CN108734079A - Image big data instant analysis method - Google Patents
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- CN108734079A CN108734079A CN201810120409.5A CN201810120409A CN108734079A CN 108734079 A CN108734079 A CN 108734079A CN 201810120409 A CN201810120409 A CN 201810120409A CN 108734079 A CN108734079 A CN 108734079A
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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
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- G06V2201/07—Target detection
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Abstract
Image big data instant analysis method of the present invention is related to a kind of window state instant analysis method, the method includes：Use network shooting component, including IP cameras, data volume measuring apparatus, self-adapting compressing equipment and web-transporting device；Wherein, the IP cameras are 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 technology
With the development of science and technology, the technology of image capture device also increasingly improves.The image collected is more clear, differentiates
Rate, display effect also greatly improve.But existing image capture device the image collected cannot be satisfied 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 to have higher image processing techniques in this way, and in processing
The time for spending user more is needed, cumbersome, technical sophistication is handled.
Invention content
To solve the above-mentioned problems, the present invention provides a kind of window state instant analysis methods, using IP cameras 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 extraction, 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 extracts, and various different imageable targets are identified 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, row 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 ensureing 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, the method includes：
Use network shooting component, including IP cameras, data volume measuring apparatus, self-adapting compressing equipment and network transmission
Equipment, the IP cameras are used to carry out rotary image data shooting to site environment to obtain continuous multiframe site environment
Image, the data volume measuring apparatus are connect with the IP cameras, 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 apparatus, 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；
Using pixel detection equipment often going for the gain reinforcement image is detected for receiving the gain reinforcement image
Pixel quantity as row sum of all pixels, to detect the pixel quantity of each column of the gain reinforcement image using as row picture
Plain sum.
Description of the drawings
Embodiment of the present invention is described below with reference to attached drawing, wherein：
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 block diagram according to the window state instant analysis platform shown in embodiment of the present invention.
Specific implementation mode
The embodiment of the window state instant analysis method of the present 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 to meet higher
Thermal technology require.Advanced building can use double-deck even three layers of vacuum Low-E glass, two pass rubber weather strip, to ensure it
Best thermal and insulating performance.Horizontal skylight can make rimless unit, also referred to as dome skylight.Glass curtain wall can be recognized
To be a kind of special window, i.e. whole building exterior wall all becomes the window of light-permeable.
During the use 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 however, this monitoring is using manual type, being can not
Hitless operation in 24 hours can be kept, thus is unpractical, needs 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 to build 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 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 cameras, data volume measuring apparatus, self-adapting compressing equipment and network transmission are set
It is standby；
Wherein, the IP cameras are used to carry out rotary image data shooting to site environment to obtain continuous multiframe
Site environment image.
Then, continue that the concrete structure of the window state instant analysis platform of the present invention is further detailed.
In the window state instant analysis platform：
The data volume measuring apparatus is connect with the IP cameras, 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 apparatus, is used for the size of 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 often capable picture 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 row pixel
Number；
Reference data collecting device carries out brightness for receiving the gain reinforcement image to the gain reinforcement image
Peak is analyzed, and to obtain the corresponding maximum brightness value of the gain reinforcement image, and is established and is arrived the maximum brightness value with zero
To the maximum brightness value it is that ordinate is formed by numerical matrix for abscissa and zero, each number in the numerical matrix
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 circuit of pre-determined distance threshold value；
Slickness extraction equipment is connect with the reference data collecting device, for receiving the numerical matrix and described
Maximum brightness value, and execute following slickness extraction operation：For each data item in the numerical matrix, its cross is calculated
The difference of coordinate and ordinate square as the first intermediate value, the result obtained after first intermediate value is subtracted by 1
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 respectively with the pixel detection equipment and the slickness extraction equipment, for obtaining
The corresponding characteristic value of the gain reinforcement image, the row sum of all pixels of the gain reinforcement image and the gain reinforcement image
Row 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 row 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：The data volume of calculating is bigger, and the compressive strength to the site environment image of adjusting is higher, and is pressed
Site environment image after contracting.
And in the window state instant analysis platform：
The web-transporting device is additionally operable to fold every state parameter of the window target in the gain reinforcement image
It is added on corresponding site environment image, and the image after superposition is compressed to be wirelessly sent in far-end video service
The heart；
Wherein, the surface smoothness a reference value of window is more than the surface smoothness a reference value of timber, and the surface of timber is smooth
Property a reference value be more than wall surface smoothness a reference value and wall surface smoothness a reference value be more than lamps and lanterns surface light
Slip a reference value.
Meanwhile window state instant analysis method according to embodiments of the present invention includes the following steps：
Use network shooting component, including IP cameras, data volume measuring apparatus, self-adapting compressing equipment and network transmission
Equipment；
Wherein, the IP cameras are 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 the window state instant analysis method of the present invention are further detailed.
In the window state instant analysis method：
The data volume measuring apparatus is connect with the IP cameras, 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 apparatus, is used for the size of 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；
Using pixel detection equipment often going for the gain reinforcement image is detected for receiving the gain reinforcement image
Pixel quantity as row sum of all pixels, to detect the pixel quantity of each column of the gain reinforcement image using as row picture
Plain sum；
Using reference data collecting device, for receiving the gain reinforcement image, the gain reinforcement image is carried out
Maximum brightness value is analyzed, and 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 circuit 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 extraction equipment, connect with the reference data collecting device, for receive the numerical matrix and
The maximum brightness value, and execute following slickness extraction operation：For each data item in the numerical matrix, 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 extraction 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 row 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 row 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
It states three weighted terms to be added to obtain parameter to be compared, and the parameter to be compared and default each different objects surface is 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：The data volume of calculating is bigger, and the compressive strength to the site environment image of adjusting is higher, and is pressed
Site environment image after contracting.
In the window state instant analysis method：
The web-transporting device is additionally operable to fold every state parameter of the window target in the gain reinforcement image
It is added on corresponding site environment image, and the image after superposition is compressed to be wirelessly sent in far-end video service
The heart；
Wherein, the surface smoothness a reference value of window is more than the surface smoothness a reference value of timber, and the surface of timber is smooth
Property a reference value be more than wall surface smoothness a reference value and wall surface smoothness a reference value be more than lamps and lanterns surface light
Slip a reference value.
In addition, the web-transporting device is 4G web-transporting devices, 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 networks.
4G LTE are the standard of a global general-use, including two kinds of network modes FDD and TDD, are respectively used to paired spectrum
With non-paired frequency spectrum.Operator's initially choice between two patterns 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 areas 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, with protection frequency range come detach receive 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, but when supporting non-symmetrical service when supporting symmetrical service, frequency
Spectrum utilization rate will substantially reduce.
TDD sends and receivees channel with the time to detach.In the mobile communication system of TDD modes, 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.
Window state instant analysis platform using the present 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 of 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, every content without departing from technical solution of the present invention is 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 (4)
1. a kind of window state instant analysis method, which is characterized in that the method includes：
It is set using network shooting component, including IP cameras, data volume measuring apparatus, self-adapting compressing equipment and network transmission
It is standby；
Wherein, the IP cameras are used to carry out rotary image data shooting to site environment to obtain continuous multiframe scene
Ambient image.
2. window state instant analysis method as described in claim 1, it is characterised in that：
The data volume measuring apparatus is connect with the IP cameras, 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 apparatus, is used for the big minor adjustment of the data volume based on calculating
To the compressive strength of the site environment image.
3. window state instant analysis method as claimed in claim 2, it is characterised in that：
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.
4. window state instant analysis method as claimed in claim 3, which is characterized in that further include：
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；
Using pixel detection equipment the often capable picture of the gain reinforcement image is detected 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 row pixel
Number；
Using reference data collecting device, for receiving the gain reinforcement image, brightness is carried out to the gain reinforcement image
Peak is analyzed, and to obtain the corresponding maximum brightness value of the gain reinforcement image, and is established and is arrived the maximum brightness value with zero
To the maximum brightness value it is that ordinate is formed by numerical matrix for abscissa and zero, each number in the numerical matrix
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 circuit of pre-determined distance threshold value；
It using slickness extraction equipment, is connect with the reference data collecting device, for receiving the numerical matrix and described
Maximum brightness value, and execute following slickness extraction operation：For each data item in the numerical matrix, its cross is calculated
The difference of coordinate and ordinate square as the first intermediate value, the result obtained after first intermediate value is subtracted by 1
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 extraction equipment, for obtaining
The corresponding characteristic value of the gain reinforcement image, the row sum of all pixels of the gain reinforcement image and the gain reinforcement image
Row 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 row 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：The data volume of calculating is bigger, and the compressive strength to the site environment image of adjusting is higher, and after obtaining compression
Site environment image；
The web-transporting device is additionally operable to every state parameter of the window target in the gain reinforcement image being added to
On corresponding site environment image, and the image after superposition is compressed to be wirelessly sent to far-end video service centre；
Wherein, the surface smoothness a reference value of window is more than the surface smoothness a reference value of timber, the surface smoothness base of timber
Quasi- value is more than the surface smoothness of lamps and lanterns more than the surface smoothness a reference value of wall and the surface smoothness a reference value of wall
A reference value.
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Cited By (1)
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| CN111832433A (en) * | 2020-06-24 | 2020-10-27 | 科络克电子科技（上海）有限公司 | Device for extracting object characteristics from image and working method thereof |
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