CN108809780A - A kind of intelligent domestic system - Google Patents
A kind of intelligent domestic system Download PDFInfo
- Publication number
- CN108809780A CN108809780A CN201810677027.2A CN201810677027A CN108809780A CN 108809780 A CN108809780 A CN 108809780A CN 201810677027 A CN201810677027 A CN 201810677027A CN 108809780 A CN108809780 A CN 108809780A
- Authority
- CN
- China
- Prior art keywords
- image
- module
- feature parameter
- indicate
- foreground
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
- H04L12/2816—Controlling appliance services of a home automation network by calling their functionalities
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
The present invention provides a kind of intelligent domestic systems, including environmental monitoring system, safety defense monitoring system, home gateway, control terminal and household terminal, the environmental monitoring system and safety defense monitoring system are communicated to connect with home gateway, the environmental monitoring system acquires indoor environmental information using sensor, the safety defense monitoring system is for detecting indoor foreground target, generate monitoring information, the environmental information of acquisition and monitoring information are sent to control terminal by the intelligent domestic gateway, the control terminal generates control signal according to environmental information and monitoring information, household terminal is controlled.Beneficial effects of the present invention are:A kind of intelligent domestic system is provided, environmental monitoring and safety monitoring and effective control to smart home are realized.
Description
Technical field
The present invention relates to Smart Home technical fields, and in particular to a kind of intelligent domestic system.
Background technology
With the rapid development of science and technology, intelligent domestic system has become the project of industry focus.Intelligent family
Residence be using house as platform, it is related with home life using network communication technology, security precautions technology, automatic control technology etc.
Equipment is integrated, and the management system of efficient housing facilities and schedule affairs in family is built, and promotes house security, facility
Property, comfort.
In existing intelligent domestic system, user can't be made to know indoor situation in family in real time, there are no can be real
When be monitored and controlled family in indoor conditions (whether such as indoor temperature humidity, has security risk) intelligent domestic system.
Invention content
In view of the above-mentioned problems, the present invention is intended to provide a kind of intelligent domestic system.
The purpose of the present invention is realized using following technical scheme:
A kind of intelligent domestic system is provided, including environmental monitoring system, safety defense monitoring system, home gateway, control are eventually
End and household terminal, the environmental monitoring system and safety defense monitoring system are communicated to connect with home gateway, the environmental monitoring
System acquires indoor environmental information using sensor, and the safety defense monitoring system is generated for detecting indoor foreground target
The environmental information of acquisition and monitoring information are sent to control terminal by monitoring information, the intelligent domestic gateway, and the control is eventually
End generates control signal according to environmental information and monitoring information, controls household terminal.
Beneficial effects of the present invention are:Provide a kind of intelligent domestic system, realize environmental monitoring and safety monitoring with
And effective control to smart home.
Optionally, the safety defense monitoring system includes the first detection subsystem and the second detection subsystem, first inspection
It includes image collection module, preprocessing module, the first foreground detection module to survey subsystem, and described image acquisition module is for obtaining
Detection image, the preprocessing module for being filtered to detection image, the first foreground detection module for pair
The foreground of detection image is detected, and the second detection subsystem includes parameter determination module, filters out module and the second foreground
Detection module, the parameter determination module are used to determine the characteristic parameter of image, and the module that filters out is for the spy according to image
Sign parameter filters out underproof detection image, and the second foreground detection module is used for according to after filtering out unqualified detection image
Detection image is detected foreground.
Optionally, the parameter determination module includes first processing module, Second processing module, third processing module and
Four processing modules, the first processing module are used to determine the fisrt feature parameter of image, and the Second processing module is for true
Determine the second feature parameter of image, the third processing module is used to determine the third feature parameter of image, the fourth process
Module is used to determine the fourth feature parameter of image.
Optionally, the first processing module is used to determine the fisrt feature parameter of image, specially:
By image in HSB space representations, indicate that background image, P (t) indicate that the image of t moment, P (t-1) indicate with P (0)
The image at t-1 moment;
Image fisrt feature parameter is determined using following formula:
In formula, E1(t, 0), E1(t, t-1) indicates that the fisrt feature parameter of image, M indicate that the width of image, N indicate image
Height, I indicate the maximum value of tone, Hi(t) number for the pixel that tone value is i in P (t), H are indicatedi(0) tone in P (0) is indicated
Value is the number of the pixel of i, Hi(t-1) number for the pixel that tone value is i in P (t-1) is indicated;The fisrt feature parameter is got over
Greatly, indicate that two images tone variations are bigger.
Optionally, the Second processing module is used to determine the second feature parameter of image, specially:
Image is indicated in gray space, subtracts each other to obtain gray scale difference component with original image and filtered gray level image
As Pa, grey scale difference image is converted by binary edge map P using following formulab:
In formula, Pb(x, y) indicates binary edge map PbIn the pixel value of position (x, y), Pa(x, y) indicates grey scale difference image Pa?
The pixel value of position (x, y), Y2Indicate preset binary-state threshold;
If the edge image of P (0) is Pb(0), the edge image of P (t) is Pb(t), the edge image of P (t-1) is Pb(t-
1) image second feature parameter E, is determined using following formula2(t, 0), E2(t, t-1):
In formula, E2(t, 0), E2(t, t-1) indicates the second feature parameter of image,Indicate xor operation, ∪ is indicated or behaviour
Make,It indicates respectivelyIntermediate value is not equal to 0 pixel
Number;The second feature parameter is bigger, indicates that the difference degree between two images edge is bigger.
Optionally, the third processing module is used to determine the third feature parameter of image, specially:
Image third feature parameter E is determined using following formula3(t):
In formula, E3(t) the third feature parameter of image, P are indicatedf(t) indicate that t moment bianry image, the value of foreground pixel are
255, the value of background pixel is 0, S (Pf(t)) P is indicatedf(t) number of pixel of the intermediate value not equal to 0;The third feature parameter
It is bigger, indicate t moment foreground pixel number account for total number of image pixels ratio it is higher.
Optionally, the fourth processing module is used to determine the fourth feature parameter of image, specially:
By image in HSB space representations, indicate that background image, P (t) indicate that the image of t moment, P (t-1) indicate with P (0)
The image at t-1 moment;
Image fourth feature parameter is determined using following formula:
In formula, E4(t, 0), E4(t, t-1) indicates that the fisrt feature parameter of image, M indicate that the width of image, N indicate image
Height, I indicate the maximum value of brightness, Bj(t) number for the pixel that brightness value is i in P (t), B are indicatedj(0) brightness in P (0) is indicated
Value is the number of the pixel of i, Bj(t-1) number for the pixel that brightness value is i in P (t-1) is indicated;The fourth feature parameter is got over
Greatly, indicate that two images brightness change is bigger.
Optionally, described to filter out that module filters out module including the first image, the second image filters out module and the filter of third image
Except module, described first image filters out module for being filtered out to similar image, second image filter out module for pair
The violent image of scene changes is filtered out, and the third image filters out module for being carried out to the image that wrong foreground detection occurs
It filters out.
Optionally, described first image filters out module for being filtered out to similar image, specially:If meeting E simultaneously2
(t, 0)<Z0, E2(t, t-1)<Z0, E3(t-1)<Z1, then filtered out using the image as similar image, wherein Z0It indicates to judge
The whether identical threshold value in two images edge, if being less than the threshold value, then it is assumed that two images are identical, Z1Expression judges foreground object
Whether negligible threshold value, if be less than the threshold value, then it is assumed that foreground can be ignored;
Second image filters out module for being filtered out to the violent image of scene changes, specially:If meeting E1(t,
0)>Z2、E1(t, t-1)>Z2、E4(t, 0)>Z3, E4(t, t-1)>Z3In arbitrary condition, then it is assumed that image scene variation is violent,
It is filtered out, wherein Z2Expression judges whether picture tone occurs the threshold value of significantly change, if more than the threshold value, then pattern colour
Readjust the distribution raw significantly change, Z3Expression judges whether brightness of image occurs the threshold value of significantly change, and if more than the threshold value, then image is bright
Significantly change occurs for degree;
The third image filters out module for being filtered out to the image that wrong foreground detection occurs, specially:If full
Sufficient E3(t)>Z5, Z5Expression judge the excessive threshold value of foreground object, then using the image as generation mistake foreground detection image into
Row filters out.
Description of the drawings
Using attached drawing, the invention will be further described, but the embodiment in attached drawing does not constitute any limit to the present invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the structural schematic diagram of the present invention;
Reference numeral:
Environmental monitoring system 1, safety defense monitoring system 2, home gateway 3, control terminal 4, household terminal 5.
Specific implementation mode
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of intelligent domestic system of the present embodiment, including environmental monitoring system 1, safety defense monitoring system 2, family
Gateway 3, control terminal 4 and household terminal 5 are occupied, the environmental monitoring system 1 and safety defense monitoring system 2 are logical with home gateway 3
Letter connection, the environmental monitoring system 1 acquire indoor environmental information using sensor, and the safety defense monitoring system 2 is for examining
Indoor foreground target is surveyed, monitoring information is generated, the intelligent domestic gateway 3 sends the environmental information of acquisition and monitoring information
To control terminal 4, the control terminal 4 generates control signal according to environmental information and monitoring information, is controlled to household terminal 5
System.
A kind of intelligent domestic system is present embodiments provided, realizes environmental monitoring and safety monitoring and to smart home
Effective control.
Preferably, the safety defense monitoring system 2 includes the first detection subsystem and the second detection subsystem, first inspection
It includes image collection module, preprocessing module, the first foreground detection module to survey subsystem, and described image acquisition module is for obtaining
Detection image, the preprocessing module for being filtered to detection image, the first foreground detection module for pair
The foreground of detection image is detected, and the second detection subsystem includes parameter determination module, filters out module and the second foreground
Detection module, the parameter determination module are used to determine the characteristic parameter of image, and the module that filters out is for the spy according to image
Sign parameter filters out underproof detection image, and the second foreground detection module is used for according to after filtering out unqualified detection image
Detection image is detected foreground.
This preferred embodiment is by screening image, and overcoming previous foreground detection, use may destroy the back of the body in the process
The image of scape model carries out foreground detection, improves the robustness of foreground detection.
Preferably, the parameter determination module includes first processing module, Second processing module, third processing module and
Four processing modules, the first processing module are used to determine the fisrt feature parameter of image, and the Second processing module is for true
Determine the second feature parameter of image, the third processing module is used to determine the third feature parameter of image, the fourth process
Module is used to determine the fourth feature parameter of image;
The first processing module is used to determine the fisrt feature parameter of image, specially:
By image in HSB space representations, indicate that background image, P (t) indicate that the image of t moment, P (t-1) indicate with P (0)
The image at t-1 moment;
Image fisrt feature parameter is determined using following formula:
In formula, E1(t, 0), E1(t, t-1) indicates that the fisrt feature parameter of image, M indicate that the width of image, N indicate image
Height, I indicate the maximum value of tone, Hi(t) number for the pixel that tone value is i in P (t), H are indicatedi(0) tone in P (0) is indicated
Value is the number of the pixel of i, Hi(t-1) number for the pixel that tone value is i in P (t-1) is indicated;The fisrt feature parameter is got over
Greatly, indicate that two images tone variations are bigger;
The Second processing module is used to determine the second feature parameter of image, specially:
Image is indicated in gray space, subtracts each other to obtain gray scale difference component with original image and filtered gray level image
As Pa, grey scale difference image is converted by binary edge map P using following formulab:
In formula, Pb(x, y) indicates binary edge map PbIn the pixel value of position (x, y), Pa(x, y) indicates grey scale difference image Ps?
The pixel value of position (x, y), T2Indicate preset binary-state threshold;
If the edge image of P (0) is Pb(0), the edge image of P (t) is Pb(t), the edge image of P (t-1) is Pb(t-
1) image second feature parameter E, is determined using following formula2(t, 0), E2(t, t-1):
In formula, E2(t, 0), E2(t, t-1) indicates the second feature parameter of image,Indicate xor operation, ∪ is indicated or behaviour
Make,It indicates respectivelyIntermediate value is not equal to 0 pixel
Number;The second feature parameter is bigger, indicates that the difference degree between two images edge is bigger;
The third processing module is used to determine the third feature parameter of image, specially:
Image third feature parameter E is determined using following formula3(t):
In formula, E3(t) the third feature parameter of image, P are indicatedf(t) indicate that t moment bianry image, the value of foreground pixel are
255, the value of background pixel is 0, S (Pf(t)) P is indicatedf(t) number of pixel of the intermediate value not equal to 0;The third feature parameter
It is bigger, indicate t moment foreground pixel number account for total number of image pixels ratio it is higher;
The fourth processing module is used to determine the fourth feature parameter of image, specially:
By image in HSB space representations, indicate that background image, P (t) indicate that the image of t moment, P (t-1) indicate with P (0)
The image at t-1 moment;
Image fourth feature parameter is determined using following formula:
In formula, E4(t, 0), E4(t, t-1) indicates that the fisrt feature parameter of image, M indicate that the width of image, N indicate image
Height, I indicate the maximum value of brightness, Bj(t) number for the pixel that brightness value is i in P (t), B are indicatedj(0) brightness in P (0) is indicated
Value is the number of the pixel of i, Bj(t-1) number for the pixel that brightness value is i in P (t-1) is indicated;The fourth feature parameter is got over
Greatly, indicate that two images brightness change is bigger;
The change of brightness of image, tone and edge feature is turned to image parameter by this preferred embodiment, passes through characteristics of image
The parameter of variation describes input picture and foreground detection result.By describing input picture, avoid use that from may destroying background
The image of model carries out the update of background model;Specifically, fisrt feature parameter is bigger, indicate that two images tone variations are got over
Greatly, second feature parameter is bigger, indicates that the difference degree between two images edge is bigger, and third feature parameter is bigger, indicates t
The ratio that the number of moment foreground pixel accounts for total number of image pixels is higher, and fourth feature parameter is bigger, indicates two images brightness
Variation is bigger;
Preferably, described to filter out that module filters out module including the first image, the second image filters out module and the filter of third image
Except module, described first image filters out module for being filtered out to similar image, second image filter out module for pair
The violent image of scene changes is filtered out, and the third image filters out module for being carried out to the image that wrong foreground detection occurs
It filters out;
Described first image filters out module for being filtered out to similar image, specially:If meeting E simultaneously2(t, 0)<
Z0, E2(t, t-1)<Z0, E3(t-1)<Z1, then filtered out using the image as similar image, wherein Z0Expression judges two width figures
As the whether identical threshold value in edge, if being less than the threshold value, then it is assumed that two images are identical, Z1Expression judges that foreground object whether may be used
With the threshold value ignored, if being less than the threshold value, then it is assumed that foreground can be ignored;
Second image filters out module for being filtered out to the violent image of scene changes, specially:If meeting E1(t,
0)>Z2、E1(t, t-1)>Z2、E4(t, 0)>Z3, E4(t, t-1)>Z3In arbitrary condition, then it is assumed that image scene variation is violent,
It is filtered out, wherein Z2Expression judges whether picture tone occurs the threshold value of significantly change, if more than the threshold value, then pattern colour
Readjust the distribution raw significantly change, Z3Expression judges whether brightness of image occurs the threshold value of significantly change, and if more than the threshold value, then image is bright
Significantly change occurs for degree;
The third image filters out module for being filtered out to the image that wrong foreground detection occurs, specially:If full
Sufficient E3(t)>Z5, Z5Expression judge the excessive threshold value of foreground object, then using the image as generation mistake foreground detection image into
Row filters out;
This preferred embodiment realizes filtering out for image, ensure that the accuracy of display foreground detection, specifically, according to the
One characteristic parameter, second feature parameter, third feature image and fourth feature parameter are to similar image, scene acute variation image
It is filtered out with the image that wrong foreground detection occurs, realizes the accurate of image and filter out.
Through the above description of the embodiments, those skilled in the art can be understood that it should be appreciated that can
To realize the embodiments described herein with hardware, software, firmware, middleware, code or its any appropriate combination.For hardware
It realizes, processor can be realized in one or more the following units:Application-specific integrated circuit (ASIC), digital signal processor
(DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processing
Device, controller, microcontroller, microprocessor, other electronic units or combinations thereof designed for realizing functions described herein.
For software implementations, some or all of embodiment flow can instruct relevant hardware to complete by computer program.
When realization, above procedure can be stored in computer-readable medium or as the one or more on computer-readable medium
Instruction or code are transmitted.Computer-readable medium includes computer storage media and communication media, wherein communication media packet
It includes convenient for transmitting any medium of computer program from a place to another place.Storage medium can be that computer can
Any usable medium of access.Computer-readable medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other
Optical disc storage, magnetic disk storage medium or other magnetic storage apparatus or can be used in carry or store with instruction or data
The desired program code of structure type simultaneously can be by any other medium of computer access.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation for protecting range, although being explained in detail to the present invention with reference to preferred embodiment, the ordinary skill destination of this field
It should be appreciated that can be modified or replaced equivalently to technical scheme of the present invention, without departing from technical solution of the present invention
Spirit and scope.
Claims (9)
1. a kind of intelligent domestic system, which is characterized in that including environmental monitoring system, safety defense monitoring system, home gateway, control
Terminal and household terminal, the environmental monitoring system and safety defense monitoring system are communicated to connect with home gateway, the environment prison
Control system acquires indoor environmental information using sensor, and the safety defense monitoring system is raw for detecting indoor foreground target
At monitoring information, the environmental information of acquisition and monitoring information are sent to control terminal, the control by the intelligent domestic gateway
Terminal generates control signal according to environmental information and monitoring information, controls household terminal.
2. intelligent domestic system according to claim 1, which is characterized in that the safety defense monitoring system includes the first detection
Subsystem and the second detection subsystem, the first detection subsystem includes image collection module, preprocessing module, the first foreground
Detection module, described image acquisition module is for obtaining detection image, and the preprocessing module is for filtering detection image
Wave processing, the first foreground detection module is for being detected the foreground of detection image, the second detection subsystem packet
It includes parameter determination module, filter out module and the second foreground detection module, the parameter determination module is used to determine the feature of image
Parameter, the module that filters out according to the characteristic parameter of image for filtering out underproof detection image, second foreground detection
Module is used to be detected foreground according to filtering out the detection image after unqualified detection image.
3. intelligent domestic system according to claim 2, which is characterized in that the parameter determination module includes the first processing
Module, Second processing module, third processing module and fourth processing module, the first processing module are used to determine the of image
One characteristic parameter, the Second processing module are used to determine the second feature parameter of image, and the third processing module is for true
Determine the third feature parameter of image, the fourth processing module is used to determine the fourth feature parameter of image.
4. intelligent domestic system according to claim 3, which is characterized in that the first processing module is for determining image
Fisrt feature parameter, specially:
By image in HSB space representations, indicate that background image, P (t) indicate that the image of t moment, P (t-1) indicate t-1 with P (0)
The image at moment;
Image fisrt feature parameter is determined using following formula:
In formula, E1(t, 0), E1(t, t-1) indicates that the fisrt feature parameter of image, M indicate that the width of image, N indicate the height of image, I
Indicate the maximum value of tone, Hi(t) number for the pixel that tone value is i in P (t), H are indicatedi(0) indicate that tone value is i in P (0)
Pixel number, Hi(t-1) number for the pixel that tone value is i in P (t-1) is indicated;The fisrt feature parameter is bigger, table
Show that two images tone variations are bigger.
5. intelligent domestic system according to claim 4, which is characterized in that the Second processing module is for determining image
Second feature parameter, specially:
Image is indicated in gray space, is subtracted each other to obtain grey scale difference image P with original image and filtered gray level imagea,
Grey scale difference image is converted by binary edge map P using following formulab:In formula,
Pb(x, y) indicates binary edge map PbIn the pixel value of position (x, y), Pa(x, y) indicates grey scale difference image PaIn position
The pixel value of (x, y), T2Indicate preset binary-state threshold;
If the edge image of P (0) is Pb(0), the edge image of P (t) is Pb(t), the edge image of P (t-1) is Pb(t-1), it adopts
Image second feature parameter E is determined with following formula2(t, 0), E2(t, t-1):
In formula, E2(t, 0), E2(t, t-1) indicates the second feature parameter of image,Indicating xor operation, ∪ is indicated or operation,S[Pb(t)∪Pb(0)]、S[Pb(t)∪Pb(t-1)] it indicates respectively[Pb(t)∪Pb(0)]、[Pb(t)∪Pb(t-1)] intermediate value is not equal to 0 pixel
Number;The second feature parameter is bigger, indicates that the difference degree between two images edge is bigger.
6. intelligent domestic system according to claim 5, which is characterized in that the third processing module is for determining image
Third feature parameter, specially:
Image third feature parameter E is determined using following formula3(t):
In formula, E3(t) the third feature parameter of image, P are indicatedf(t) t moment bianry image is indicated, the value of foreground pixel is 255,
The value of background pixel is 0, S (Pf(t)) P is indicatedf(t) number of pixel of the intermediate value not equal to 0;The third feature parameter is bigger,
The ratio that the number of expression t moment foreground pixel accounts for total number of image pixels is higher.
7. intelligent domestic system according to claim 6, which is characterized in that the fourth processing module is for determining image
Fourth feature parameter, specially:
By image in HSB space representations, indicate that background image, P (t) indicate that the image of t moment, P (t-1) indicate t-1 with P (0)
The image at moment;
Image fourth feature parameter is determined using following formula:
In formula, E4(t, 0), E4(t, t-1) indicates that the fisrt feature parameter of image, M indicate that the width of image, N indicate the height of image, I
Indicate the maximum value of brightness, Bj(t) number for the pixel that brightness value is i in P (t), B are indicatedj(0) indicate that brightness value is i in P (0)
Pixel number, Bj(t-1) number for the pixel that brightness value is i in P (t-1) is indicated;The fourth feature parameter is bigger, table
Show that two images brightness change is bigger.
8. intelligent domestic system according to claim 7, which is characterized in that the module that filters out is filtered out including the first image
Module, the second image filter out module and third image filters out module, described first image filter out module for similar image into
Row filters out, and second image filters out module for being filtered out to the violent image of scene changes, and the third image filters out mould
Block is used to filter out the image that wrong foreground detection occurs.
9. intelligent domestic system according to claim 8, which is characterized in that described first image filters out module for phase
It is filtered out like image, specially:If meeting E simultaneously2(t, 0) < Z0, E2(t, t-1) < Z0, E3(t-1) < Z1, then by the figure
As being filtered out as similar image, wherein Z0Expression judges the whether identical threshold value in two images edge, if being less than the threshold
Value, then it is assumed that two images are identical, Z1Expression judges the whether negligible threshold value of foreground object, if being less than the threshold value, recognizes
It can ignore for foreground;
Second image filters out module for being filtered out to the violent image of scene changes, specially:If meeting E1(t, 0) >
Z2、E1(t, t-1) > Z2、E4(t, 0) > Z3, E4(t, t-1) > Z3In arbitrary condition, then it is assumed that image scene variation is violent,
It is filtered out, wherein Z2Expression judges whether picture tone occurs the threshold value of significantly change, if more than the threshold value, then pattern colour
Readjust the distribution raw significantly change, Z3Expression judges whether brightness of image occurs the threshold value of significantly change, and if more than the threshold value, then image is bright
Significantly change occurs for degree;
The third image filters out module for being filtered out to the image that wrong foreground detection occurs, specially:If meeting E3
(t) > Z5, Z5Expression judges the excessive threshold value of foreground object, then is carried out the image as the image that wrong foreground detection occurs
It filters out.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810677027.2A CN108809780A (en) | 2018-06-27 | 2018-06-27 | A kind of intelligent domestic system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810677027.2A CN108809780A (en) | 2018-06-27 | 2018-06-27 | A kind of intelligent domestic system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN108809780A true CN108809780A (en) | 2018-11-13 |
Family
ID=64072222
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810677027.2A Withdrawn CN108809780A (en) | 2018-06-27 | 2018-06-27 | A kind of intelligent domestic system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108809780A (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103019181A (en) * | 2012-11-20 | 2013-04-03 | 程亮 | Intelligent internet-of-things home system based on ZigBee wireless communication protocol |
CN203206269U (en) * | 2013-04-15 | 2013-09-18 | 深圳市宁冠鸿科技有限公司 | Control system for intelligent home furnishing |
CN204287783U (en) * | 2014-11-26 | 2015-04-22 | 中铁建工集团诺德投资有限公司 | Intelligent domestic system |
CN206224219U (en) * | 2016-07-14 | 2017-06-06 | 深圳易趣合智能技术有限公司 | A kind of intelligent home control system |
-
2018
- 2018-06-27 CN CN201810677027.2A patent/CN108809780A/en not_active Withdrawn
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103019181A (en) * | 2012-11-20 | 2013-04-03 | 程亮 | Intelligent internet-of-things home system based on ZigBee wireless communication protocol |
CN203206269U (en) * | 2013-04-15 | 2013-09-18 | 深圳市宁冠鸿科技有限公司 | Control system for intelligent home furnishing |
CN204287783U (en) * | 2014-11-26 | 2015-04-22 | 中铁建工集团诺德投资有限公司 | Intelligent domestic system |
CN206224219U (en) * | 2016-07-14 | 2017-06-06 | 深圳易趣合智能技术有限公司 | A kind of intelligent home control system |
Non-Patent Citations (1)
Title |
---|
马琼雄: "基于视觉的服务机器人人机交互技术研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108885813B (en) | Intelligent sales counter, article identification method, apparatus, server and storage medium | |
CN108932510A (en) | A kind of rubbish detection method and device | |
CN109484935A (en) | A kind of lift car monitoring method, apparatus and system | |
EP2779172A1 (en) | System and method of audio information display on video playback timeline | |
CN101460971A (en) | Uncleanness detecting device | |
CN105554380B (en) | A kind of switching method and device round the clock | |
CN108389352A (en) | Fire source probing method and device | |
CN110363731B (en) | Image fusion method and device and electronic equipment | |
CN110390229A (en) | A kind of face picture screening technique, device, electronic equipment and storage medium | |
CN109302566A (en) | A kind of method, apparatus and terminal device of determining screening-mode | |
CN109961042A (en) | Smoke detection method combining deep convolutional neural network and visual change diagram | |
CN105279511A (en) | Color time varying characteristic-based traffic light relocating method and device | |
CN108093183B (en) | Camera day and night mode switching method and terminal equipment | |
CN105005852A (en) | Image analysis based intelligent monitoring system for dormitory environment | |
CN109378067A (en) | Terminal control method and healthy and safe educational management all-in-one machine | |
CN116129102A (en) | Water meter identification method and related device based on improved image processing algorithm | |
EP3698336A1 (en) | Intrusion detection methods and devices | |
CN108876824B (en) | Target tracking method, device and system and dome camera | |
CN108809780A (en) | A kind of intelligent domestic system | |
CN110321808A (en) | Residue and robber move object detecting method, equipment and storage medium | |
CN109978889A (en) | Image processing method, system, device, storage medium and blackboard device | |
CN108921834A (en) | A kind of human body foreground detection system | |
CN114119408A (en) | Express delivery detection method and device based on cat eye camera and cat eye camera | |
CN108960253A (en) | A kind of object detection system | |
CN108846980A (en) | A kind of monitoring and alarming system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WW01 | Invention patent application withdrawn after publication | ||
WW01 | Invention patent application withdrawn after publication |
Application publication date: 20181113 |