A transmission data processing method for a building information publishing system

Abstract

The present invention relates to the field of data processing technology, and more particularly to a transmission data processing method for a building information publishing system. The method comprises: dividing building surveillance video data of a building area into building image data at multiple time points, determining the image expressiveness of the building image data; determining the architectural image expressiveness of a newly added building area in a first difference image at the current time point; correcting the architectural image expressiveness based on architectural image data at each time point within a continuous video data range of the architectural image data at the current time point to obtain a corrected architectural image expressiveness; determining the transmission priority of the architectural image data at the current time point, and controlling the building information publishing system to transmit the architectural image data based on the transmission priority. In this way, the present invention improves the transmission quality of building surveillance video data of the building information publishing system.

Description

Technical Field

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

[0002] With the advancement of building informatization, building surveillance systems are playing an increasingly important role in ensuring building safety, real-time monitoring of the building environment, and providing building information data support. Building surveillance video data is an indispensable component of building management, especially in application scenarios such as building safety monitoring, construction site monitoring, and emergency response, where surveillance video data provides critical visual information.

[0003] In some scenarios, building information publishing systems often transmit building surveillance video data in the order it is generated. This can lead to prioritizing data unrelated to core information like building safety and occupant activity, such as ambient noise or irrelevant background information. This can prevent key information, including building changes, from being transmitted in a timely manner. Without prioritizing video data based on its importance, some critical building information can be delayed. This results in low transmission quality of building surveillance video data from the building information publishing system, impacting building management efficiency. Summary of the Invention

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

[0005] In order to solve the above technical problems, the technical solutions adopted are as follows:

[0006] An embodiment of the present invention provides a transmission data processing method for a building information publishing system, comprising: dividing building monitoring video data of a building area into building image data at multiple moments, and determining the picture expression degree of the building image data based on the average gradient value, the number of gray levels, and the gray value mean in the building image data at each moment; determining the building picture expression of a newly added building area in a first difference image at a current moment based on the gray value of a pixel point in a first difference image and the gray value between pixels in its neighborhood, the first difference image being the difference between the gray value of pixels at the same position in building image data at adjacent moments; correcting the building picture expression based on building image data at each moment in a continuous video data range of the building image data at the current moment to obtain a corrected building picture expression; determining the transmission priority of the building image data at the current moment based on the picture expression degree of the building image data, the corrected building picture expression of the building image data at the current moment, and the corrected building picture expression 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.

[0007] Optionally, determining the degree of picture expression of the architectural image data based on the average gradient value, the number of gray levels and the mean gray value in the architectural image data at each moment includes: calculating a first product between the average gradient value and the number of gray levels in the architectural image data at each moment, and calculating the absolute value of a first difference between the mean gray value and a predetermined value; calculating a first sum between the absolute value of the first difference and a hyperparameter; and determining a first ratio between the first product and the first sum as the degree of picture expression of the architectural image data.

[0008] Optionally, determining the architectural image expressiveness of the newly added architectural area in the first difference image at the current moment based on the grayscale value of the pixel point in the first difference image and the grayscale value of the pixel points in its neighborhood includes: determining the regional grayscale consistency of the first change area in the first difference image based on the grayscale value of the pixel point in the first difference image and the grayscale value 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 architectural image data at the current moment and the architectural image data at the next adjacent moment by using a mapping method; taking the ratio of the number of intersection sequence and union sequence of the position coordinates of the edge pixel points of the second change area in the architectural image data at the current moment and the edge pixel points of the second change area in the architectural image data at the next adjacent moment as the edge position invariance of the second change area; taking the first average value of the local binary pattern values ​​of the edge pixel points of the second change area in the architectural image data at the current moment as the edge position invariance of the second change area and the second average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data of the next adjacent moment, determine the intensity of the texture change of the second change area; determine 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 grayscale consistency, edge position invariance and texture change intensity; take 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; take the third average value of the local binary pattern values ​​of all pixels 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; determine the architectural picture expressiveness of the architectural 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.

[0009] Optionally, determining the regional grayscale consistency of the first change area in the first difference image based on the grayscale value of the pixel point in the first difference image and the grayscale value between the pixel points in its neighborhood includes: inversely normalizing the mean of the absolute value of the difference between the grayscale value of the pixel point in the first difference image and the grayscale value between the pixel points in its neighborhood to obtain the grayscale consistency of the pixel points in the first difference image; clustering the grayscale consistency of all pixel points in the first difference image to obtain multiple clusters, each cluster serving as a first change area in the first difference image, and taking the mean of the grayscale consistency of all pixel points in each first change area as the regional grayscale consistency of each first change area.

[0010] Optionally, determining the severity of the texture change in the second changing region based on a first average value of local binary pattern values ​​of edge pixels of the second changing region in architectural image data at a current moment and a second average value of local binary pattern values ​​of edge pixels of the second changing region in architectural image data at a next adjacent moment includes:

[0011] Calculate a first average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data at the current moment, and a second average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data at the next adjacent moment; and determine 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 area.

[0012] Optionally, based on the regional grayscale consistency, edge position invariance and texture change severity, 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 includes: calculating a second product between the regional grayscale consistency and the edge position invariance, and calculating a second ratio between the texture change severity and the second product; and normalizing the second ratio to obtain the possibility.

[0013] Optionally, determining the architectural picture expressiveness of the architectural image data at the current moment based on 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 includes: superimposing the areas of each newly added building area to obtain the superimposed area, and calculating the third product of the superimposed area, the fourth average value, and the number of newly added building areas; and normalizing the third product to obtain the architectural picture expressiveness.

[0014] Optionally, the architectural picture expressiveness is corrected according to the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment, and the corrected architectural picture expressiveness includes: taking the architectural image data at multiple consecutive moments after the current moment as the continuous video data range; calculating the second difference image between the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment and the architectural image data at the current moment; recording all the newly added architectural areas in each second difference image as the total newly added architectural areas in each second difference image, and 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 area; taking the intersection area between the target area and the reference area as the construction progress area; taking 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; taking the normalized value of the number of edge pixels in the overlapping area between adjacent construction progress areas as the non-construction equipment information change factor of the previous construction progress area; calculating the fourth product between the construction information change factor and the non-construction equipment information change factor of each construction progress area; and superimposing the fourth products of each construction progress area to obtain a superimposed value; normalizing the superimposed value to obtain the construction information change value at the current moment; and determining the fifth product between the construction information change value and the construction picture expressiveness as the modified construction picture expressiveness.

[0015] Optionally, determining the transmission priority of the architectural image data at the current moment based on the picture expression degree of the architectural image data, the corrected architectural picture expressiveness of the architectural image data at the current moment, and the corrected architectural picture expressiveness of the architectural image data at all moments in the continuous video data range includes: recording the maximum absolute value of the difference between the picture expression degree of the architectural image data at the current moment and the picture expression degree of the architectural image data at all moments in the continuous video data range as the importance factor of the architectural image data at the current moment; calculating the sixth product between the importance factor and the corrected architectural picture expressiveness at the current moment, and normalizing the sixth product to obtain the architectural picture importance of the architectural image data at the current moment; and taking the architectural picture importance of the architectural image data at the current moment and the average value of the architectural picture importance of the architectural image data at the current moment and the architectural picture importance of the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment as the transmission priority of the architectural image data at the current moment.

[0016] Optionally, controlling the building information publishing system to transmit building image data based on transmission priority includes: taking building image data with a transmission priority greater than or equal to a second threshold as a priority transmission object, and taking building image data with a transmission priority less than the second threshold as an object to be transmitted; using the building information publishing system to losslessly compress the priority transmission object and transmit it to the database, and using the building information publishing system to losslessly compress the object to be transmitted and transmit it to the database.

[0017] The present invention has the following beneficial effects: first, the building monitoring video data of the building area is divided into building image data at multiple moments, and the picture expression degree of the building image data is determined according to the average gradient value, the number of gray levels and the gray value mean in the building image data at each moment; secondly, the building picture expression of the newly added building area in the first difference image at the current moment is determined according to the gray value of the pixel point in the first difference image and the gray value between the pixels in its neighborhood, and the first difference image is the difference between the gray value of the pixel points at the same position in the building image data at adjacent moments; then, the building picture expression is corrected 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 expression; finally, the transmission priority of the building image data at the current moment is determined according to the picture expression degree of the building image data, the corrected building picture expression of the building image data at the current moment and the corrected building picture expression of the building image data at all moments in the continuous video data range, and the building information publishing system is controlled to transmit the building image data based on the transmission priority.

[0018] Thus, embodiments of the present invention can determine the transmission priority of building image data at each moment during the transmission of building surveillance video data based on the degree of image quality of the building image data at each moment and the expressiveness of the building image within the continuous video data range at each moment. Consequently, important and critical building image data can be transmitted first according to the transmission priority, thereby improving the transmission quality of building surveillance video data in the building information release system and enhancing building management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flow chart of a transmission data processing method for a building information publishing system provided by one embodiment of the present invention;

[0021] Figure 2 A schematic structural diagram of a transmission data processing device for a building information publishing system provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0022] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of a data transmission processing method for a building information publishing system proposed in accordance with the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0023] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0024] The following describes in detail a specific scheme of a transmission data processing method for a building information publishing system provided by the present invention in conjunction with the accompanying drawings.

[0025] Example 1:

[0026] See also Figure 1 , which shows a flow chart of a transmission data processing method for a building information publishing system provided by one embodiment of the present invention, including:

[0027] Step S101: Divide the building monitoring video data of the building area into building image data at multiple moments, and determine the picture expression degree of the building image data according to the average gradient value, number of gray levels and gray value mean in the building image data at each moment.

[0028] Specifically, this embodiment of the present invention selects a high-definition camera that covers the entire building area and monitors at a fixed angle to obtain building surveillance video data. The camera's installation angle and height must ensure a clear view of the entire building area, avoiding obstructions and blind spots, and avoiding strong direct sunlight, especially during daytime, which can affect image clarity. Therefore, this embodiment of the present invention selects a camera with automatic lighting control capabilities. The building surveillance video data is divided into several moments of building image data, with each hour being considered a moment.

[0029] Furthermore, in order to give priority to transmitting more important information, it is necessary to determine the importance of the building image data at each moment in the process of building monitoring video data transmission. When judging the importance of the building image data at each moment in the data transmission process, the importance of the data in the transmission process can be determined by analyzing the picture performance of the building image data at a single moment and the picture performance of continuous building video images. For the picture of the building image data at a single moment, it is necessary to pay attention to the key information displayed by the building image data, but the picture importance of the building image data at the current moment cannot be determined solely based on the picture of the building image data at a single moment. For the picture of continuous building video images, the performance difference between continuous building video pictures also has a certain influencing factor on the picture importance of the building image data at the current moment in the data transmission process. Therefore, it is necessary to further analyze the picture performance difference between continuous building video images to obtain the picture importance of the building image data at each moment.

[0030] Furthermore, in the embodiment of the present invention, the first The time range of the last 11 moments after the moment is the first The continuous video data range at a certain moment.

[0031] Furthermore, when the number of grayscale levels in the architectural image data increases and the average gradient value increases, the architectural image data has a higher level of detail and more complex content. When the average grayscale value in the architectural image data is too small or too large, the architectural image data will appear very dark or very bright, indicating that the image in the architectural image data is relatively monotonous. It can be assumed that the current image is at night or during the day when workers are resting and no construction work is being carried out. Therefore, the content displayed is not obvious and important, and the image importance during the transmission process is relatively low. Therefore, the embodiment of the present invention uses the grayscale level, gradient, and grayscale value in the architectural image data to calculate the image quality of the architectural image data at each moment. Among them, as an optional embodiment of the present invention, determining the picture expression degree of the architectural image data according to the average gradient value, the number of gray levels and the mean gray value in the architectural image data at each moment includes: calculating the first product between the average gradient value and the number of gray levels in the architectural image data at each moment, and calculating the absolute value of the first difference between the mean gray value and a predetermined value; calculating the first sum between the absolute value of the first difference and a hyperparameter; and determining the first ratio between the first product and the first sum as the picture expression degree of the architectural image data.

[0032] Specifically, the predetermined value may be 128. In the embodiment of the present invention, the following formula is used to calculate the image representation degree of the building image data:

[0033]

[0034] In the above formula, Indicates the The degree of image representation of architectural image data at a specific moment. Indicates the The average gradient value in the building image data at a certain moment. Indicates the The number of gray levels in the building image data at a moment. Indicates the The mean grayscale value in the building image data at a certain moment. Represents a preset hyperparameter, which is preset in the embodiment of the present invention , used to prevent the denominator from being 0.

[0035] Step S102 : determining the architectural image expressiveness of the newly added building area in the first difference image at the current moment according to the grayscale value of the pixel in the first difference image and the grayscale value between the pixels in its neighborhood.

[0036] The first difference image is the difference between the grayscale values ​​of pixels at the same position in the building image data at adjacent moments.

[0037] Specifically, when a change occurs between the architectural image data at a single moment and the architectural image data at a single moment within the continuous video data range, it indicates that the architectural surveillance video records workers performing construction work and achieving significant results during the current time period. Compared to stable video image frames, rapidly changing video image frames clearly show more critical information, so they are more important during data transmission. Therefore, it is necessary to compare the architectural image data at the current moment with the architectural image data at a single moment within the continuous video data range. If the performance difference between the architectural image data is large, it means that there is a large change between the architectural image data at the current moment and the architectural image data at a certain moment within the continuous video data range, and its importance during data transmission is higher. Therefore, it is necessary to obtain the architectural image importance of the architectural image data at each moment and use this to determine the architectural image expressiveness of the architectural image data.

[0038] Furthermore, as an optional embodiment of the present invention, determining the architectural image expressiveness of the newly added architectural area in the first difference image at the current moment based on the grayscale value of the pixel point in the first difference image and the grayscale value of the pixel points in its neighborhood includes: determining the regional grayscale consistency of the first change area in the first difference image based on the grayscale value of the pixel point in the first difference image and the grayscale value 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 architectural image data at the current moment and the architectural image data at the next adjacent moment by using a mapping method; taking the ratio of the number of intersection sequence and union sequence of the position coordinates of the edge pixel points of the second change area in the architectural image data at the current moment and the edge pixel points of the second change area in the architectural image data at the next adjacent moment as the edge position invariance of the second change area; and calculating the edge position invariance of the second change area based on the local binary pattern value of the edge pixel points of the second change area in the architectural image data at the current moment. The first average value and the second average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data of the next adjacent moment are used to determine the intensity of the texture change of the second change area; based on the regional grayscale consistency, edge position invariance and texture change intensity, 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 is determined; the first change area with a possibility greater than or equal to the first threshold is used as the newly added building area in the first difference image; the third average value of the local binary pattern values ​​of all pixels in the newly added building area in the first difference image at the current moment is used as the richness of construction details of the newly added building area; based on 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, the architectural picture expressiveness of the architectural image data at the current moment is determined.

[0039] Specifically, the embodiment of the present invention is Moment and The grayscale values ​​of the pixels at the same position in the building image data at the moment are subtracted ( Time minus the At the moment of the first difference image, the first difference image is obtained. pixels, the The grayscale value of a pixel represents its grayscale change at two different moments. The smaller the grayscale difference between a pixel and its eight neighboring pixels, the smaller the grayscale difference between the pixel and its eight neighboring pixels. The greater the grayscale change consistency of the pixels. As an optional embodiment of the present invention, determining the regional grayscale consistency of the first change area in the first difference image based on the grayscale value of the pixel in the first difference image and the grayscale value of the pixel in its neighborhood includes: inversely normalizing the mean of the absolute value of the difference between the grayscale value of the pixel in the first difference image and the grayscale value of the pixel in its neighborhood to obtain the grayscale consistency of the pixel in the first difference image; clustering the grayscale consistency of all pixels in the first difference image to obtain multiple clusters, each cluster being a first change area in the first difference image, and taking the mean of the grayscale consistency of all pixels in each first change area as the regional grayscale consistency of each first change area.

[0040] Specifically, the embodiment of the present invention is The gray value of each pixel and the mean of the absolute value of the gray value difference between the pixels in its eight neighborhoods are inversely normalized as the first difference image. The grayscale consistency of pixels. In the first difference image, the K-means clustering algorithm is used to cluster the grayscale consistency of all pixels in the first difference image to obtain several clusters, and the area to which each cluster belongs is used as a change area in the first difference image, that is, the first change area. The embodiment of the present invention uses the mean of the grayscale consistency of all pixels in each first change area as the regional grayscale consistency of each first change area. Among them, the K value in the K-means clustering algorithm can be obtained by the elbow method in the well-known technology, and the embodiment of the present invention will not be repeated here.

[0041] Furthermore, in the embodiment of the present invention, for the first difference image The first change region is obtained by mapping. Moment and The first architectural image data at the moment A change area, namely the second change area.

[0042] Furthermore, in an embodiment of the present invention, in building surveillance video data, construction unchanged areas generally refer to those backgrounds and static parts of buildings (such as walls, windows, floor slabs, etc.) in building surveillance video data, which may be affected by the environment and produce large grayscale changes at different times, but the grayscale values ​​of these areas are relatively stable. And because the structures of these areas (such as building walls, door and window frames, etc.) are often static in surveillance videos, their texture and edge features will not change significantly over time. The grayscale changes in construction change areas at different times are large, because these areas will undergo different degrees of changes during the construction process. For example, changes to walls and windows will cause significant changes in the texture and grayscale of these areas. Therefore, if the first The edge texture of the changed area in the first difference image remains unchanged, and the greater the consistency of the grayscale change, the greater the The changed area belongs to the construction unchanged area. The edge texture of the changed area in the first difference image of the two moments has undergone a drastic change, and the smaller the consistency of the grayscale change, the greater the change in the first difference image. The changed area may belong to the newly added area of ​​the building. Therefore, in the embodiment of the present invention, during the construction process, the newly added structure of the building will usually cause a large change in the edge information of the area. This change is usually manifested as a large number of new edge pixels appearing in the building image data, causing the size of the union to be much larger than the size of the intersection. Therefore, in the embodiment of the present invention, if the ratio of the intersection to the union is smaller, it means that the edge information of the changed area has changed significantly, which is due to the change caused by the construction activity. Then use the Canny edge detection algorithm to obtain the first The second change region is in Moment and The edge pixel points in the building image data at the moment The second change region is in Moment and The ratio of the number of intersection sequences and union sequences of the position coordinates of all edge pixels in the building image data at the moment is taken as the first The edge position invariance of the second variation region.

[0043] Furthermore, as an optional embodiment of the present invention, determining the severity of texture change in the second change area based on the first average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data at the current moment and the second average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data at the next adjacent moment includes: calculating the first average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data at the current moment and the second average value of the local binary pattern values ​​of the edge pixels of the second change area in the architectural image data at the next adjacent moment; and 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 area.

[0044] Specifically, in the embodiment of the present invention, when Moment and When the absolute value of the difference between the mean values ​​of the local binary pattern (LBP) values ​​of the edge pixels of the second change area at time t is large, it usually indicates that the texture of the second change area has undergone a significant change. This change may be caused by construction activities, because construction often brings significant texture changes, such as wall polishing, adding or removing building materials, etc. Therefore, the embodiment of the present invention sets the The second change region is in The mean LBP value of all edge pixels in the building image data at the moment is The absolute value of the difference between the mean LBP values ​​of all edge pixels in the building image data at time t is recorded as The second change area has a drastic change in texture.

[0045] Furthermore, as an optional embodiment of the present invention, determining the possibility that the first change area corresponding to the second change area in the first difference image belongs to a newly added building area based on the regional grayscale consistency, edge position invariance and texture change severity includes: calculating the second product between the regional grayscale consistency and the edge position invariance, and calculating the second ratio between the texture change severity and the second product; normalizing the second ratio to obtain the possibility.

[0046] Specifically, the embodiment of the present invention uses the following formula to calculate the probability:

[0047]

[0048] In the above formula, Indicates the The first difference image at the moment The first area of ​​change is the possibility of adding a new building area. Indicates the The first difference image at the moment The intensity of texture change in the first change area. Indicates the The first difference image at the moment The regional grayscale consistency of the first change area. Indicates the The first difference image at the moment The edge position invariance of the first change region. Represents the normalization function, which is used to Perform normalization processing.

[0049] Furthermore, in the embodiment of the present invention, the first threshold value is 0.8. If the probability that the first changed area belongs to the newly added building area is greater than or equal to 0.8, then the The first changed area is regarded as the newly added building area in the first difference image. When the number of newly added building areas is larger, the area is larger, and the internal texture complexity is higher, it means that the first In the building image data at a certain moment, the larger the construction area, the more construction areas there are, and the richer the internal details of the construction areas, the more attention should be paid to them. The architectural image data at that moment has greater architectural picture expressiveness.

[0050] Furthermore, as an optional embodiment of the present invention, determining the architectural picture expressiveness of the architectural image data at the current moment based on 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 includes: superimposing the area of ​​each newly added building area to obtain the superimposed area, and calculating the third product of the superimposed area, the fourth average value, and the number of newly added building areas; and normalizing the third product to obtain the architectural picture expressiveness.

[0051] Specifically, the embodiment of the present invention is The newly added building area is in The mean LBP value of all pixels in the first difference image at all times is recorded as The richness of construction details of the newly added area of ​​a building. Then, the following formula is used to calculate the architectural image expressiveness of the current moment's architectural image data:

[0052]

[0053] In the above formula, Indicates the The architectural image expressiveness of architectural image data at a specific moment. Indicates the The fourth average value is the average of the richness of construction details of all newly added areas of the building in the first difference image at the time instant. Indicates the The number of newly added areas of all buildings in the first difference image at the moment. Indicates the The first difference image at the moment The area of ​​the newly added building area. Represents the normalization function, which is used to Perform normalization processing.

[0054] Step S103 , correcting the architectural picture expressiveness according to the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment to obtain a corrected architectural picture expressiveness.

[0055] Specifically, the movement of workers and the change of construction tools can lead to an increase in the expressiveness of the building picture. Therefore, it is necessary to further analyze the changing characteristics of the building information in the building image data at each moment within the range of continuous video data at each moment, correct the expressiveness of the building picture, and obtain the corrected architectural picture expressiveness.

[0056] Furthermore, as an optional embodiment of the present invention, the architectural picture expressiveness is corrected according to the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment, and the corrected architectural picture expressiveness includes: taking the architectural image data at multiple consecutive moments after the current moment as the continuous video data range; calculating the second difference image between the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment and the architectural image data at the current moment; recording all the newly added architectural areas in each second difference image as the total newly added architectural areas in each second difference image, and obtaining a sequence of the total newly added architectural areas arranged in chronological order; taking the first total newly added architectural area in the sequence of the total newly added architectural areas as the target area, and the other total newly added architectural areas as the target area. A newly added area is used as a reference area; the intersection area between the target area and the reference area is used as the construction progress area; the normalized value of the area of ​​the non-overlapping area between adjacent construction progress areas is used as the construction information change factor of the previous construction progress area; the normalized value of the number of edge pixels in the overlapping area between adjacent construction progress areas is used as the non-construction equipment information change factor of the previous construction progress area; the fourth product between the construction information change factor and the non-construction equipment information change factor of each construction progress area is calculated; and the fourth products of each construction progress area are superimposed to obtain a superimposed value; the superimposed value is normalized to obtain the construction information change value at the current moment; and the fifth product between the construction information change value and the construction picture expressiveness is determined to be the modified construction picture expressiveness.

[0057] Specifically, the embodiment of the present invention obtains the The building image data at all moments within the continuous video data range of the moment is A second difference image is generated between the building image data at each moment. Similarly, all newly added building areas in each second difference image are obtained and recorded as the total newly added building areas in each second difference image. A sequence of total newly added building areas is then generated in chronological order. In the sequence of total newly added building areas, the first newly added building area is designated as the target area, and the remaining newly added building areas are designated as reference areas. If only newly added building areas exist within the continuous video data, indicating slow construction progress, the intersection of the target area and each reference area is considered a key image for displaying construction progress. The intersection of the target area and each reference area is then recorded as a construction progress area. For any two adjacent construction progress areas, there must be both non-overlapping and overlapping areas between them. Overlapping areas represent completed construction areas, while non-overlapping areas represent new construction progress areas. When personnel enter or exit a newly added construction area, or construction equipment is abandoned after use, non-overlapping edge features appear in the overlapping areas of the construction progress areas, indicating that the construction progress area is not displaying construction progress. The lower the building information change value of the construction progress area, the lower the building information change value of the construction progress area.

[0058] Furthermore, the embodiment of the present invention obtains the The construction progress area and The normalized value of the area of ​​the non-overlapping area between the construction progress areas is recorded as Building information change factor for each construction progress area. The construction progress area and The overlapping area between the construction progress areas is obtained in the The construction progress area and The normalized value of the number of edge pixels in the overlapping area between the construction progress areas is recorded as The non-construction equipment information change factor of each construction progress area. The larger the construction information change factor of the construction progress area, the larger the non-construction equipment information change factor, indicating that the construction progress area is an important key screen for displaying construction progress, and the larger the construction information change value of the construction progress area. Therefore, in this embodiment of the present invention, the following formula can be used to calculate the current building information change value:

[0059]

[0060] In the above formula, Indicates the The building information change value at the moment. Indicates the The number of all construction progress areas at the moment. Represents the building information change factor of the i-th building progress area. Indicates the Non-construction equipment information change factors for each construction progress area. Represents the normalization function, which is used to Perform normalization processing.

[0061] Furthermore, the embodiment of the present invention adopts the following formula to obtain the corrected architectural image expressiveness:

[0062]

[0063] In the above formula, Indicates the Modification of architectural image data at the moment of time to express architectural images. Indicates the The architectural image expressiveness of architectural image data at a specific moment. Indicates the The building information change value of the building image data at the moment.

[0064] Step S104: Determine the transmission priority of the architectural image data at the current moment based on the image expression level of the architectural image data, the revised architectural image expression of the architectural image data at the current moment, and the revised architectural image expression of the architectural image data at all moments in the continuous video data range, and control the architectural information publishing system to transmit the architectural image data based on the transmission priority.

[0065] Specifically, if the image quality of building image data at a single moment is low, while there is building image data with higher image quality within the continuous video data, this indicates that changes in external lighting may have affected the building's quality. For example, strong sunlight, changing shadows, or weather conditions may cause the image quality to be low at that moment. However, as time passes, the lighting becomes more favorable or the weather improves, and the image quality improves, this does not indicate low image importance. Therefore, it is necessary to jointly analyze the differences in image quality within the continuous video data range to comprehensively determine the image importance of the building image data at each moment, and use this to calculate the transmission priority of the building image data at the current moment.

[0066] Furthermore, as an optional embodiment of the present invention, determining the transmission priority of the architectural image data at the current moment based on the picture expression degree of the architectural image data, the corrected architectural picture expressiveness of the architectural image data at the current moment, and the corrected architectural picture expressiveness of the architectural image data at all moments in the continuous video data range includes: recording the maximum absolute value of the difference between the picture expression degree of the architectural image data at the current moment and the picture expression degree of the architectural image data at all moments in the continuous video data range as the importance factor of the architectural image data at the current moment; calculating the sixth product between the importance factor and the corrected architectural picture expressiveness at the current moment, and normalizing the sixth product to obtain the architectural picture importance of the architectural image data at the current moment; and taking the architectural picture importance of the architectural image data at the current moment and the average value of the architectural picture importance of the architectural image data at the current moment and the architectural picture importance of the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment as the transmission priority of the architectural image data at the current moment.

[0067] Specifically, the embodiment of the present invention obtains the The maximum absolute value of the difference in the degree of picture expression between the architectural image data at the moment and the architectural image data at all moments in the continuous video data range is recorded as The importance factor of the building image data at each moment. The greater the corrected building picture expressiveness, the greater the information change of the building progress between the building image data at the current moment and the picture at a certain moment within the continuous video data range, and therefore the higher its importance in the data transmission process. Therefore, the embodiment of the present invention uses the following formula to calculate the building picture importance of the building image data at the current moment:

[0068]

[0069] In the above formula, Indicates the The importance of the building picture of the building image data at a certain moment. Indicates the Corrected architectural image expressiveness of architectural image data at a specific moment. Indicates the The importance factor of the building image data at a certain moment. Represents the normalization function, which is used to Perform normalization processing.

[0070] So far, the embodiment of the present invention obtains the importance of the building picture of the building image data at each moment.

[0071] Furthermore, during the transmission of building surveillance video data, to ensure the transmission quality of building image data, data can be selectively transmitted, with priority given to data carrying more critical information, to ensure that the prioritized video image data is core and critical. Therefore, the transmission priority of building image data at each moment is determined based on the importance of the building image data within the continuous video data range.

[0072] Specifically, the embodiment of the present invention uses the following formula to calculate the transmission priority of the building image data at each moment:

[0073]

[0074] In the above formula, Indicates the The transmission priority of building image data at a certain moment. Indicates the The number of all moments in the continuous video data range of moment. Indicates the The first The importance of the architectural image data of the building. The continuous video data range of moments includes the i-th moment.

[0075] Furthermore, as an optional embodiment of the present invention, controlling the building information publishing system to transmit building image data based on transmission priority includes: taking building image data with a transmission priority greater than or equal to a second threshold as a priority transmission object, and taking building image data with a transmission priority less than the second threshold as an object to be transmitted; using the building information publishing system to losslessly compress the priority transmission object and then transmit it to the database, and using the building information publishing system to losslessly compress the object to be transmitted and then transmit it to the database.

[0076] Specifically, the embodiment of the present invention sets the second threshold value to 0.3. When the transmission priority of the building image data at the 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 moment carries more key information and has a higher priority in the data transmission process. The building image data generated within the continuous video data range of the moment The building image data at the moment is recorded as the priority transmission object. The transmission priority of building image data at the moment is less than When The building image data generated within the continuous video data range at the moment carries less key information and has a lower priority in the data transmission process. The building image data at each moment is recorded as the object to be transmitted. Thus, all priority transmission objects in the building monitoring video data are obtained.

[0077] Furthermore, an embodiment of the present invention performs different types of transmission methods on building monitoring video data based on the building image data that is transmitted first. During the transmission of building monitoring video data, all building image data that are transmitted first are first losslessly compressed and then directly transmitted to the database. Then, all building image data to be transmitted are lossily compressed and then transmitted to the database.

[0078] The present invention can prioritize the transmission of building image data at each moment during the transmission of building surveillance video data based on the visual quality of the building image data at each moment and the visual quality of the building image within the continuous video data at each moment. This allows for the transmission of important and critical building image data based on the transmission priority, thereby improving the transmission quality of building surveillance video data within the building information publishing system and enhancing building management efficiency.

[0079] Example 2:

[0080] Corresponding to the transmission data processing method for the building information publishing system provided in the above embodiment, based on the same technical concept, an embodiment of the present invention further provides a transmission data processing device for the building information publishing system. The transmission data processing device for the building information publishing system is used to execute the transmission data processing method for the building information publishing system. Figure 2 A structural diagram of a transmission data processing device for a building information publishing system provided by an embodiment of the present invention is shown as follows: Figure 2 The transmission data processing device used in the building information publishing system may have relatively large differences due to different configurations or performances, and may include one or more processors 201 and memory 202. The memory 202 is used to store computer programs that can be run on the processor 201. The processor 201 is used to execute the program stored in the memory 202 to achieve the above Figure 1 The various steps in the method embodiment are described above. Memory 202 may be either transient or persistent storage. The application stored in memory 202 may include one or more modules (not shown), each of which may include a series of computer-executable instructions for a transmission data processing device used in a building information publishing system.

[0081] Furthermore, the processor 201 can be configured to communicate with the memory 202, and execute a series of computer-executable instructions stored in the memory 202 on the transmission data processing device for the building information publishing system. The transmission data processing device for the building information publishing system can also 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.

[0082] Specifically in this embodiment, the transmission data processing device used in the building information publishing system includes a processor, a communication interface, a memory and a communication bus; wherein the processor, the communication interface and the memory communicate with each other through the bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to achieve the above Figure 1 The various steps in the method embodiment have the beneficial effects of the above method embodiments. To avoid repetition, the embodiments of the present invention will not be described again here.

[0083] It should be noted that the transmission data processing device for the building information publishing system provided in the embodiment of the present invention and the transmission data processing method for the building information publishing system provided in the embodiment 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 transmission data processing method for the aforementioned building information publishing system, and has the same or similar beneficial effects, and the repeated parts will not be repeated.

[0084] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0086] The embodiment of the present invention further provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by an electronic device including multiple application programs, the electronic device executes Figure 1 The methods disclosed in the illustrated embodiments implement the functions and beneficial effects of the various methods in the preceding method embodiments, which will not be described in detail here.

[0087] Among them, the computer readable storage medium includes read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

Claims

1. A transmission data processing method for a building information publishing system, characterized in that: include: Dividing the building surveillance video data of the building area into building image data at a plurality of moments, and determining the image representation degree of the building image data based on the average gradient value, the number of gray levels, and the gray value mean in the building image data at each moment; Determining the architectural image expressiveness of the newly added building area in the first difference image at the current moment based on the grayscale value of a pixel point in the first difference image and the grayscale value of pixels in its neighborhood, wherein the first difference image is the difference between the grayscale values ​​of pixels at the same position in the architectural image data at adjacent moments; Correcting the architectural image expressiveness according to architectural image data at each moment in a continuous video data range of the architectural image data at the current moment to obtain a corrected architectural image expressiveness; Based on the picture expression degree of the architectural image data, the revised architectural picture expressiveness of the architectural image data at the current moment and the revised architectural picture expressiveness of the architectural image data at all moments in the continuous video data range, the transmission priority of the architectural image data at the current moment is determined, and the architectural information publishing system is controlled to transmit the architectural image data based on the transmission priority.

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

3. The transmission data processing method for a building information publishing system according to claim 1, characterized in that: The determining, based on the grayscale value of a pixel point in the first difference image and the grayscale value of pixels in its neighborhood, of the architectural image expressiveness of the newly added architectural area in the first difference image at the current moment comprises: determining regional grayscale consistency of a first changed region in the first difference image based on the grayscale value of a pixel point in the first difference image and the grayscale values ​​of pixels in its neighborhood; Obtaining a second change region corresponding to the first change region in the first difference image from the building image data at the current moment and the building image data at the next adjacent moment using a mapping method; The ratio of the number of the intersection sequence and the number of the union sequence of the position coordinates of the edge pixel points of the second changing area in the architectural image data at the current moment and the edge pixel points of the second changing area in the architectural image data at the next adjacent moment is used as the edge position invariance of the second changing area; determining a severity of texture change in the second changing region based on a first average value of local binary pattern values ​​of edge pixels of the second changing region in the architectural image data at the current moment and a second average value of local binary pattern values ​​of edge pixels of the second changing region in the architectural image data at a next adjacent moment; Determining, based on the grayscale consistency of the region, the edge position invariance, and the intensity of the texture change, the possibility that a first changed region corresponding to the second changed region in the first difference image belongs to a newly added building region; taking the first changed area with the probability greater than or equal to the first threshold as the newly added building area in the first difference image; taking a third average value of the local binary pattern values ​​of all pixels 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; The architectural picture expressiveness of the architectural image data at the current moment is determined based on the fourth average value of the construction detail richness of all newly added building areas in the first difference image at the current moment, the area of ​​each of the newly added building areas 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.

4. The transmission data processing method for a building information publishing system according to claim 3, characterized in that: The determining, based on the grayscale value of a pixel point in the first difference image and the grayscale values ​​of pixels in its neighborhood, of the regional grayscale consistency of the first changed region in the first difference image includes: Normalizing the grayscale values ​​of pixels in the first difference image by an inversely proportional average of the absolute values ​​of the differences between the grayscale values ​​of pixels in its neighborhood to obtain grayscale consistency of the pixels in the first difference image; Clustering is performed on the grayscale consistency of all pixels in the first difference image to obtain multiple clusters, each of the clusters is used as a first change area in the first difference image, and the mean of the grayscale consistency of all pixels in each first change area is used as the regional grayscale consistency of each first change area.

5. The transmission data processing method for a building information publishing system according to claim 3, characterized in that: The determining, based on a first average value of local binary pattern values ​​of edge pixels of the second change region in the architectural image data at the current moment and a second average value of local binary pattern values ​​of edge pixels of the second change region in the architectural image data at the next adjacent moment, comprises: Calculating a first average of local binary pattern values ​​of edge pixels of a second change region in the architectural image data at the current moment, and a second average of local binary pattern values ​​of edge pixels of a second change region in the architectural image data at a next adjacent moment; The absolute value of the difference between the first average value and the second average value is determined as the texture change severity of the second change region.

6. The transmission data processing method for a building information publishing system according to claim 3, characterized in that: Determining, based on the regional grayscale consistency, the edge position invariance, and the texture change severity, 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 includes: Calculating a second product between the regional grayscale consistency and the edge position invariance, and calculating a second ratio between the texture change severity and the second product; The second ratio is normalized 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 image expressiveness of the architectural image data at the current moment based on a fourth average value of the richness of construction details of all newly added building areas in the first difference image at the current moment, an 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 includes: superimposing the areas of the newly added building areas to obtain a superimposed area, and calculating a third product of the superimposed area, the fourth average value, and the number of the newly added building areas; The third product is normalized to obtain the architectural image expressiveness.

8. The transmission data processing method for a building information publishing system according to claim 1, characterized in that: The step of correcting the architectural image expressiveness based on architectural image data at each moment in the continuous video data range of the architectural image data at the current moment to obtain the corrected architectural image expressiveness comprises: Taking the building image data of a plurality of consecutive moments after the current moment as the continuous video data range; Calculating a 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; Recording all 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 as the target area, and the remaining total newly added building areas as reference areas; using the intersection area between the target area and the reference area as the construction progress area; The normalized value of the area of ​​the non-overlapping area between adjacent construction progress areas is used as the construction information change factor of the previous construction progress area; The normalized value of the number of edge pixels in the overlapping area between adjacent construction progress areas is used 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 of the construction progress areas; and superimposing the fourth products of the construction progress areas to obtain a superimposed value; Normalizing the superposition value to obtain the building information change value at the current moment; A fifth product of the building information change value and the building picture expressiveness is determined as the modified building picture expressiveness.

9. The transmission data processing method for a building information publishing system according to claim 1, characterized in that: The determining of the transmission priority of the architectural image data at the current moment according to the picture expression degree of the architectural image data, the corrected architectural picture expression of the architectural image data at the current moment, and the corrected architectural picture expression of the architectural image data at all moments in the continuous video data range includes: The maximum absolute value of the difference between the image expression level of the building image data at the current moment and the image expression levels of the building image data at all moments in the continuous video data range is recorded as the importance factor of the building image data at the current moment; Calculating a sixth product between the importance factor and the corrected architectural picture expressiveness at the current moment, and normalizing the sixth product to obtain the architectural picture importance of the architectural image data at the current moment; The architectural picture importance of the architectural image data at the current moment and the average of the architectural picture importance of the architectural image data at each moment in the continuous video data range of the architectural image data at the current moment are used as the transmission priority of the architectural 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 to 9, characterized in that: The controlling the building information publishing system to transmit the building image data based on the transmission priority comprises: The architectural image data whose transmission priority is greater than or equal to a second threshold is selected as a priority transmission object, and the architectural image data whose transmission priority is less than the second threshold is selected as an object to be transmitted; The building information publishing system is used to perform lossless compression on the priority transmission object and then transmit it to the database. The building information publishing system is also used to perform lossy compression on the object to be transmitted and then transmit it to the database.

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