factor of the building progress area is larger and the non-building equipment information change factor is larger, it indicates that the building progress area belongs to the important key pictures showing the building progress, and the building information change value of the building progress area is larger. Therefore, the embodiment of the present invention can specifically calculate the building information change value at the current moment by the following formula: In the above formula, represents the building information change value at the th moment. represents the number of all building progress areas at the th moment. Represents the building information change factor of the i-th building progress area. Represents the non-building equipment information change factor of the building progress area. Represents a normalization function, which is used to perform normalization processing.

[0048] Furthermore, the embodiment of the present invention uses the following formula to obtain the corrected building picture expressiveness: In the above formula, Represents the corrected building picture expressiveness of the building image data at the th moment. Represents the building picture expressiveness of the building image data at the th moment. Represents the building information change value of the building image data at the th moment.

[0049] Step S104, according to the picture expression degree of the building image data, the corrected building picture expressiveness of the building image data at the current moment, and the corrected building picture expressiveness of the building image data at all moments in the continuous video data range, determine the transmission priority degree of the building image data at the current moment, and control the building information release system to transmit the building image data based on the transmission priority degree.

[0050] Specifically, if the picture expression degree of the building image data at a single moment is low, and there is building image data with a high picture expression degree in its continuous video data range, it indicates that the performance of the building may be affected due to changes in external light. For example, strong light irradiation, shadow changes, and weather conditions may cause the image quality at this moment to be low, but as time goes by, the light becomes more suitable or the weather improves, and the image quality is improved. Therefore, it cannot be said that its picture importance degree is low at this time. Therefore, it is necessary to jointly analyze the differences in the picture expression degrees within the continuous video data range, comprehensively obtain the picture importance degree of the building image data at each moment, and calculate the transmission priority degree of the building image data at the current moment based on this.

[0051] Further, as an alternative embodiment of the present invention, determining the transmission priority level of the building image data at the current moment according to the degree of picture representation of the building image data, the corrected building picture representation of the building image data at the current moment, and the corrected building picture representations of the building image data at all moments within the continuous video data range includes: taking the maximum value of the absolute value of the difference between the degree of picture representation of the building image data at the current moment and the degrees of picture representation of the building image data at all moments within the continuous video data range as the importance factor of the building image data at the current moment; calculating the sixth product between the importance factor and the corrected building picture representation at the current moment, and performing normalization processing on the sixth product to obtain the importance level of the building picture of the building image data at the current moment; taking the importance level of the building picture of the building image data at the current moment and the average value of the importance levels of the building pictures of the building image data at each moment within the continuous video data range of the building image data at the current moment as the transmission priority level of the building image data at the current moment.

[0052] Specifically, the embodiment of the present invention obtains the maximum value of the absolute value of the difference in the degree of picture representation between the building image data at the th moment and the building image data at all moments within its continuous video data range, and records it as the importance factor of the building image data at the th moment. The greater the corrected building picture representation, the greater the information change in the building progress between the building image data at the current moment and the picture at a certain moment within its continuous video data range. Therefore, its importance level in the data transmission process is higher. Therefore, the embodiment of the present invention uses the following formula to calculate the importance level of the building picture of the building image data at the current moment: In the above formula, represents the importance level of the building picture of the building image data at the th moment. represents the corrected building picture representation of the building image data at the th moment. represents the importance factor of the building image data at the th moment. represents the normalization function, which is used to perform normalization processing on .

[0053] So far, the embodiment of the present invention obtains the importance levels of the building pictures of the building image data at each moment.

[0054] Further, during the transmission of building monitoring video data, in order to ensure the transmission quality of building image data, data can be selectively transmitted, and data carrying more key information is preferentially transmitted to ensure that the preferentially transmitted video image data is core key data. Therefore, according to the importance degree of the building picture of the building image data within the continuous video data range, the transmission priority degree of the building image data at each moment is obtained.

[0055] Specifically, the embodiment of the present invention calculates the transmission priority degree of the building image data at each moment by using the following formula: In the above formula, represents the transmission priority degree of the building image data at the -th moment. represents the number of all moments in the continuous video data range at the -th moment. represents the importance degree of the building picture of the -th building image data within the continuous video data range at the -th moment. It should be noted that the continuous video data range at the -th moment includes the i-th moment.

[0056] Further, as an optional embodiment of the present invention, controlling the building information publishing system to transmit the building image data based on the transmission priority degree includes: regarding the building image data with a transmission priority degree greater than or equal to the second threshold as the preferential transmission object, and regarding the building image data with a transmission priority degree less than the second threshold as the object to be transmitted; using the building information publishing system to losslessly compress the preferential transmission object and then transmit it to the database, and using the building information publishing system to lossily compress the object to be transmitted and then transmit it to the database.

[0057] Specifically, the embodiment of the present invention sets the second threshold to 0.3. When the transmission priority degree of the building image data at the -th moment is greater than or equal to 0.3, it indicates that the building image data generated within the continuous video data range at the -th moment carries more key information and has a higher priority during data transmission. The building image data generated within the continuous video data range at the -th moment is preferentially transmitted, and the building image data at the -th moment is recorded as the preferential transmission object. When the transmission priority degree of the building image data at the -th moment is less than , it indicates that the building image data generated within the continuous video data range at the -th moment carries less key information and has a lower priority during data transmission. The building image data at the The building image data at each moment is recorded as the object to be transmitted. Thus, all the objects to be preferentially transmitted in the building monitoring video data are obtained.

[0058] Furthermore, in the embodiments of the present invention, different types of transmission methods are performed on the building monitoring video data based on the building image data to be preferentially transmitted. During the transmission process of the building monitoring video data, all the building image data to be preferentially transmitted is losslessly compressed first and then directly transmitted to the database. Then, all the building image data to be transmitted is lossily compressed and then transmitted to the database.

[0059] The embodiments of the present invention can determine the transmission priority degree of the building image data at each moment according to the picture performance degree of the building image data at each moment during the transmission process of the building monitoring video data and the performance of the building picture within the continuous video data range at each moment. Thus, the important and key building image data can be preferentially transmitted according to the transmission priority degree, thereby improving the transmission quality of the building monitoring video data of the building information release system and thus improving the building management efficiency.

[0060] Embodiment 2: Corresponding to the transmission data processing method for the building information release system provided in the above embodiment, based on the same technical concept, the embodiments of the present invention also provide a transmission data processing device for the building information release system. The transmission data processing device for the building information release system is used to execute the above transmission data processing method for the building information release system. Figure 2 FIG. is a schematic structural diagram of a transmission data processing device for a building information release system provided by an embodiment of the present invention. As Figure 2 shown. The transmission data processing device for the building information release system may vary greatly due to configuration or performance differences. It may include one or more processors 201 and a memory 202. The memory 202 is used to store computer programs that can run on the processor 201. The processor 201 is used to execute the programs stored in the memory 202 to implement each step in the method embodiments above. Figure 1 Among them, the memory 202 can be short-term storage or persistent storage. The application programs stored in the memory 202 may include one or more modules (not shown in the figure), and each module may include a series of computer-executable instructions for the transmission data processing device for the building information release system.

[0061] Furthermore, the processor 201 can be configured to communicate with the memory 202 and execute a series of computer-executable instructions in the memory 202 on the transmission data processing device for the building information distribution system. The transmission data processing device for the building information distribution system may further include one or more power supplies 203, one or more wired or wireless network interfaces 204, one or more input / output interfaces 205, and one or more keyboards 206.

[0062] Specifically, in this embodiment, the transmission data processing device for the building information distribution system includes a processor, a communication interface, a memory, and a communication bus; among them, the processor, the communication interface, and the memory complete mutual communication through the bus; the memory is used to store computer programs; the processor is used to execute the programs stored on the memory to implement each step in the method embodiments above Figure 1 and has the beneficial effects of the above method embodiments. To avoid repetition, the embodiments of the present invention will not be described in detail here.

[0063] It should be noted that the transmission data processing device for the building information distribution system provided by the embodiments of the present invention and the transmission data processing method for the building information distribution system provided by the embodiments of the present invention are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned transmission data processing method for the building information distribution system and has the same or similar beneficial effects. The repeated parts will not be described again.

[0064] It should be noted that the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be beneficial.

[0065] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0066] The embodiments of the present invention also propose a computer-readable storage medium. The computer-readable medium stores one or more programs. When the one or more programs are executed by an electronic device including multiple application programs, the electronic device is caused to execute Figure 1 the methods disclosed in the illustrated embodiments and implement the functions and beneficial effects of the various methods in the foregoing method embodiments, which will not be described in detail here.

[0067] Among them, the computer-readable storage medium includes read-only memory (ROM for short), random access memory (RAM for short), magnetic disks, optical discs, etc.

Claims

1. A method for processing transmission data used in a building information publishing system, characterized in that, Including: Dividing the building monitoring video data of a building area into building image data at multiple moments, and determining the picture performance degree of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data at each moment; Determining the building picture performance of the newly added building area in the first difference image at the current moment according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood, where the first difference image is the difference between the gray values of the pixel points at the same position in the building image data at adjacent moments; Correcting the building picture performance according to the building image data at each moment in the continuous video data range of the building image data at the current moment to obtain the corrected building picture performance; Determining the transmission priority degree of the building image data at the current moment according to the picture performance degree of the building image data, the corrected building picture performance of the building image data at the current moment, and the corrected building picture performance of the building image data at all moments in the continuous video data range, and controlling the building information publishing system to transmit the building image data based on the transmission priority degree.

2. The transmission data processing method for a building information publishing system according to claim 1, characterized in that, The determining the picture performance degree of the building image data according to the average gradient value, the number of gray levels, and the average gray value in the building image data at each moment includes: Calculating the first product between the average gradient value and the number of gray levels in the building image data at each moment, and calculating the absolute value of the first difference between the average gray value and a predetermined value; Calculating the first sum value between the absolute value of the first difference and a hyperparameter; Determining the first ratio between the first product and the first sum value as the picture performance degree of the building image data.

3. The transmission data processing method for a building information publishing system according to claim 1, characterized in that, The determining the building picture performance of the newly added building area in the first difference image at the current moment according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood includes: Determining the regional gray consistency of the first change area in the first difference image according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood; Using the mapping method to obtain the second change area corresponding to the first change area in the first difference image from the building image data at the current moment and the building image data at the next adjacent moment; Taking the ratio of the number between the intersection sequence and the union sequence of the position coordinates of the edge pixel points of the second change area in the building image data at the current moment and the edge pixel points of the second change area in the building image data at the next adjacent moment as the edge position invariance of the second change area; Determining the texture change severity of the second change area according to the first average value of the local binary pattern values of the edge pixel points of the second change area in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixel points of the second change area in the building image data at the next adjacent moment; Determine the possibility that the first changed region corresponding to the second changed region in the first difference image belongs to a newly added building region according to the regional gray consistency, the edge position invariance, and the drastic texture change; Use the first changed regions with the possibility greater than or equal to the first threshold as the newly added building regions in the first difference image; Use the third average value of the local binary pattern values of all pixel points in the newly added building regions in the first difference image at the current moment as the richness of construction details of the newly added building regions; Determine the building image performance of the building image data at the current moment according to the fourth average value of the richness of construction details of all newly added building regions in the first difference image at the current moment, the areas of the newly added building regions in the first difference image at the current moment, and the number of newly added building regions in the first difference image at the current moment; 4. The transmission data processing method for a building information publishing system according to claim 3, characterized in that The determination of the regional gray consistency of the first changed region in the first difference image according to the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood includes: Perform inverse proportional normalization on the mean value of the absolute values of the differences between the gray value of the pixel points in the first difference image and the gray values of the pixel points in its neighborhood to obtain the gray consistency of the pixel points in the first difference image; Cluster the gray consistencies of all pixel points in the first difference image to obtain multiple clustering clusters. Each clustering cluster is used as a first changed region in the first difference image, and use the mean value of the gray consistencies of all pixel points in each first changed region as the regional gray consistency of each first changed region; 5. The transmission data processing method for a building information publishing system according to claim 3, characterized in that, The determination of the drastic texture change of the second changed region according to the first average value of the local binary pattern values of the edge pixel points of the second changed region in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixel points of the second changed region in the building image data at the next adjacent moment includes: Calculate the first average value of the local binary pattern values of the edge pixel points of the second changed region in the building image data at the current moment and the second average value of the local binary pattern values of the edge pixel points of the second changed region in the building image data at the next adjacent moment; Determine the absolute value of the difference between the first average value and the second average value as the drastic texture change of the second changed region; 6. The transmission data processing method for a building information publishing system according to claim 3, characterized in that The determination of the possibility that the first changed region corresponding to the second changed region in the first difference image belongs to a newly added building region according to the regional gray consistency, the edge position invariance, and the drastic texture change includes: Calculate the second product between the regional gray consistency and the edge position invariance, and calculate the second ratio between the drastic texture change and the second product; Perform normalization processing on the second ratio to obtain the possibility; 7. The transmission data processing method for a building information publishing system according to claim 3, characterized in that, Determining the architectural scene expressiveness of the architectural image data at the current moment based on the fourth average value of the construction detail richness of all newly added architectural areas in the first difference image at the current moment, the areas of the newly added architectural areas in the first difference image at the current moment, and the number of newly added architectural areas in the first difference image at the current moment includes: Superposing the areas of the newly added architectural areas to obtain a superposed area, and calculating a third product among the superposed area, the fourth average value, and the number of newly added architectural areas; Performing normalization processing on the third product to obtain the architectural scene expressiveness.

8. The transmission data processing method for a building information publishing system according to claim 1, characterized in that Correcting the architectural scene expressiveness based on the architectural image data at each moment within the continuous video data range of the architectural image data at the current moment to obtain a corrected architectural scene expressiveness includes: Regarding the architectural image data at multiple consecutive moments after the current moment as the continuous video data range; Calculating a second difference image between the architectural image data at each moment within the continuous video data range of the architectural image data at the current moment and the architectural image data at the current moment; Denoting all the newly added architectural areas in each of the second difference images as the total newly added architectural areas in each second difference image, obtaining a sequence of total newly added architectural areas arranged in chronological order, taking the first total newly added architectural area in the sequence of total newly added architectural areas as the target area, and the other total newly added architectural areas as reference areas; Regarding the intersection area between the target area and the reference areas as the construction progress area; Regarding the normalized value of the area of the non-overlapping area between adjacent construction progress areas as the construction information change factor of the previous construction progress area; Regarding the normalized value of the number of edge pixels of the overlapping area between adjacent construction progress areas as the non-construction equipment information change factor of the previous construction progress area; Calculating a fourth product between the construction information change factor and the non-construction equipment information change factor of each construction progress area; And superposing the fourth products of the construction progress areas to obtain a superposed value; Normalizing the superposed value to obtain the construction information change value at the current moment; Determining the fifth product between the construction information change value and the architectural scene expressiveness as the corrected architectural scene expressiveness.

9. The transmission data processing method for a building information publishing system according to claim 1, characterized in that, Determining the transmission priority level of the architectural image data at the current moment based on the scene expressiveness degree of the architectural image data, the corrected architectural scene expressiveness of the architectural image data at the current moment, and the corrected architectural scene expressiveness of the architectural image data at all moments within the continuous video data range includes: Denoting the maximum value of the absolute value of the difference between the scene expressiveness degree of the architectural image data at the current moment and the scene expressiveness degrees of the architectural image data at all moments within the continuous video data range as the importance factor of the architectural image data at the current moment; Calculate the sixth product between the importance factor and the corrected building picture expressiveness at the current moment, and normalize the sixth product to obtain the importance of the building picture of the building image data at the current moment; Take the importance of the building picture of the building image data at the current moment and the average value of the importance of the building picture of the building image data at each moment in the continuous video data range of the building image data at the current moment as the transmission priority of the building image data at the current moment.

10. The transmission data processing method for a building information publishing system according to any one of claims 1-9, characterized in that, The controlling the building information publishing system to transmit the building image data based on the transmission priority includes: Regarding the building image data with the transmission priority greater than or equal to the second threshold as the priority transmission object, and regarding the building image data with the transmission priority less than the second threshold as the object to be transmitted; Using the building information publishing system to transmit the priority transmission object to the database after lossless compression, and using the building information publishing system to transmit the object to be transmitted to the database after lossy compression.

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