CN109145379B - Intelligent drawing system and management method for building layer height map - Google Patents
Intelligent drawing system and management method for building layer height map Download PDFInfo
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Abstract
The invention belongs to the technical field of computer CAD drawing, and discloses an intelligent drawing system and a management method for a building layer height map, wherein an unmanned aerial vehicle is used for carrying a monocular camera to input building data information; accurately identifying the recorded building layer height data, and extracting a building area; carrying out data design according to the entered building layer height data; constructing a corresponding building layer height model according to the designed data; carrying out a mapping drawing design on the manufactured building layer height model; storing the designed building layer height model data; and displaying the drawn building layer height model effect diagram. According to the invention, the man-machine conversation mode is utilized by the data input module, so that the complexity and cost of the system are reduced; the invention can provide the precision of the picture through smoothing and gradient calculation, and improve the definition of the picture; the combination of noise classification can balance the brightness characteristics of the illumination non-uniform image.
Description
Technical Field
The invention belongs to the technical field of computer CAD (computer aided design) building drawing, and particularly relates to an intelligent drawing system and a management method for a building layer height map.
Background
Currently, the current state of the art commonly used in the industry is as follows:
building is a generic term for buildings and structures. Is drawn by people by using the mastered technical means of substances and a certain scientific rule in order to meet the social life needs.
The existing mobile application generally displays a building model based on H5 (namely HTML5 and hypertext markup language 5), firstly, a server analyzes a building model file to obtain geometric data, then the geometric data is transmitted to a Web page through a network, the Web front end analyzes the geometric data by using JavaScript (an transliterated script language) to obtain the building geometric model, and then the building model is rendered and displayed by using WebGL (full-written Web Graphics Library, which is a 3D drawing standard).
Because WebGL shows performance relatively poor on mobile terminal, picture blocking is not smooth during man-machine interaction, especially for large-scale building model easily causes browser collapse, even can't show, therefore, current three-dimensional building model is difficult to satisfy in mobile terminal's bandwagon effect, and user experience is relatively poor.
In summary, the problems of the prior art are:
the related data identification accuracy of the existing building layer drawing process on the building is poor;
meanwhile, the graphic data of the building cannot be accurately simulated, the simulation speed is low, the stability is poor, the building is easily influenced by external factors, and the robustness is poor; affecting the rendering effect.
In the prior art, the virtual building model can perform advanced analysis and analysis, such as energy analysis, heat analysis, pipeline conflict detection, safety analysis and the like of a green building, and generally detects the safety performance and environmental protection performance of the corresponding building model from the whole, has certain limitation, and can influence the drawing accuracy of the building model.
When the image is polluted by noise, the traditional enhancement algorithm is easy to fail, the image effect is poor, and the definition is not high.
The existing intelligent drawing of the building layer height map lacks feedback on the safety condition and can not treat different safety types differently.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides an intelligent drawing system for a building layer height map.
The invention is realized in such a way that a building layer high-level diagram intelligent drawing system management method comprises the following steps:
building data information is input by using a monocular camera carried by an unmanned aerial vehicle; transforming the acquired image into a gray image by using Y= -0.299R+0.587G+0.114B; wherein Y: pixel value, R: red component, G: green component, B: a blue component; carrying out image smoothing treatment on the gray level image, and then carrying out gradient calculation; calculating a degree difference of luminance values between a specific pixel and an adjacent pixel; dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve; for the layer with the lowest brightness and the layer with the highest brightness, histogram equalization processing is carried out first, and then noise points are removed; for other layers, firstly removing noise points, then carrying out histogram equalization treatment, and combining a plurality of treated layers into an enhanced image;
accurately identifying the recorded building layer height data, and extracting a building area; in the process of accurately identifying building layer height data, determining and acquiring offset probability of a corresponding building area, and constructing a transition state process;
acquiring last two evaluation state strategies successfully and strategy failures through computer analysis;
building a corresponding Markov state diagram, building a building area image and extracting.
X 0 In an initial state, X 1 ，X 2 ，X 3 ……X i Is represented by X 0 The state which can be transferred after passing the security analysis rule;
P 01 ，P 02 ，P 03 ……P 0i is represented by X 0 To X 1 ，X 2 ，X 3 ……X i Probability of X i+1 ，X i+2 The two states obtained after the computer analysis are respectively represented as a success strategy and a failure strategy;
r 1,i+1 ，r 1,i+2 is X 1 To X i+1 ，X i+2 Probability of r 2,i+1 ，r 2,i+2 Is X 2 To X i+1 ，X i+2 Probability … … r of (2) i,i+1 ，r i,i+2 Is X i To X i+1 ，X i+2 From which the efficiency, safety, analysis state transition matrix of the building area calculation strategy is derived:
in the matrix, p is the probability of transition from the state, r is the probability of absorption, and the relationship between p and r is as follows:
basic matrix F:
F＝(I-Q) -1
the absorption matrix B is as follows:
B＝FR＝(I-Q) -1 ×R；
carrying out data design according to the entered building layer height data;
constructing a corresponding building layer height model according to the designed data;
further, the building layer height map intelligent drawing system management method further comprises the following steps:
carrying out a mapping drawing design on the manufactured building layer height model;
storing the designed building layer height model data;
and displaying the drawn building layer height model effect diagram.
Further, the specific calculation method in the gradient calculation comprises the following steps: when the luminance value of the coordinates (a, b) of a specific pixel of the smoothed clipping image is expressed as f (a, b), gradient vectors of all pixels are calculated using the expression shown below.
Gradient vectorA physical quantity representing a degree difference in luminance value between a specific pixel and an adjacent pixel; based on]The value sum +.x of the x component of the gradient vector shown in>The value of the y component of the gradient vector shown in (c) by +.>The expression shown in (a) calculates the direction θ of the gradient vector;
calculating gradient calculation in standard image processing by discretization of image data, and calculating gradient between adjacent pixels using differentiation in an expression shown in the following formula;
dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve, and the method specifically comprises the following steps: assuming that the luminance value i=i (x, y) of each pixel of the image I, the image I is divided into an I0 layer, an I1 layer, an I2 layer and an I3 layer by a set of thresholds I1, I2, I3;
for the I0 layer, the luminance value I of each pixel satisfies: i is more than or equal to 0 and less than i1;
for the I1 layer, the luminance value I of each pixel satisfies: i1 is less than or equal to i2;
for the I2 layer, the luminance value I of each pixel satisfies: i2 is less than or equal to i < i3;
for the I3 layer, the luminance value I of each pixel satisfies: i3 is equal to or more than i and equal to or less than 255.
I=i0+i1+i2+i3 corresponds to 4 layers of film stack, and the boundary of each layer of image is formed by a closed curve;
combining the plurality of processed image layers into an enhanced image, which specifically comprises the following steps: merging the I0 layer, the I1 layer, the I2 layer and the I3 layer into an enhanced image according to the formula I=I0×j0+I1×j1+I2×j2+I3×j3, wherein j0, j1, j2 and j3 are nonlinear coefficients or linear coefficients; where j=a×s+b, s=crγ, a, b are coefficients and are different when j is j0, j1, j2, j3, s is an exponential calibration function, and c, r and γ are all positive constants. In particular, in s=crγ, when c takes 1, γ takes different values Γ, a cluster of transformation curves is obtained, and when c=1, transformation curves of different γ values are obtained;
when gamma is less than 1, mapping the narrow-band input dark value to the wide-band output value by power conversion, and mapping the wide-band input bright value to the narrow-band output value;
when gamma is more than 1, mapping the broadband input dark value to the narrowband output value by power conversion, and mapping the narrowband input bright value to the broadband output value;
when γ=1, it is proportional linear transformation;
for pictures with uneven lighting at night, the dark part has a great deal of detail needed, and the bright part is easy to overexposure; adopting four layers to make the gamma value of the dark part layer smaller than 1; enhancing the visual data analysis capability of the dark place; for the bright portion layer, a calibration value γ value greater than 1 is used, so that the contrast inside the bright portion is enhanced.
Further, the determining obtains the offset probability of the corresponding building area, and the constructing the transition state includes a building area quantization rule and a building area evaluation rule.
Further, the building area quantization rule includes:
quantification of safety evaluation indexes:
the selected index quantization parameter is defined as S, wherein each factor is defined as (S0, S1, S2, … …), and a corresponding weight value (n 0, n1, n2, … …) is assigned to each factor, and then the total security value of the algorithm is:
S＝s0*n0+s1*n1+s2*n2……；
quantification of efficiency evaluation index:
the selected quantization parameter is defined as E, where each factor is defined as (E0, E1, E2, … …), and each factor is given a corresponding weight value (m 0, m1, m2, … …), then the overall efficiency value of the algorithm is:
E＝e0*m0+e1*m1+e2*m2……；
the strategies of each rule are ordered, the S/E value is used as a scalar, the explanation safety and efficiency close to 1 are the best, the explanation safety higher than 1 is low in efficiency, the explanation safety lower than 1 is high in efficiency, the corresponding probability is divided according to the distance from 1, the probability is smaller when the distance from 1 is larger, and the probability is larger when the distance from 1 is smaller;
the building area evaluation rule includes:
the specific formula is as follows:
P1＝w1*50％+w2*50％
P2＝1-P1
p1 represents good building area security, P2 represents poor building area security, w1 represents computer analysis, and w2 represents computer analysis.
Another object of the present invention is to provide a computer program for implementing the building level elevation map intelligent drawing system management method.
Another object of the present invention is to provide an information data processing terminal for implementing the building level elevation map intelligent drawing system management method.
It is another object of the present invention to provide a computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the building level elevation map intelligent drawing system management method.
Another object of the present invention is to provide a building layer high-level diagram intelligent drawing system for implementing the building layer high-level diagram intelligent drawing system management method, the building layer high-level diagram intelligent drawing system comprising:
the data input module is connected with the data identification module and used for inputting building data information;
the data identification module is connected with the data module and the central processing module and used for accurately identifying the input building data and extracting a building area;
the central processing module is connected with the data input module, the data identification module, the design module, the modeling module, the drawing design module, the data storage module and the display module and used for controlling the normal work of each module;
the design module is connected with the central processing module and is used for drawing and designing according to the input building data;
the modeling module is connected with the central processing module and is used for constructing a corresponding model according to the designed data;
the drawing design module is connected with the central processing module and is used for carrying out A3 (A4) drawing output design on the manufactured model;
the data storage module is connected with the central processing module and used for storing the processed building model data;
and the display module is connected with the central processing module and used for displaying the drawn building layer height map model effect map through a display.
The invention further aims to provide a building drawing platform with the building layer height drawing intelligent drawing system.
In summary, the invention has the advantages and positive effects that:
the invention uses the unmanned aerial vehicle to carry the monocular camera to input the building data information; transforming the acquired image into a gray image by using Y= -0.299R+0.587G+0.114B; wherein Y: pixel value, R: red component, G: green component, B: a blue component; carrying out image smoothing treatment on the gray level image, and then carrying out gradient calculation; calculating a degree difference of luminance values between a specific pixel and an adjacent pixel; dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve; for the layer with the lowest brightness and the layer with the highest brightness, histogram equalization processing is carried out first, and then noise points are removed; for other layers, firstly removing noise points, then carrying out histogram equalization treatment, and combining a plurality of treated layers into an enhanced image;
the invention can provide the precision of the picture through smoothing and gradient calculation, and improve the definition of the picture; the characteristics of high execution efficiency and good enhancement effect on low-contrast images are utilized, the characteristics of uneven illumination brightness can be balanced by combining noise classification, pixels of the images are divided into a plurality of image layers according to brightness values, noise classification removal is implemented in each layer with unchanged connectivity, different algorithms are adopted to respectively process each part of the original image, the results are subjected to geometric superposition to obtain a final image, the global brightness difference of the image is reduced, the image contrast is enhanced, dark part details of the image are enhanced, the bright part details of the image are basically reserved, noise is effectively restrained, and the visibility is improved.
The invention extracts the security algorithms in the aspects of authentication, authorization, access, transmission, storage and the like from the state library according to the actual state, so as to obtain the optimal security, and make the resource allocation most reasonable, namely ensure that the used security policy is safe and efficient, and sequentially carries out two-step evaluation of efficiency and security evaluation, system and user evaluation on the adopted security policy by using a Markov process to construct an evaluation model, and the result of the two-step evaluation is taken as basic data so as to be convenient for the user to use when selecting the security policy, thereby saving resources to the greatest extent, improving the security authentication of the high-rise map of the building, and providing proper, reasonable and more humanized selection. The system of the invention realizes the intelligent requirement.
Drawings
Fig. 1 is a block diagram of a building floor height map intelligent drawing system provided by an embodiment of the invention.
In the figure: 1. a data entry module; 2. a data identification module; 3. a central processing module; 4. designing a module; 5. a modeling module; 6. a drawing design module; 7. a data storage module; 8. and a display module.
Fig. 2 is a flowchart of a building level elevation map intelligent drawing system management method provided by an embodiment of the invention.
FIG. 3 is a Markov state diagram provided by an embodiment of the present invention;
fig. 4 is a diagram of a general user security policy selection experiment provided by an embodiment of the present invention.
Detailed Description
For a further understanding of the invention, its features and advantages, reference is now made to the following examples, which are illustrated in the accompanying drawings.
As shown in fig. 1, the building layer height map intelligent drawing system provided by the embodiment of the invention includes:
the data input module 1 is connected with the data identification module 2 and is used for inputting building data information;
the data identification module 2 is connected with the data module and the central processing module and is used for accurately identifying the input building data and extracting a building area;
the central processing module 3 is connected with the data input module, the data identification module, the design module, the modeling module, the drawing design module, the data storage module and the display module and used for controlling the normal work of each module;
the design module 4 is connected with the central processing module and is used for drawing and designing according to the input building data;
the modeling module 5 is connected with the central processing module and is used for constructing a corresponding model according to the designed data;
the drawing design module 6 is connected with the central processing module and is used for carrying out A3 (A4) drawing output design on the manufactured model;
the data storage module 7 is connected with the central processing module and used for storing the processed building model data;
and the display module 8 is connected with the central processing module and used for displaying the drawn building layer height map model effect map through a display.
When the method is drawn, the data input module 1 is used for inputting building data information by using the monocular camera carried by the unmanned aerial vehicle; accurately identifying the input building data through the data identification module 2, and extracting a building area; the central processing module 3 schedules the design module 4 to perform data design according to the input building data; constructing a corresponding model according to the designed data through a modeling module 5; carrying out charting drawing design on the manufactured model through a drawing design module 6; the data storage module 7 is used for storing the building model data after the drawing design; finally, the drawn building model effect diagram is displayed through the display module 8.
The invention is further described in connection with specific analysis.
As shown in fig. 2, the method for managing the building layer high-level graph intelligent drawing system provided by the embodiment of the invention includes:
s101, building data information is input by using an unmanned aerial vehicle-mounted monocular camera;
s102, accurately identifying the recorded building layer height data and extracting a building area;
s103, carrying out data design according to the entered building layer height data;
s104, constructing a corresponding building layer height model according to the designed data;
s105, carrying out a mapping drawing design on the manufactured building layer height model;
s106, storing the designed building layer height model data;
and S107, displaying a drawn building layer height model effect diagram.
Wherein, the liquid crystal display device comprises a liquid crystal display device,
transforming the acquired image into a gray image by using Y= -0.299R+0.587G+0.114B; wherein Y: pixel value, R: red component, G: green component, B: a blue component; carrying out image smoothing treatment on the gray level image, and then carrying out gradient calculation; calculating a degree difference of luminance values between a specific pixel and an adjacent pixel; dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve; for the layer with the lowest brightness and the layer with the highest brightness, histogram equalization processing is carried out first, and then noise points are removed;
for other layers, firstly removing noise points, then carrying out histogram equalization treatment, and combining a plurality of treated layers into an enhanced image;
accurately identifying the recorded building layer height data, and extracting a building area; in the process of accurately identifying building layer height data, determining and acquiring offset probability of a corresponding building area, and constructing a transition state process;
acquiring last two evaluation state strategies successfully and strategy failures through computer analysis;
as in fig. 3, a corresponding markov state diagram is constructed, and a building area image is constructed and extracted.
X 0 In an initial state, X 1 ，X 2 ，X 3 ……X i Is represented by X 0 The state which can be transferred after passing the security analysis rule;
P 01 ，P 02 ，P 03 ……P 0i is represented by X 0 To X 1 ，X 2 ，X 3 ……X i Probability of X i+1 ，X i+2 The two states obtained after the computer analysis are respectively represented as a success strategy and a failure strategy;
r 1,i+1 ，r 1,i+2 is X 1 To X i+1 ，X i+2 Probability of r 2,i+1 ，r 2,i+2 Is X 2 To X i+1 ，X i+2 Probability … … r of (2) i,i+1 ，r i,i+2 Is X i To X i+1 ，X i+2 From which the efficiency, safety, analysis state transition matrix of the building area calculation strategy is derived:
in the matrix, p is the probability of transition from the state, r is the probability of absorption, and the relationship between p and r is as follows:
basic matrix F:
F＝(I-Q) -1
the absorption matrix B is as follows:
B＝FR＝(I-Q) -1 ×R；
the specific calculation method in gradient calculation comprises the following steps: when the luminance value of the coordinates (a, b) of a specific pixel of the smoothed clipping image is expressed as f (a, b), gradient vectors of all pixels are calculated using the expression shown below.
The gradient vector represents a physical quantity of a degree difference in luminance value between a specific pixel and an adjacent pixel; based on]The value sum +.x of the x component of the gradient vector shown in>The value of the y component of the gradient vector shown in (c) by +.>The expression shown in (a) calculates the direction θ of the gradient vector;
calculating gradient calculation in standard image processing by discretization of image data, and calculating gradient between adjacent pixels using differentiation in an expression shown in the following formula;
dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve, and the method specifically comprises the following steps: assuming that the luminance value i=i (x, y) of each pixel of the image I, the image I is divided into an I0 layer, an I1 layer, an I2 layer and an I3 layer by a set of thresholds I1, I2, I3;
for the I0 layer, the luminance value I of each pixel satisfies: i is more than or equal to 0 and less than i1;
for the I1 layer, the luminance value I of each pixel satisfies: i1 is less than or equal to i2;
for the I2 layer, the luminance value I of each pixel satisfies: i2 is less than or equal to i < i3;
for the I3 layer, the luminance value I of each pixel satisfies: i3 is equal to or more than i and equal to or less than 255.
I=i0+i1+i2+i3 corresponds to 4 layers of film stack, and the boundary of each layer of image is formed by a closed curve;
combining the plurality of processed image layers into an enhanced image, which specifically comprises the following steps: merging the I0 layer, the I1 layer, the I2 layer and the I3 layer into an enhanced image according to the formula I=I0×j0+I1×j1+I2×j2+I3×j3, wherein j0, j1, j2 and j3 are nonlinear coefficients or linear coefficients; where j=a×s+b, s=crγ, a, b are coefficients and are different when j is j0, j1, j2, j3, s is an exponential calibration function, and c, r and γ are all positive constants. In particular, in s=crγ, when c takes 1, γ takes different values Γ, a cluster of transformation curves is obtained, and when c=1, transformation curves of different γ values are obtained;
when gamma is less than 1, mapping the narrow-band input dark value to the wide-band output value by power conversion, and mapping the wide-band input bright value to the narrow-band output value;
when gamma is more than 1, mapping the broadband input dark value to the narrowband output value by power conversion, and mapping the narrowband input bright value to the broadband output value;
when γ=1, it is proportional linear transformation;
for pictures with uneven lighting at night, the dark part has a great deal of detail needed, and the bright part is easy to overexposure; adopting four layers to make the gamma value of the dark part layer smaller than 1; enhancing the visual data analysis capability of the dark place; for the bright portion layer, a calibration value γ value greater than 1 is used, so that the contrast inside the bright portion is enhanced.
The determining obtains the offset probability of the corresponding building area, and the construction transition state comprises a building area quantification rule and a building area evaluation rule.
The building area quantization rule includes:
quantification of safety evaluation indexes:
the selected index quantization parameter is defined as S, wherein each factor is defined as (S0, S1, S2, … …), and a corresponding weight value (n 0, n1, n2, … …) is assigned to each factor, and then the total security value of the algorithm is:
S＝s0*n0+s1*n1+s2*n2……；
quantification of efficiency evaluation index:
the selected quantization parameter is defined as E, where each factor is defined as (E0, E1, E2, … …), and each factor is given a corresponding weight value (m 0, m1, m2, … …), then the overall efficiency value of the algorithm is:
E＝e0*m0+e1*m1+e2*m2……；
the strategies of each rule are ordered, the S/E value is used as a scalar, the explanation safety and efficiency close to 1 are the best, the explanation safety higher than 1 is low in efficiency, the explanation safety lower than 1 is high in efficiency, the corresponding probability is divided according to the distance from 1, the probability is smaller when the distance from 1 is larger, and the probability is larger when the distance from 1 is smaller;
the building area evaluation rule includes:
the specific formula is as follows:
P1＝w1*50％+w2*50％
P2＝1-P1
p1 represents good building area security, P2 represents poor building area security, w1 represents computer analysis, and w2 represents computer analysis.
The effect of the application of the present invention will be further described with reference to simulation.
1. Simulation environment and platform extension construction:
in the embodiment of the invention, a simulation tool Cloudsim is adopted for simulation experiments, an operating system is Windows2003, cloudsim version is Cloudsim-3.0, and JDK version is jdk1.8.0_25.
(1) Simulation environment
The simulation environment is configured, and the simulation environment is as follows: the system comprises 10 servers, wherein six building area computing system management platforms serving as strategy management are respectively an account number safety library, a user state library, an authentication and authorization library, an encryption algorithm library, a storage scheme safety library and a safety strategy management library, and the other two servers are storage servers; the number of the simulation users is 200, wherein 100 users are administrators, and the other 100 users are ordinary users;
(2) Simulation platform extension
The Cloudsim platform needs to be extended to have these functions. According to the structure of Cloudsim, adding strategy source programs such as Account.Java, state.Java, authentication.Java, encryption.Java, storageschema.Java and the like under the org.cloudbus.cloudsim package correspondingly, modifying the corresponding classes of the programs, and compiling to finally generate a new Cloudsim platform.
2. Experimental simulation test and result analysis
(1) Purpose of experiment
The experiment is mainly used for verifying the safety strategy calculated by the building area and evaluating the feasibility and the overall performance of the model. The experiment is to construct four state safety libraries according to common users and manager users, establish all strategies corresponding to the users through the four state libraries, quantize efficiency and safety values of the strategies and determine probability of the strategies, add system evaluation and user evaluation to obtain evaluation probability of each strategy, construct a state transition probability matrix based on a Markov process, obtain the strategy with high efficiency, safety and highest evaluation from the matrix, select 100M data uploaded by the common users and manager users as basic behaviors of the experiment, compare time required by the behaviors with consumed resources to perform performance tests to obtain corresponding data, and analyze the data in detail to explain the practicability of the safety strategy and evaluation model.
(2) Experimental protocol
The experimental scheme of the invention is as follows:
step1, constructing four state security libraries of common users and manager users, as shown in the following table 1 and table 2:
table 1: safety table for general user state
Table 2: administrator user state security table
The security policy base of 2 user types calculated from the building areas respectively in tables 1 and 2 is the general user PB (PB 0 ，PB 1 ，PB 2 … …) and administrator PB (PB) 0 ，PB 1 ，PB 2 … …) of the four state libraries of tables 1 and 2, from which several types of test used in the test were selected in a safe and efficient sequence for test convenience, the general user PB table and the manager PB table were constructed as shown in table 3, table 4 below:
table 3: general user PB table
/>
Table 4: administrator user PB table
| PB 0 | CS 0 ,AA 0 ,EA 0 ,SS 0 |
| PB 1 | CS 0 ,AA 1 ,EA 1 ,SS 0 |
| PB 2 | CS 1 ,AA 1 ,EA 1 ,SS 1 |
| PB 3 | CS 2 ,AA 2 ,EA 2 ,SS 1 |
| PB 4 | CS 2 ,AA 1 ,EA 2 ,SS 1 |
| PB 5 | CS 3 ,AA 2 ,EA 2 ,SS 2 |
| PB 6 | CS 3 ,AA 3 ,EA 3 ,SS 2 |
Step 2: the PB probability of the user and the PB probability of the administrator are calculated respectively by using the quantization rules of safety and efficiency, and the calculated probability is the quantized transition probability of the safety and efficiency of each PB policy, and is the secondary X 0 Steering X 1 ，X 2 ，X 3 ……X i Is a probability of (2).
Step 3, using the safety and efficiency evaluation rules to calculate the evaluation probability of the common user and manager to the system as the slave X 1 ，X 2 ，X 3 ……X i Transfer to X i+1 ，X i+2 Is a probability of (2).
Step 4, constructing a transition matrix based on a Markov process through probabilities of Step 2 and Step 3, obtaining a value with the maximum success probability from the transition matrix, regarding the obtained maximum value as the PB with the best safety and efficiency, evaluating the PB with the best safety, efficiency and evaluation, and sequencing all PB according to the safety, efficiency and evaluation conditions, and recording the PB in a database.
Step 5, configuring algorithms in various libraries of the strategies of the table 2 and the table 3 as tasks to CCDCSMP.java programs in Cloudsim simulation application, wherein each access needs to go through four algorithms in PB library as four tasks.
Step 6, uploading 100M by using 100 times of ordinary users and 100 times of manager users respectively as basic behaviors of the experiment, using the result of Step 4 as a selection condition of the users, and using the time, the number of users and the consumed time of the whole process as experimental parameters to obtain data graphs of the experiment respectively as shown in figures 2 and 3.
Step 7: the data graphs of the cloud computing resource utilization (comprehensive resources such as CPU, memory, bandwidth and the like) as Y-axis and the obtained experiments are shown in the following FIG. 4.
3. Experimental results and analysis
Analysis of the above experiments, in FIG. 4, the security policies selected by the average user are PB 0 ，PB 1 ，PB 2 ，PB 3 ，PB 4 ，PB 5 ，PB 6 Seven total, PB in the experiment 6 Is not selected by the common user, and the reason for analyzing the PB is that 6 The strategy is not worth selecting the cost of the common user due to the fact that the algorithms of authentication authorization, transmission, encryption storage and the like of the state library are complex and time-consuming; PB with few security policy algorithms and minimal time consumption 0 The number of the choices is small, so that the common users generally have data security requirements; PB (PB) 2 With PB 3 The number of people selected by the strategy is more than 20 and 37 respectively, the time consumption of the two strategies is less, and the safety algorithm is also suitable.
The administrator user selectable algorithms are seven in total, but PB 0 And PB 6 Neither algorithm administrator has the choice, because one is the security policy is too low, one is the security policy is higher, and the most selected is PB 3 And PB 4 Policy, but overall, the security level required by the manager user is higher than that required by the ordinary user, and the number of people using more complex algorithm is also relatively highMany.
Through experimental verification of the utilization rate of cloud computing resources and the number selection relation of users of an ordinary user and an administrator, a security policy with a plurality of selected people can be obtained from a graph, wherein the security policy is generally PB (public service) with higher utilization rate as the ordinary user 3 And administrator user's PB 3 0.78 and 0.85 respectively, and a common user PB with fewer security policies is used 0 And administrator user PB 1 Although the resource utilization rate is higher, the PB of the general user is not higher than that of the PB of the general user 3 And administrator user's PB 3 Is a resource utilization of (a).
The security policy algorithm calculated by using the building area can be obtained from the above experiment, so that the corresponding user can select the policy algorithm with reliability, security, high efficiency and good resource utilization rate, and the practicality of the policy is reflected, thereby saving resources, improving the security, and highlighting the characteristics of user evaluation and the like.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When used in whole or in part, is implemented in the form of a computer program product comprising one or more computer instructions. When loaded or executed on a computer, produces a flow or function in accordance with embodiments of the present invention, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the invention in any way, but any simple modification, equivalent variation and modification of the above embodiments according to the technical principles of the present invention are within the scope of the technical solutions of the present invention.
Claims (9)
1. The intelligent drawing system management method for the building layer height map is characterized by comprising the following steps of:
building data information is input by using a monocular camera carried by an unmanned aerial vehicle; converting the acquired image into a gray level image by utilizing Y= +0.299R+0.587G+0.114B; wherein Y: pixel value, R: red component, G: green component, B: a blue component; carrying out image smoothing treatment on the gray level image, and then carrying out gradient calculation; calculating a degree difference of luminance values between a specific pixel and an adjacent pixel; dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve; for the layer with the lowest brightness and the layer with the highest brightness, histogram equalization processing is carried out first, and then noise points are removed; for other layers, firstly removing noise points, then carrying out histogram equalization treatment, and combining a plurality of treated layers into an enhanced image;
accurately identifying the recorded building layer height data, and extracting a building area; in the process of accurately identifying building layer height data, determining and acquiring offset probability of a corresponding building area, and constructing a transition state process;
acquiring last two evaluation state strategies successfully and strategy failures through computer analysis;
constructing a corresponding Markov state diagram, constructing a building area image and extracting;
X 0 in an initial state, X 1 ，X 2 ，X 3 ……X i Is composed ofX 0 The state which can be transferred after passing the security analysis rule;
p 01 ，p 02 ，p 03 ……p 0i is represented by X 0 To X 1 ，X 2 ，X 3 ……X i Probability of X i+1 ，X i+2 The two states obtained after the computer analysis are respectively represented as a success strategy and a failure strategy;
r 1,i+1 ，r 1,i+2 is X 1 To X i+1 ，X i+2 Probability of r 2,i+1 ，r 2,i+2 Is X 2 To X i+1 ，X i+2 Probability … … r of (2) i,i+1 ，r i,i+2 Is X i To X i+1 ，X i+2 From which the efficiency, safety, analysis state transition matrix of the building area calculation strategy is derived:
in the matrix, p is the probability of transition from the state, r is the probability of absorption, and the relationship between p and r is as follows:
basic matrix F:
F＝(I-Q) -1
the absorption matrix B is as follows:
B＝FR＝(I-Q) -1 ×R；
carrying out data design according to the entered building layer height data;
and constructing a corresponding building layer height model according to the designed data.
2. The building level high map intelligent drawing system management method according to claim 1, wherein the building level high map intelligent drawing system management method further comprises:
carrying out a mapping drawing design on the manufactured building layer height model;
storing the designed building layer height model data;
and displaying the drawn building layer height model effect diagram.
3. The building level elevation map intelligent drawing system management method according to claim 1, wherein the specific calculation method in gradient calculation is as follows: when the brightness value of the coordinates (a, b) of a specific pixel of the smoothed cut image is expressed as f (a, b), gradient vectors of all pixels are calculated using the expression shown below;
the gradient vector represents a physical quantity of a degree difference in luminance value between a specific pixel and an adjacent pixel; based onThe value sum +.x of the x component of the gradient vector shown in>The value of the y component of the gradient vector shown in (c) by +.>The expression shown in (a) calculates the direction θ of the gradient vector;
calculating gradient calculation in standard image processing by discretization of image data, and calculating gradient between adjacent pixels using differentiation in an expression shown in the following formula;
dividing pixels of an image into a plurality of layers according to brightness values, wherein the boundary of the image in each layer is formed by a closed curve, and the method specifically comprises the following steps: assuming that the luminance value i=i (x, y) of each pixel of the image I, the image I is divided into an I0 layer, an I1 layer, an I2 layer and an I3 layer by a set of thresholds I1, I2, I3;
for the I0 layer, the luminance value I of each pixel satisfies: i is more than or equal to 0 and less than i1;
for the I1 layer, the luminance value I of each pixel satisfies: i1 is less than or equal to i2;
for the I2 layer, the luminance value I of each pixel satisfies: i2 is less than or equal to i < i3;
for the I3 layer, the luminance value I of each pixel satisfies: i3 is more than or equal to i and less than or equal to 255;
i=i0+i1+i2+i3 corresponds to 4 layers of film stack, and the boundary of each layer of image is formed by a closed curve;
combining the plurality of processed image layers into an enhanced image, which specifically comprises the following steps: merging the I0 layer, the I1 layer, the I2 layer and the I3 layer into an enhanced image according to the formula I=I0×j0+I1×j1+I2×j2+I3×j3, wherein j0, j1, j2 and j3 are nonlinear coefficients or linear coefficients; where j=a×s+b, s=crγ, a, b are coefficients and are different when j is j0, j1, j2, j3, s is an exponential calibration function, and c, r and γ are normal numbers; in particular, in s=crγ, when c takes 1, γ takes different values Γ, a cluster of transformation curves is obtained, and when c=1, transformation curves of different γ values are obtained;
when gamma is less than 1, mapping the narrow-band input dark value to the wide-band output value by power conversion, and mapping the wide-band input bright value to the narrow-band output value;
when gamma is more than 1, mapping the broadband input dark value to the narrowband output value by power conversion, and mapping the narrowband input bright value to the broadband output value;
when γ=1, it is proportional linear transformation;
for pictures with uneven lighting at night, the dark part has a great deal of detail needed, and the bright part is easy to overexposure; adopting four layers to make the gamma value of the dark part layer smaller than 1; enhancing the visual data analysis capability of the dark place; for the bright portion layer, a calibration value γ value greater than 1 is used, so that the contrast inside the bright portion is enhanced.
4. The method for intelligent drawing system management of building level elevation map of claim 1, wherein,
the determining obtains the offset probability of the corresponding building area, and the construction transition state comprises a building area quantification rule and a building area evaluation rule.
5. The building level elevation view intelligent drawing system management method of claim 4, wherein the building area quantization rule comprises:
quantification of safety evaluation indexes:
the selected index quantization parameter is defined as S, wherein each factor is defined as (S0, S1, S2, … …), and a corresponding weight value (n 0, n1, n2, … …) is assigned to each factor, so that the total security value of the algorithm is:
S＝s0*n0+s1*n1+s2*n2……；
quantification of efficiency evaluation index:
the selected quantization parameter is defined as E, where each factor is defined as (E0, E1, E2, … …), and each factor is given a corresponding weight value (m 0, m1, m2, … …), then the overall efficiency value of the algorithm is:
E＝e0*m0+e1*m1+e2*m2……；
the strategies of each rule are ordered, the S/E value is used as a scalar, the explanation safety and efficiency close to 1 are the best, the explanation safety higher than 1 is low in efficiency, the explanation safety lower than 1 is high in efficiency, the corresponding probability is divided according to the distance from 1, the probability is smaller when the distance from 1 is larger, and the probability is larger when the distance from 1 is smaller;
the building area evaluation rule includes:
the specific formula is as follows:
P1＝w1*50％+w2*50％
P2＝1-P1
p1 represents good building area security, P2 represents poor building area security, w1 represents computer analysis, and w2 represents computer analysis.
6. An information data processing terminal for realizing the building layer high-level map intelligent drawing system management method according to any one of claims 1 to 5.
7. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the building level elevation map intelligent drawing system management method of any one of claims 1 to 5.
8. A building level elevation view intelligent drawing system for implementing the building level elevation view intelligent drawing system management method of claim 1, characterized in that the building level elevation view intelligent drawing system comprises:
the data input module is connected with the data identification module and used for inputting building data information;
the data identification module is connected with the data module and the central processing module and used for accurately identifying the input building data and extracting a building area;
the central processing module is connected with the data input module, the data identification module, the design module, the modeling module, the drawing design module, the data storage module and the display module and used for controlling the normal work of each module;
the design module is connected with the central processing module and is used for drawing and designing according to the input building data;
the modeling module is connected with the central processing module and is used for constructing a corresponding model according to the designed data;
the drawing design module is connected with the central processing module and is used for carrying out A3 or A4 drawing output design on the manufactured model;
the data storage module is connected with the central processing module and used for storing the processed building model data;
and the display module is connected with the central processing module and used for displaying the drawn building layer height map model effect map through a display.
9. A building drawing platform carrying the building layer height map intelligent drawing system of claim 8.
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