CN108734079B - Image big data instant analysis method - Google Patents
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- CN108734079B CN108734079B CN201810120409.5A CN201810120409A CN108734079B CN 108734079 B CN108734079 B CN 108734079B CN 201810120409 A CN201810120409 A CN 201810120409A CN 108734079 B CN108734079 B CN 108734079B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/12—Details of acquisition arrangements; Constructional details thereof
- G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
- G06V10/147—Details of sensors, e.g. sensor lenses
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/94—Hardware or software architectures specially adapted for image or video understanding
- G06V10/95—Hardware or software architectures specially adapted for image or video understanding structured as a network, e.g. client-server architectures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/07—Target detection
Abstract
Image big data instant analysis method of the present invention is related to a kind of window state instant analysis method, which comprises uses network shooting component, including IP camera, data volume measuring device, self-adapting compressing equipment and web-transporting device；Wherein, the IP camera is used to carry out rotary image data shooting to site environment to obtain continuous multiframe site environment image.
Description
Technical field
The present invention relates to big data field more particularly to a kind of image big data instant analysis methods.
Background technique
With the development of science and technology, the technology of image capture device also increasingly improves.Acquired image is more clear, differentiates
Rate, display effect also greatly improve.But existing image capture device acquired image is unable to satisfy the more next of user's proposition
More individual requirements.The prior art can be handled after collecting image by user is further again to image manually,
To meet the individual requirement of user.But processing needs user's image processing techniques with higher in this way, and in processing
The time for needing to spend user more handles cumbersome, technology complexity.
Summary of the invention
To solve the above-mentioned problems, the present invention provides a kind of window state instant analysis methods, using IP camera pair
Site environment carries out rotary image data shooting to obtain continuous multiframe site environment image, to every frame site environment image
The identification of high-precision window target and the extraction of each window parameter are executed, to effectively maintain each window at the scene
There should be effect in environment.
Wherein, the present invention at least has the important inventive point of following four:
(1) style of shooting of rotary image data is convenient for identifying all kinds of monitoring objectives and realizes different state ginsengs
Number extracts, and improves on-site supervision effect；
(2) slickness based on window surface imaging is higher than the characteristic of the slickness of other body surfaces imaging, to target
The slickness of image is detected and is extracted, and identifies various different imageable targets so as to the slickness based on target image
Type；
(3) while the slickness based on target image carries out target type discrimination, the row of target image is also introduced
Sum of all pixels, column sum of all pixels participate in calculating, and introduce weight mechanism, to improve the accuracy of type discrimination results；
(4) operation of the self-adapting compressing based on data volume size is carried out by the image acquired to network shooting component,
While guaranteeing image effect, the bandwidth of network data transmission is reduced.
According to an aspect of the present invention, a kind of window state instant analysis method is provided, which comprises
Use network shooting component, including IP camera, data volume measuring device, self-adapting compressing equipment and network transmission
Equipment, the IP camera are used to carry out rotary image data shooting to site environment to obtain continuous multiframe site environment
Image, the data volume measuring device are connect with the IP camera, for receiving the site environment image and to described existing
Field ambient image carries out data volume calculating, and the self-adapting compressing equipment is connect with the data volume measuring device, for being based on
The big minor adjustment of the data volume of calculating to the compressive strength of the site environment image, the web-transporting device with it is described adaptive
Compression device is answered to connect, for compressed site environment image wireless to be sent to far-end video service centre；
Using automatic gain reinforcement equipment, held for receiving the site environment image, and to the site environment image
Row automatic gain reinforcement, to obtain simultaneously output gain reinforcement image；
Every row of the gain reinforcement image is detected for receiving the gain reinforcement image using pixel detection equipment
Pixel quantity as row sum of all pixels, to detect the pixel quantity of each column of the gain reinforcement image using as column picture
Plain sum.
Detailed description of the invention
Embodiment of the present invention is described below with reference to attached drawing, in which:
Fig. 1 is the outer of the target window that is monitored according to the window state instant analysis platform shown in embodiment of the present invention
Shape figure.
Fig. 2 is the structural block diagram according to the window state instant analysis platform shown in embodiment of the present invention.
Specific embodiment
The embodiment of window state instant analysis method of the invention is described in detail below with reference to accompanying drawings.
With the development of Building technology and the raising of human living standard, the construction of window is also increasingly sophisticated higher to meet
Thermal technology require.Advanced building can be using double-deck even three layers of vacuum Low-E glass, two pass rubber weather strip, to guarantee it
Optimal thermal and insulating performance.Horizontal skylight can be made rimless unit, also referred to as dome skylight.Glass curtain wall can be recognized
To be a kind of special window, i.e. the whole building exterior wall window that all becomes light-permeable.
In the use process of window, the current state of window is affected to the corresponding internal environment where window,
Accordingly, it is therefore desirable to maintain the monitoring of the state to indoor each window, if being can not however, this monitoring is using manual type
Be able to maintain hitless operation in 24 hours, thus be it is unpractical, need a kind of new technical solution to maintain to indoor each
The position of window identifies and succeeding state detection.
In order to overcome above-mentioned deficiency, the present invention has built a kind of image big data instant analysis method, i.e., a kind of window shape
The image big data instant analysis method of state, realizes the high accuracy analysis to window state and judgement.
Fig. 1 is the outer of the target window that is monitored according to the window state instant analysis platform shown in embodiment of the present invention
Shape figure, as shown in Figure 1, the target window that the window state instant analysis platform is monitored includes fixed window page 1 and active window
Page 2.
Fig. 2 is the structural block diagram according to the window state instant analysis platform shown in embodiment of the present invention, described flat
Platform includes:
Network shooting component, including IP camera, data volume measuring device, self-adapting compressing equipment and network transmission are set
It is standby；
Wherein, the IP camera is used to carry out rotary image data shooting to site environment to obtain continuous multiframe
Site environment image.
Then, continue that the specific structure of window state instant analysis platform of the invention is further detailed.
In the window state instant analysis platform:
The data volume measuring device is connect with the IP camera, for receiving the site environment image and to described
Site environment image carries out data volume calculating；
The self-adapting compressing equipment is connect with the data volume measuring device, the size for the data volume based on calculating
Adjust the compressive strength to the site environment image.
In the window state instant analysis platform:
The web-transporting device is connect with the self-adapting compressing equipment, for by compressed site environment image without
Line is sent to far-end video service centre.
Can also include: in the window state instant analysis platform
Automatic gain reinforcement equipment executes certainly for receiving the site environment image, and to the site environment image
Dynamic gain reinforcement, to obtain simultaneously output gain reinforcement image；
Pixel detection equipment detects the picture of every row of the gain reinforcement image for receiving the gain reinforcement image
Vegetarian refreshments quantity is as row sum of all pixels, to detect the pixel quantity of each column of the gain reinforcement image using total as column pixel
Number；
Reference data acquires equipment, for receiving the gain reinforcement image, carries out brightness to the gain reinforcement image
Peak analysis to obtain the corresponding maximum brightness value of the gain reinforcement image, and establishes and arrives the maximum brightness value with zero
It to the maximum brightness value is that ordinate is formed by numerical matrix, each number in the numerical matrix for abscissa and zero
It is in the gain reinforcement image, to be reached from the pixel for the abscissa that brightness value is the data item bright according to the numerical value of item
Angle value is the quantity that the distance of the pixel of the ordinate of the data item is less than the route of pre-determined distance threshold value；
Slickness extract equipment is connect, for receiving the numerical matrix and described with reference data acquisition equipment
Maximum brightness value, and execute following slickness extraction operation: for each of numerical matrix data item, calculate its cross
The difference of coordinate and ordinate square to subtract the result obtained after first intermediate value for 1 as the first intermediate value
It is inverted to obtain coefficient value, the coefficient value and the value of the data item are multiplied to obtain the corresponding component of the data item
The component value of all data item in the numerical matrix is added corresponding to obtain and export the gain reinforcement image by value
Slickness；
Material identification apparatus is connect, for obtaining respectively with the pixel detection equipment and the slickness extract equipment
The row sum of all pixels and the gain reinforcement image of the corresponding characteristic value of the gain reinforcement image, the gain reinforcement image
Column sum of all pixels, based on different weights coefficient to the corresponding characteristic value of the gain reinforcement image, the gain reinforcement image
Row sum of all pixels and the column sum of all pixels of the gain reinforcement image weighted respectively to obtain three weighted terms, by described three
A weighted term is added to obtain parameter to be compared, and by the parameter to be compared and presets each different objects surface smoothness base
Quasi- value is compared, to obtain and export the corresponding object type of the gain reinforcement image, the object type include window,
Wall, timber and lamps and lanterns；
State analysis equipment is connect with the material identification apparatus, is used for when the object type is window, to described
Window target in gain reinforcement image carries out the analysis and extraction of every state parameter, and exports in the gain reinforcement image
Window target every state parameter；
Wherein, the big minor adjustment of the data volume of the self-adapting compressing equipment based on calculating is to the site environment image
Compressive strength includes: that the data volume of calculating is bigger, adjusting it is higher to the compressive strength of the site environment image, and pressed
Site environment image after contracting.
And in the window state instant analysis platform:
The web-transporting device is also used to fold every state parameter of the window target in the gain reinforcement image
It is added on corresponding site environment image, and superimposed image is compressed to be wirelessly sent in far-end video service
The heart；
Wherein, the surface smoothness a reference value of window is greater than the surface smoothness a reference value of timber, and the surface of timber is smooth
Property a reference value be greater than wall surface smoothness a reference value and wall surface smoothness a reference value be greater than lamps and lanterns surface light
Slip a reference value.
Meanwhile window state instant analysis method according to embodiments of the present invention the following steps are included:
Use network shooting component, including IP camera, data volume measuring device, self-adapting compressing equipment and network transmission
Equipment；
Wherein, the IP camera is used to carry out rotary image data shooting to site environment to obtain continuous multiframe
Site environment image.
Then, continue that the specific steps of window state instant analysis method of the invention are further detailed.
In the window state instant analysis method:
The data volume measuring device is connect with the IP camera, for receiving the site environment image and to described
Site environment image carries out data volume calculating；
The self-adapting compressing equipment is connect with the data volume measuring device, the size for the data volume based on calculating
Adjust the compressive strength to the site environment image.
In the window state instant analysis method:
The web-transporting device is connect with the self-adapting compressing equipment, for by compressed site environment image without
Line is sent to far-end video service centre.
The window state instant analysis method can also include:
Using automatic gain reinforcement equipment, held for receiving the site environment image, and to the site environment image
Row automatic gain reinforcement, to obtain simultaneously output gain reinforcement image；
Every row of the gain reinforcement image is detected for receiving the gain reinforcement image using pixel detection equipment
Pixel quantity as row sum of all pixels, to detect the pixel quantity of each column of the gain reinforcement image using as column picture
Plain sum；
Equipment is acquired using reference data, for receiving the gain reinforcement image, the gain reinforcement image is carried out
Maximum brightness value analysis to obtain the corresponding maximum brightness value of the gain reinforcement image, and is established with zero to the brightness most
High level is abscissa and zero to the maximum brightness value is that ordinate is formed by numerical matrix, each in the numerical matrix
The numerical value of a data item is, in the gain reinforcement image, from brightness value be the data item abscissa pixel to
It is less than the quantity of the route of pre-determined distance threshold value for the distance of the pixel of the ordinate of the data item up to brightness value；
Using slickness extract equipment, connect with reference data acquisition equipment, for receive the numerical matrix with
The maximum brightness value, and execute following slickness extraction operation: for each of numerical matrix data item, calculate
The difference of its abscissa and ordinate square using as the first intermediate value, 1 subtracted and is obtained after first intermediate value
As a result inverted to obtain coefficient value, it is multiplied to the coefficient value and the value of the data item to obtain the data item corresponding
The component value of all data item in the numerical matrix is added to obtain and export the gain reinforcement image pair by component value
The slickness answered；
Using material identification apparatus, it connect, is used for the pixel detection equipment and the slickness extract equipment respectively
Obtain the corresponding characteristic value of the gain reinforcement image, the row sum of all pixels of the gain reinforcement image and the gain reinforcement
The column sum of all pixels of image, based on different weights coefficient to the corresponding characteristic value of the gain reinforcement image, the gain reinforcement
The column sum of all pixels of the row sum of all pixels of image and the gain reinforcement image is weighted respectively to obtain three weighted terms, by institute
Three weighted terms are stated to be added to obtain parameter to be compared, and by the parameter to be compared with to preset each different objects surface smooth
Property a reference value is compared, and to obtain and export the corresponding object type of the gain reinforcement image, the object type includes
Window, wall, timber and lamps and lanterns；
Use state analytical equipment is connect with the material identification apparatus, is used for when the object type is window, right
Window target in the gain reinforcement image carries out the analysis and extraction of every state parameter, and exports the gain reinforcement figure
Every state parameter of window target as in；
Wherein, the big minor adjustment of the data volume of the self-adapting compressing equipment based on calculating is to the site environment image
Compressive strength includes: that the data volume of calculating is bigger, adjusting it is higher to the compressive strength of the site environment image, and pressed
Site environment image after contracting.
In the window state instant analysis method:
The web-transporting device is also used to fold every state parameter of the window target in the gain reinforcement image
It is added on corresponding site environment image, and superimposed image is compressed to be wirelessly sent in far-end video service
The heart；
Wherein, the surface smoothness a reference value of window is greater than the surface smoothness a reference value of timber, and the surface of timber is smooth
Property a reference value be greater than wall surface smoothness a reference value and wall surface smoothness a reference value be greater than lamps and lanterns surface light
Slip a reference value.
In addition, the web-transporting device is 4G web-transporting device, it is connect with the self-adapting compressing equipment, being used for will
Compressed site environment image is wirelessly sent to far-end video service centre by 4G communication network.
4G LTE is the standard of a global general-use, including two kinds of network modes FDD and TDD, is respectively used to paired spectrum
With non-paired frequency spectrum.Operator's initially choice between two modes purely for spectrum availability the considerations of.Fortune mostly
Battalion quotient will dispose two kinds of networks simultaneously, so as to all frequency spectrum resources for making full use of it to possess.The technically area FDD and TDD
Very little, the main distinction are not that frequency division duplex (FDD) and time division duplex (TDD) are two using different duplex modes in fact
The different duplex mode of kind.
FDD is received and transmitted on two symmetrical frequency channels of separation, separated with protection frequency range reception and
Send channel.FDD must use pairs of frequency, carry out differentiating uplink and downlink link by frequency, unidirectional resource is in the time
On be continuous.FDD can make full use of the frequency spectrum of uplink and downlink when supporting symmetrical service, but when supporting non-symmetrical service, frequency
Spectrum utilization rate will substantially reduce.
TDD sends and receivees channel with the time to separate.In the mobile communication system of TDD mode, sending and receiving makes
Use the different time-gap of same frequency carrier wave as the carrying of channel, unidirectional resource is discontinuous, the time in time
Resource is distributed in two directions.Some period sends a signal to mobile station by base station, and the time in addition is by moving
Platform sends a signal to base station, must harmonious ability work well between base station and mobile station.
Using window state instant analysis platform of the invention and method, for each of indoor scene environment in the prior art
The technical issues of a window state-detection inefficiency, obtains the indoor scene figure of all angles by rotary style of shooting
Picture, and signature analysis is carried out to indoor scene image and is determining corresponding object type to obtain the corresponding object type of image
In the case where for window, the extraction of each state parameter of corresponding window is carried out, to improve each window of site environment
The automatization level of state-detection.
It is understood that although the present invention has been disclosed in the preferred embodiments as above, above-described embodiment not to
Limit the present invention.For any person skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible changes and modifications all are made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of variation.Therefore, anything that does not depart from the technical scheme of the invention are right according to the technical essence of the invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments still fall within the range of technical solution of the present invention protection
It is interior.
Claims (1)
1. a kind of window state instant analysis method, which is characterized in that the described method includes:
It is set using network shooting component, including IP camera, data volume measuring device, self-adapting compressing equipment and network transmission
It is standby；
Wherein, the IP camera is used to carry out rotary image data shooting to site environment to obtain continuous multiframe scene
Ambient image；
The data volume measuring device is connect with the IP camera, for receiving the site environment image and to the scene
Ambient image carries out data volume calculating；
The self-adapting compressing equipment is connect with the data volume measuring device, the big minor adjustment for the data volume based on calculating
To the compressive strength of the site environment image；
The web-transporting device is connect with the self-adapting compressing equipment, for sending out compressed site environment image wireless
Give far-end video service centre；
Using automatic gain reinforcement equipment, executed certainly for receiving the site environment image, and to the site environment image
Dynamic gain reinforcement, to obtain simultaneously output gain reinforcement image；
The picture of every row of the gain reinforcement image is detected for receiving the gain reinforcement image using pixel detection equipment
Vegetarian refreshments quantity is as row sum of all pixels, to detect the pixel quantity of each column of the gain reinforcement image using total as column pixel
Number；
Equipment is acquired using reference data, for receiving the gain reinforcement image, brightness is carried out to the gain reinforcement image
Peak analysis to obtain the corresponding maximum brightness value of the gain reinforcement image, and establishes and arrives the maximum brightness value with zero
It to the maximum brightness value is that ordinate is formed by numerical matrix, each number in the numerical matrix for abscissa and zero
It is in the gain reinforcement image, to be reached from the pixel for the abscissa that brightness value is the data item bright according to the numerical value of item
Angle value is the quantity that the distance of the pixel of the ordinate of the data item is less than the route of pre-determined distance threshold value；
It using slickness extract equipment, is connect with reference data acquisition equipment, for receiving the numerical matrix and described
Maximum brightness value, and execute following slickness extraction operation: for each of numerical matrix data item, calculate its cross
The difference of coordinate and ordinate square to subtract the result obtained after first intermediate value for 1 as the first intermediate value
It is inverted to obtain coefficient value, the coefficient value and the value of the data item are multiplied to obtain the corresponding component of the data item
The component value of all data item in the numerical matrix is added corresponding to obtain and export the gain reinforcement image by value
Slickness；
Using material identification apparatus, it is connect respectively with the pixel detection equipment and the slickness extract equipment, for obtaining
The row sum of all pixels and the gain reinforcement image of the corresponding slickness of the gain reinforcement image, the gain reinforcement image
Column sum of all pixels, based on different weights coefficient to the corresponding slickness of the gain reinforcement image, the gain reinforcement image
Row sum of all pixels and the column sum of all pixels of the gain reinforcement image weighted respectively to obtain three weighted terms, by described three
A weighted term is added to obtain parameter to be compared, and by the parameter to be compared and presets each different objects surface smoothness base
Quasi- value is compared, to obtain and export the corresponding object type of the gain reinforcement image, the object type include window,
Wall, timber and lamps and lanterns；
Use state analytical equipment is connect with the material identification apparatus, is used for when the object type is window, to described
Window target in gain reinforcement image carries out the analysis and extraction of every state parameter, and exports in the gain reinforcement image
Window target every state parameter；
Wherein, compression of the big minor adjustment of the data volume of the self-adapting compressing equipment based on calculating to the site environment image
Intensity includes: that the data volume of calculating is bigger, adjusting it is higher to the compressive strength of the site environment image, and after obtaining compression
Site environment image；
The web-transporting device is also used to for every state parameter of the window target in the gain reinforcement image being added to
On corresponding site environment image, and superimposed image is compressed to be wirelessly sent to far-end video service centre；
Wherein, the surface smoothness a reference value of window is greater than the surface smoothness a reference value of timber, the surface smoothness base of timber
Quasi- value is greater than the surface smoothness a reference value of wall and the surface smoothness a reference value of wall is greater than the surface smoothness of lamps and lanterns
A reference value；
Wherein, the web-transporting device is 4G web-transporting device, is connect with the self-adapting compressing equipment, for that will compress
Site environment image afterwards is wirelessly sent to far-end video service centre by 4G communication network, wherein 4G LTE is one complete
The general standard of ball, including two kinds of network modes FDD and TDD, are respectively used to paired spectrum and non-paired frequency spectrum, frequency division duplex
That is FDD and time division duplex, that is, TDD is two different duplex modes, and FDD is carried out on two symmetrical frequency channels of separation
It sends and receivees, is separated with protection frequency range and send and receive channel, FDD must use pairs of frequency, come area by frequency
Divide uplink downlink, unidirectional resource is continuously that TDD sends and receivees channel with the time to separate in time.
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Effective date of registration: 20190326 Address after: Room 3056, Area A, Building 7, Building 3, 88 Chenxiang Road, Jiading District, Shanghai 201800 Applicant after: Shanghai Limo Network Technology Co., Ltd. Address before: 213164 Changzhou Institute of Information Technology, 22 Mingxinzhong Road, Changzhou University City, Jiangsu Province Applicant before: Chen Bo |
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