CN107194955A - Adaptive big data management method - Google Patents
Adaptive big data management method Download PDFInfo
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- CN107194955A CN107194955A CN201710470471.2A CN201710470471A CN107194955A CN 107194955 A CN107194955 A CN 107194955A CN 201710470471 A CN201710470471 A CN 201710470471A CN 107194955 A CN107194955 A CN 107194955A
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Abstract
The present invention relates to a kind of adaptive big data management method, including：Outdoor scene image capture is carried out to window outer scene, to obtain outdoor scene image；The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis result；The analysis result is received, different filtering strategies are performed to the outdoor scene image based on the analysis result, and export filtered image；The filtered image is received, the personage the track whether analysis of personage's track detection belongs to dangerous person with the personage track judged in the filtered image is performed to the filtered image；When personage track in the filtered image belongs to the personage track of dangerous person, automatic window-closing operation is performed to window.
Description
Technical field
The present invention relates to switch control field, more particularly to a kind of adaptive big data management method.
Background technology
Building, i.e. building, mansion, for literal meaning, building refer to tall and big building construction.Each building are all integrated
Multiple windows carry out building structure constructions.Window refers to the hole built on wall or roof on architecture, to make light
Or air is got in.Can bidirectional opening modern window by window frame, middle transparent part and movable part (hinge, handle,
Pulley etc.) three parts composition.Window frame is responsible for supporting the main structure of forms, can be timber, metal, ceramics or plastic material, thoroughly
Bright part is attached on window frame, can be paper, cloth, silk or glass material.Movable part is main based on metal material, in people
The place that hand is touched may also be wrapped up with heat-insulating materials such as plastics.
In the prior art, in order to prevent a bad actor from being got in from window, indoor occupant is damaged or property is made
Into loss, the people of lowrise layer typically install the strick precaution that burglary-resisting window carries out a bad actor additional, so, on the one hand add economy
Cost, on the other hand causes limited view, while being adversely affected to housing appearance.
The content of the invention
In order to solve the above problems, the invention provides a kind of adaptive big data management method, image can be performed
Personage's track detection analyzes the personage track for whether belonging to dangerous person with the personage track judged in described image, in the figure
When personage track as in belongs to the personage track of dangerous person, automatic window-closing operation is performed to window, it is even more important that also
Having used includes the image capture device of multiple photoelectric conversion units in parallel, and the analysis for the personage track of dangerous person is provided
The view data of fine definition.
According to an aspect of the present invention there is provided a kind of adaptive big data management method, methods described includes：
Outdoor scene image capture is carried out to window outer scene, to obtain outdoor scene image；
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis knot
Really；
The analysis result is received, different filtering plans are performed to the outdoor scene image based on the analysis result
Omit, and export filtered image；
The filtered image is received, the analysis of personage's track detection is performed to the filtered image to judge the filtering
Whether the personage track in image belongs to the personage track of dangerous person afterwards；
When personage track in the filtered image belongs to the personage track of dangerous person, automatic close is performed to window
Window is operated.
More specifically, in the adaptive big data management method, in addition to：
The current state of window is detected to judge that window is in closed state or is not turned off state；
Wherein, when the personage track in the filtered image belongs to the personage track of dangerous person, window is performed
Automatic window-closing operation includes：When it is to be in closed state to judge window, stop operating the automatic window-closing that window is performed.
More specifically, in the adaptive big data management method, in addition to：
When personage track in the filtered image belongs to the personage track of dangerous person, broadcasting connects with dangerous person
The corresponding audio alert file of nearly window；
When personage track in the filtered image belongs to the personage track of dangerous person, it will be approached with dangerous person
The position of the corresponding text information of window and window is together sent on the mobile terminal that householder holds.
More specifically, in the adaptive big data management method：
Outdoor scene image capture is carried out to window outer scene, included with obtaining outdoor scene image：
Using the sub- equipment of the light-intensity test being arranged on window housing, detect the irradiation luminous intensity outside window to export
Real-time lighting intensity
Sub- equipment is detected using light intensity rate of change, is connected with the sub- equipment of the light-intensity test, for detecting that real-time lighting is strong
The rate of change of degree, when the rate of change of real-time lighting intensity is more than or equal to default rate of change threshold value, sends rate of change and crosses high RST,
Otherwise, rate of change normal signal is sent；
Using the sub- equipment of the adaptive sensing being arranged on window housing, detect that sub- equipment is connected with light intensity rate of change,
For carrying out outdoor scene image capture to window outer scene, to obtain outdoor scene image；Adaptive sensing is set
It is standby to include pixel data readout equipment and each pixel data obtains equipment, each pixel data obtain equipment include it is multiple simultaneously
The photoelectric conversion unit of connection, when receiving the rate of change normal signal, each pixel data obtains equipment only using many
Data that a photoelectric conversion unit in individual photoelectric conversion unit in parallel is sensed and output, when receiving the rate of change
When crossing high RST, each pixel data obtains equipment and merges the data that multiple photoelectric conversion units in parallel are sensed
After export, the pixel data readout equipment respectively with each pixel data obtain equipment be connected, for reading each picture respectively
The data of plain data acquisition facility output constitute the outdoor field using the pixel value as each pixel, the pixel value of each pixel
Scape image；
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis knot
Fruit includes：
Using the first sub- equipment of image initial survey, for receiving the outdoor scene image, based on each of outdoor scene image
The pixel value of individual pixel determines the mean square deviation of outdoor scene image pixel value to be exported as target mean square error；
Using the second sub- equipment of image initial survey, for receiving outdoor scene image, noise point is carried out to outdoor scene image
Analysis, to obtain the maximum main noise signal of noise amplitude and the big secondary noise signal of noise amplitude time, based on main noise signal, secondary
Noise signal and outdoor scene image determine the signal to noise ratio of outdoor scene image to be exported as target signal to noise ratio；
The analysis result is received, different filtering plans are performed to the outdoor scene image based on the analysis result
Omiting, and export filtered image includes：
Using the first sub- equipment of filtering, for performing following filtering process：Length is used for 6 to the image received
HARR wavelet basis carries out 5 grades of decomposition and lays equal stress on structure to obtain the filtering image of the sub- equipment output of the first filtering；
Using the second sub- equipment of filtering, for performing following filtering process：For each pixel of the image received,
Use various filter windows to carry out the acquisition of corresponding various block of pixels centered on the pixel to the pixel, determine each picture
Gray value variance in plain block, the minimum corresponding filter window of selection gray value variance is as target filter window to the pixel
Pixel value carries out medium filtering to obtain its filtered pixel value, and the filtered pixel value of all pixels based on the image received is obtained
Take the filtering image of the sub- equipment output of the second filtering；
Using the sub- equipment of adaptive recursive filtering, for performing following filtering process：The image received is carried out adaptive
Recursive filtering processing is answered to obtain the filtering image of the sub- equipment output of adaptive recursive filtering；
Using adaptively selected sub- equipment, respectively with the sub- equipment of adaptive recursive filtering, the first sub- equipment of filtering, the second filter
Marble equipment, the first sub- equipment of image initial survey and the sub- equipment connection of the second image initial survey, for receiving target mean square error and mesh
Mark signal to noise ratio, and be less than or equal to default snr threshold in target signal to noise ratio and target mean square error is more than or equal to default mean square deviation threshold
During value, perform filtering process to outdoor scene image to be located using the first sub- equipment of filtering and the second sub- equipment of filtering successively
Image is managed, when target signal to noise ratio is less than or equal to default snr threshold and target mean square error is more than default mean deviation threshold, is made
Filtering process is performed to outdoor scene image to obtain processing image with the second sub- equipment of filtering, is more than in target signal to noise ratio default
When snr threshold and target mean square error are more than or equal to default mean deviation threshold, using the first sub- equipment of filtering to outdoor scene figure
As performing filtering process to obtain processing image, it is more than default snr threshold in target signal to noise ratio and target mean square error is less than pre-
If during mean deviation threshold, performing filtering process to outdoor scene image to obtain processing figure using the sub- equipment of adaptive recursive filtering
Picture；
Wherein, the filtered image is received, the analysis of personage's track detection is performed to the filtered image to judge
Stating the personage track in filtered image and whether belonging to the personage track of dangerous person includes：The processing image is received, to institute
State processing image and perform whether the analysis of personage's track detection belongs to dangerous people with the personage track judged in the filtered image
The personage track of thing.
More specifically, in the adaptive big data management method, in addition to：Prestore default snr threshold and
Default mean deviation threshold.
More specifically, in the adaptive big data management method：
Perform the analysis of personage's track detection to the processing image is with the personage track judged in the filtered image
The no personage track for belonging to dangerous person includes：Personage's rail is performed to the processing image based on dangerous person's baseline locomotor track
Mark tests and analyzes the personage track for whether belonging to dangerous person with the personage track judged in the filtered image.
Brief description of the drawings
Embodiment of the present invention is described below with reference to accompanying drawing, wherein：
Fig. 1 is the block diagram of the adaptive window switching tube platform according to embodiment of the present invention.
Fig. 2 is the step flow chart of the adaptive big data management method according to embodiment of the present invention.
Reference：1 image capture device；2 image analysis equipments；3 filtering selection equipment；4 personage's track detection equipment；
5 automatic window-closing equipment；S101 carries out outdoor scene image capture to window outer scene, to obtain outdoor scene image；S102
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis result；S103
The analysis result is received, different filtering strategies are performed to the outdoor scene image based on the analysis result, and export
Filtered image；S104 receives the filtered image, and the analysis of personage's track detection is performed to the filtered image to judge
Whether the personage track in the filtered image belongs to the personage track of dangerous person；S105 is in the filtered image
When personage track belongs to the personage track of dangerous person, automatic window-closing operation is performed to window
Embodiment
Embodiment of the present invention is described in detail below with reference to accompanying drawings.
The material of window, generally speaking, is divided into three major types：Wooden, plastic-steel, aluminium alloy.Three has his own strong points.
Plastic-steel：Because being plastic material, weight is small, and heat-proof quality is good, and price is relatively low.Because often
In face of exposing to wind and rain, the sun shines, so most allowing people to concern the anti-aging problem of plastic-steel window.In fact, the plastic-steel window of high-quality
Service life up to 100 years or so.
Aluminium alloy：Be not in problem of aging because being metal material, and it is firm, and impact resistance, intensity is big.But
The weakness that aluminum window is easiest to be attacked is exactly heat-proof quality, because metal is the good conductor of heat, extraneous and indoor
Temperature can be transmitted with the framework of window.
But it is worth query, the ratio on a fan window shared by framework is simultaneously not very big, and window is not one block of metal
Plate, but the glass of frame is inlayed, the heat transmitted by framework edge strip can be produced to the indoor temperature for having warmer, air-conditioning actually
Great influence
But that precautions averts perils is good, in order to prevent this problem, " bridge cut-off " skill is employed on the aluminium alloy window having
Art, i.e., add one layer of resin material in aluminum alloy window frame, thoroughly broken off the approach of heat conduction.
It is wooden：Comparatively, wooden should be forms framework material the most perfect, no matter from heat-insulated, sound insulation angularly
For have obvious advantage, and inherent texture and natural figure are more moving.It is actual although wooden
On have be used for do the solid wood of window frame and have already been through processing special layer by layer, not only without moisture, it is desirable to higher even
Fat is sucked, so, so-called wooden actually as fossil, solid wood after treatment is only protected
Stayed the appearance of timber, quality is but completely different, will not craze and transfiguration, less with worrying incident insect bite, be corroded, moreover,
Intensity is also greatly increased.
In addition, also a kind of frame structure is referred to as aluminium Bao Mu, the outdoor part of wood frame is one layer of aluminium alloy structure,
In fact, this is the advantage that thermal insulation is good and intensity of aluminum alloy is high for combining wood frame, integrates, maximize favourable factors and minimize unfavourable ones.
The wooden unique shortcoming of window is exactly that cost is too high.
Currently, lack the effective detection mechanism to a bad actor outside window, cause people to need burglary-resisting window to be installed or real-time
The observation to environment outside window and pedestrian is kept, no small financial burden or stress is brought.In order to overcome it is above-mentioned not
Foot, the present invention has built a kind of adaptive window switching tube platform and method, can solve the problem that above-mentioned technical problem.
Fig. 1 is the block diagram of the adaptive window switching tube platform according to embodiment of the present invention, described
Platform includes：
Image capture device, for carrying out outdoor scene image capture to window outer scene, to obtain outdoor scene figure
Picture；
Image analysis equipment, is connected with described image capture device, for receiving the outdoor scene image, and to described
Outdoor scene image carries out picture signal analysis to export analysis result；
Filtering selection equipment, is connected with described image analytical equipment, for receiving the analysis result, based on the analysis
As a result different filtering strategies are performed to the outdoor scene image, and export filtered image；
Personage's track detection equipment, is connected with the filtering selection equipment, for receiving the filtered image, to described
Filtered image performs whether the analysis of personage's track detection belongs to dangerous people with the personage track judged in the filtered image
The personage track of thing；
Automatic window-closing equipment, is connected with personage's track detection equipment, for the personage in the filtered image
When track belongs to the personage track of dangerous person, automatic window-closing operation is performed to window.
Then, continue that the concrete structure of the adaptive window switching tube platform of the present invention is further detailed.
It can also include in the adaptive window switching tube platform：
Window condition detecting device, for detecting the current state of window with judge window be in closed state or
It is not turned off state；
Wherein, the automatic window-closing equipment is also connected with the window condition detecting device, and the automatic window-closing equipment exists
When personage track in the filtered image belongs to the personage track of dangerous person, automatic window-closing operation is performed to window and is wrapped
Include：When it is to be in closed state to judge window, stop operating the automatic window-closing that window is performed.
It can also include in the adaptive window switching tube platform：
Audio alert equipment, is connected with the automatic window-closing equipment, for the personage track in the filtered image
When belonging to the personage track of dangerous person, play with dangerous person close to the corresponding audio alert file of window；
Wireless Telecom Equipment, is connected with the automatic window-closing equipment, for the personage track in the filtered image
When belonging to the personage track of dangerous person, by with dangerous person close to the position one of the corresponding text information of window and window
It is same to be sent on the mobile terminal that householder holds.
In the adaptive window switching tube platform：
Described image capture device includes：
The sub- equipment of light-intensity test, is arranged on window housing, for detecting the irradiation luminous intensity outside window to export
Real-time lighting intensity；
Light intensity rate of change detects sub- equipment, is connected with the sub- equipment of the light-intensity test, for detecting real-time lighting intensity
Rate of change, when the rate of change of real-time lighting intensity is more than or equal to default rate of change threshold value, sends rate of change and crosses high RST, no
Then, rate of change normal signal is sent；
The sub- equipment of adaptive sensing, is arranged on window housing, detects that sub- equipment is connected with light intensity rate of change, for pair
Window outer scene carries out outdoor scene image capture, to obtain outdoor scene image；The sub- equipment of adaptive sensing includes
Pixel data readout equipment and each pixel data obtain equipment, and each pixel data, which obtains equipment, includes multiple light in parallel
Electric converting unit, when receiving the rate of change normal signal, each pixel data obtains equipment and only uses multiple parallel connections
Photoelectric conversion unit in the data that are sensed of a photoelectric conversion unit and output, when receiving the too high letter of the rate of change
Number when, each pixel data obtain equipment the data that multiple photoelectric conversion units in parallel are sensed are merged it is rear defeated
Go out, the pixel data readout equipment obtains equipment with each pixel data respectively and is connected, for reading each pixel count respectively
According to the data of acquisition equipment output using the pixel value as each pixel, the pixel value of each pixel constitutes the outdoor scene figure
Picture；
Described image analytical equipment includes：
The first sub- equipment of image initial survey, for receiving the outdoor scene image, each picture based on outdoor scene image
The pixel value of vegetarian refreshments determines the mean square deviation of outdoor scene image pixel value to be exported as target mean square error；
The second sub- equipment of image initial survey, for receiving outdoor scene image, noise analysis is carried out to outdoor scene image, with
The maximum main noise signal of noise amplitude and the big secondary noise signal of noise amplitude time are obtained, based on main noise signal, secondary noise
Signal and outdoor scene image determine the signal to noise ratio of outdoor scene image to be exported as target signal to noise ratio；
The filtering selection equipment includes：
The first sub- equipment of filtering, for performing following filtering process：Use length small for 6 HARR to the image received
Ripple base carries out 5 grades of decomposition and lays equal stress on structure to obtain the filtering image of the sub- equipment output of the first filtering；
The second sub- equipment of filtering, for performing following filtering process：For each pixel of the image received, use
Various filter windows carry out the acquisition of corresponding various block of pixels to the pixel centered on the pixel, determine each block of pixels
In gray value variance, the minimum corresponding filter window of selection gray value variance is used as pixel of the target filter window to the pixel
Value carries out medium filtering to obtain its filtered pixel value, and the filtered pixel values of all pixels based on the image received obtains the
The filtering image of the sub- equipment output of two filtering；
The sub- equipment of adaptive recursive filtering, for performing following filtering process：The image received is adaptively passed
Return filtering process to obtain the filtering image of the sub- equipment output of adaptive recursive filtering；
Adaptively selected sub- equipment, respectively with the sub- equipment of adaptive recursive filtering, the first sub- equipment of filtering, the second filtering
Equipment, the first sub- equipment of image initial survey and the sub- equipment connection of the second image initial survey, for receiving target mean square error and target letter
Make an uproar ratio, and be less than or equal to default snr threshold in target signal to noise ratio and target mean square error is more than or equal to default mean deviation threshold
When, perform filtering process to outdoor scene image to be handled using the first sub- equipment of filtering and the second sub- equipment of filtering successively
Image, when target signal to noise ratio is less than or equal to default snr threshold and target mean square error is more than default mean deviation threshold, is used
The second sub- equipment of filtering performs filtering process to outdoor scene image to obtain processing image, is more than default letter in target signal to noise ratio
Make an uproar when being more than or equal to default mean deviation threshold than threshold value and target mean square error, using the first sub- equipment of filtering to outdoor scene image
Filtering process is performed to obtain processing image, is more than default snr threshold in target signal to noise ratio and target mean square error is less than default
During mean deviation threshold, perform filtering process to outdoor scene image to obtain processing figure using the sub- equipment of adaptive recursive filtering
Picture；
Wherein, personage's track detection equipment is connected with the adaptively selected sub- equipment, for receiving the processing
Image, performs whether the analysis of personage's track detection is belonged to the personage track judged in the filtered image to the processing image
In the personage track of dangerous person.
It can also include in the adaptive window switching tube platform：
Data storage device, is connected with the adaptively selected sub- equipment, for prestore default snr threshold and
Default mean deviation threshold.
In the adaptive window switching tube platform：
Personage's track detection equipment performs the analysis of personage's track detection to judge the filtering to the processing image
Whether the personage track in image belongs to the personage track of dangerous person and includes afterwards：Based on dangerous person's baseline locomotor track to institute
State processing image and perform whether the analysis of personage's track detection belongs to dangerous people with the personage track judged in the filtered image
The personage track of thing.
Fig. 2 is the step flow chart of the adaptive big data management method according to embodiment of the present invention, the side
Method includes：
Outdoor scene image capture is carried out to window outer scene, to obtain outdoor scene image；
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis knot
Really；
The analysis result is received, different filtering plans are performed to the outdoor scene image based on the analysis result
Omit, and export filtered image；
The filtered image is received, the analysis of personage's track detection is performed to the filtered image to judge the filtering
Whether the personage track in image belongs to the personage track of dangerous person afterwards；
When personage track in the filtered image belongs to the personage track of dangerous person, automatic close is performed to window
Window is operated.
Then, continue that the specific steps of the adaptive big data management method of the present invention are further detailed.
The adaptive big data management method can also include：
The current state of window is detected to judge that window is in closed state or is not turned off state；
Wherein, when the personage track in the filtered image belongs to the personage track of dangerous person, window is performed
Automatic window-closing operation includes：When it is to be in closed state to judge window, stop operating the automatic window-closing that window is performed.
The adaptive big data management method can also include：
When personage track in the filtered image belongs to the personage track of dangerous person, broadcasting connects with dangerous person
The corresponding audio alert file of nearly window；
When personage track in the filtered image belongs to the personage track of dangerous person, it will be approached with dangerous person
The position of the corresponding text information of window and window is together sent on the mobile terminal that householder holds.
In the adaptive big data management method：
Outdoor scene image capture is carried out to window outer scene, included with obtaining outdoor scene image：
Using the sub- equipment of the light-intensity test being arranged on window housing, detect the irradiation luminous intensity outside window to export
Real-time lighting intensity
Sub- equipment is detected using light intensity rate of change, is connected with the sub- equipment of the light-intensity test, for detecting that real-time lighting is strong
The rate of change of degree, when the rate of change of real-time lighting intensity is more than or equal to default rate of change threshold value, sends rate of change and crosses high RST,
Otherwise, rate of change normal signal is sent；
Using the sub- equipment of the adaptive sensing being arranged on window housing, detect that sub- equipment is connected with light intensity rate of change,
For carrying out outdoor scene image capture to window outer scene, to obtain outdoor scene image；Adaptive sensing is set
It is standby to include pixel data readout equipment and each pixel data obtains equipment, each pixel data obtain equipment include it is multiple simultaneously
The photoelectric conversion unit of connection, when receiving the rate of change normal signal, each pixel data obtains equipment only using many
Data that a photoelectric conversion unit in individual photoelectric conversion unit in parallel is sensed and output, when receiving the rate of change
When crossing high RST, each pixel data obtains equipment and merges the data that multiple photoelectric conversion units in parallel are sensed
After export, the pixel data readout equipment respectively with each pixel data obtain equipment be connected, for reading each picture respectively
The data of plain data acquisition facility output constitute the outdoor field using the pixel value as each pixel, the pixel value of each pixel
Scape image；
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis knot
Fruit includes：
Using the first sub- equipment of image initial survey, for receiving the outdoor scene image, based on each of outdoor scene image
The pixel value of individual pixel determines the mean square deviation of outdoor scene image pixel value to be exported as target mean square error；
Using the second sub- equipment of image initial survey, for receiving outdoor scene image, noise point is carried out to outdoor scene image
Analysis, to obtain the maximum main noise signal of noise amplitude and the big secondary noise signal of noise amplitude time, based on main noise signal, secondary
Noise signal and outdoor scene image determine the signal to noise ratio of outdoor scene image to be exported as target signal to noise ratio；
The analysis result is received, different filtering plans are performed to the outdoor scene image based on the analysis result
Omiting, and export filtered image includes：
Using the first sub- equipment of filtering, for performing following filtering process：Length is used for 6 to the image received
HARR wavelet basis carries out 5 grades of decomposition and lays equal stress on structure to obtain the filtering image of the sub- equipment output of the first filtering；
Using the second sub- equipment of filtering, for performing following filtering process：For each pixel of the image received,
Use various filter windows to carry out the acquisition of corresponding various block of pixels centered on the pixel to the pixel, determine each picture
Gray value variance in plain block, the minimum corresponding filter window of selection gray value variance is as target filter window to the pixel
Pixel value carries out medium filtering to obtain its filtered pixel value, and the filtered pixel value of all pixels based on the image received is obtained
Take the filtering image of the sub- equipment output of the second filtering；
Using the sub- equipment of adaptive recursive filtering, for performing following filtering process：The image received is carried out adaptive
Recursive filtering processing is answered to obtain the filtering image of the sub- equipment output of adaptive recursive filtering；
Using adaptively selected sub- equipment, respectively with the sub- equipment of adaptive recursive filtering, the first sub- equipment of filtering, the second filter
Marble equipment, the first sub- equipment of image initial survey and the sub- equipment connection of the second image initial survey, for receiving target mean square error and mesh
Mark signal to noise ratio, and be less than or equal to default snr threshold in target signal to noise ratio and target mean square error is more than or equal to default mean square deviation threshold
During value, perform filtering process to outdoor scene image to be located using the first sub- equipment of filtering and the second sub- equipment of filtering successively
Image is managed, when target signal to noise ratio is less than or equal to default snr threshold and target mean square error is more than default mean deviation threshold, is made
Filtering process is performed to outdoor scene image to obtain processing image with the second sub- equipment of filtering, is more than in target signal to noise ratio default
When snr threshold and target mean square error are more than or equal to default mean deviation threshold, using the first sub- equipment of filtering to outdoor scene figure
As performing filtering process to obtain processing image, it is more than default snr threshold in target signal to noise ratio and target mean square error is less than pre-
If during mean deviation threshold, performing filtering process to outdoor scene image to obtain processing figure using the sub- equipment of adaptive recursive filtering
Picture；
Wherein, the filtered image is received, the analysis of personage's track detection is performed to the filtered image to judge
Stating the personage track in filtered image and whether belonging to the personage track of dangerous person includes：The processing image is received, to institute
State processing image and perform whether the analysis of personage's track detection belongs to dangerous people with the personage track judged in the filtered image
The personage track of thing.
The adaptive big data management method can also include：Prestore default snr threshold and default mean square deviation
Threshold value.
In the adaptive big data management method：
Perform the analysis of personage's track detection to the processing image is with the personage track judged in the filtered image
The no personage track for belonging to dangerous person includes：Personage's rail is performed to the processing image based on dangerous person's baseline locomotor track
Mark tests and analyzes the personage track for whether belonging to dangerous person with the personage track judged in the filtered image.
In addition, the photoelectric conversion unit can be realized by cmos sensor or ccd sensor.Cmos image sensor is
A kind of typical solid state image sensor, has common historical origin with CCD.Cmos image sensor is generally by image-sensitive unit
Several portions such as array, line driver, row driver, time sequence control logic, AD converter, data/address bus output interface, control interface
It is grouped into, this several part is generally all integrated on same silicon chip.Its course of work generally can be divided into reset, opto-electronic conversion,
Integrate, read several parts.
Can be such as AD converter, automatic with other integrated digital signal processing circuits on cmos image sensor chip
Light exposure control, nonuniform compensation, white balance processing, black level control, Gamma correction etc., even can in order to carry out quick calculate
So that the DSP devices with programmable functions to be integrated with cmos device, so as to constitute at single-chip digital camera and image
Reason system.
Morrison in 1963, which has been delivered, can calculate sensor, and this is that one kind can determine facula position using photoconductive effect
Structure, as cmos image sensor develop beginning.The CMOS CMOS active pixel sensor single-chip digitals of nineteen ninety-five low noise
Camera succeeds.
Cmos image sensor has following advantage：1), random window reading capability.Window read operation is at random
Cmos image sensor is functionally better than CCD one side, and also referred to as area-of-interest is chosen.In addition, cmos image
The highly integrated characteristic of sensor is easily achieved it while opening the function of multiple tracking windows.2), capability of resistance to radiation.Total comes
Say, the potential radiation resistance of cmos image sensor has important enhancing relative to CCD performances.3), system complexity and can
By property.System hardware structure can be greatly simplified using cmos image sensor.4), non-destructive data read-out mode.5)、
The spectrum assignment of optimization.Significantly, since the reason for being integrated with multiple functional transistors in pixel structure, CMOS figures
As sensor, there is also some shortcomings, mainly noise and filling rate two indices.In view of cmos image sensor is relatively excellent
Performance more so that cmos image sensor is widely used in every field.
Using the adaptive window switching tube platform and method of the present invention, for being difficult in the prior art to outdoor dangerous
Molecule carry out effective detection technical problem, by introduce include the image capture device of multiple photoelectric conversion units in parallel with
The view data of fine definition is provided, the image processing equipment for introducing multiple customizations carries out special project to the view data of fine definition
Analysis is with the presence for the track for judging outdoor a bad actor, so that the implementation for automatic window-closing to take precautions against a bad actor provides important
Reference data.
Although it is understood that the present invention is disclosed as above with preferred embodiment, but above-described embodiment and being not used to
Limit the present invention.For any those skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible variations and modification are all 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 change.Therefore, every content without departing from technical solution of the present invention, the technical spirit pair according to the present invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments, still fall within the scope of technical solution of the present invention protection
It is interior.
Claims (6)
1. a kind of adaptive big data management method, it is characterised in that methods described includes：
Outdoor scene image capture is carried out to window outer scene, to obtain outdoor scene image；
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis result；
The analysis result is received, different filtering strategies are performed to the outdoor scene image based on the analysis result, and
Export filtered image；
The filtered image is received, the analysis of personage's track detection is performed to the filtered image to judge to scheme after the filtering
Whether the personage track as in belongs to the personage track of dangerous person；
When personage track in the filtered image belongs to the personage track of dangerous person, automatic window-closing behaviour is performed to window
Make.
2. adaptive big data management method as claimed in claim 1, it is characterised in that also include：
The current state of window is detected to judge that window is in closed state or is not turned off state；
Wherein, when the personage track in the filtered image belongs to the personage track of dangerous person, window is performed automatic
Closing window operation includes：When it is to be in closed state to judge window, stop operating the automatic window-closing that window is performed.
3. adaptive big data management method as claimed in claim 2, it is characterised in that also include：
When personage track in the filtered image belongs to the personage track of dangerous person, play with dangerous person close to window
The corresponding audio alert file in family；
, will be with dangerous person close to window when personage track in the filtered image belongs to the personage track of dangerous person
Corresponding text information and the position of window are together sent on the mobile terminal that householder holds.
4. adaptive big data management method as claimed in claim 3, it is characterised in that：
Outdoor scene image capture is carried out to window outer scene, included with obtaining outdoor scene image：
Using the sub- equipment of the light-intensity test being arranged on window housing, the irradiation luminous intensity outside detection window is real-time to export
Intensity of illumination
Sub- equipment is detected using light intensity rate of change, is connected with the sub- equipment of the light-intensity test, for detecting real-time lighting intensity
Rate of change, when the rate of change of real-time lighting intensity is more than or equal to default rate of change threshold value, sends rate of change and crosses high RST, no
Then, rate of change normal signal is sent；
Using the sub- equipment of the adaptive sensing being arranged on window housing, detect that sub- equipment is connected with light intensity rate of change, be used for
Outdoor scene image capture is carried out to window outer scene, to obtain outdoor scene image；The sub- equipment bag of adaptive sensing
Include pixel data readout equipment and each pixel data obtains equipment, each pixel data obtains equipment including multiple in parallel
Photoelectric conversion unit, when receiving the rate of change normal signal, each pixel data obtain equipment only using it is multiple simultaneously
Data that a photoelectric conversion unit in the photoelectric conversion unit of connection is sensed and output, when receiving, the rate of change is too high
During signal, each pixel data acquisition equipment merges the data that multiple photoelectric conversion units in parallel are sensed rear defeated
Go out, the pixel data readout equipment obtains equipment with each pixel data respectively and is connected, for reading each pixel count respectively
According to the data of acquisition equipment output using the pixel value as each pixel, the pixel value of each pixel constitutes the outdoor scene figure
Picture；
The outdoor scene image is received, and carries out picture signal analysis to the outdoor scene image to export analysis result bag
Include：
Use the first sub- equipment of image initial survey, for receiving the outdoor scene image, each picture based on outdoor scene image
The pixel value of vegetarian refreshments determines the mean square deviation of outdoor scene image pixel value to be exported as target mean square error；
Using the second sub- equipment of image initial survey, for receiving outdoor scene image, noise analysis is carried out to outdoor scene image, with
The maximum main noise signal of noise amplitude and the big secondary noise signal of noise amplitude time are obtained, based on main noise signal, secondary noise
Signal and outdoor scene image determine the signal to noise ratio of outdoor scene image to be exported as target signal to noise ratio；
The analysis result is received, different filtering strategies are performed to the outdoor scene image based on the analysis result, and
Output filtered image includes：
Using the first sub- equipment of filtering, for performing following filtering process：Use length small for 6 HARR to the image received
Ripple base carries out 5 grades of decomposition and lays equal stress on structure to obtain the filtering image of the sub- equipment output of the first filtering；
Using the second sub- equipment of filtering, for performing following filtering process：For each pixel of the image received, use
Various filter windows carry out the acquisition of corresponding various block of pixels to the pixel centered on the pixel, determine each block of pixels
In gray value variance, the minimum corresponding filter window of selection gray value variance is used as pixel of the target filter window to the pixel
Value carries out medium filtering to obtain its filtered pixel value, and the filtered pixel values of all pixels based on the image received obtains the
The filtering image of the sub- equipment output of two filtering；
Using the sub- equipment of adaptive recursive filtering, for performing following filtering process：The image received is adaptively passed
Return filtering process to obtain the filtering image of the sub- equipment output of adaptive recursive filtering；
Using adaptively selected sub- equipment, respectively with the sub- equipment of adaptive recursive filtering, the first sub- equipment of filtering, the second filtering
Equipment, the first sub- equipment of image initial survey and the sub- equipment connection of the second image initial survey, for receiving target mean square error and target letter
Make an uproar ratio, and be less than or equal to default snr threshold in target signal to noise ratio and target mean square error is more than or equal to default mean deviation threshold
When, perform filtering process to outdoor scene image to be handled using the first sub- equipment of filtering and the second sub- equipment of filtering successively
Image, when target signal to noise ratio is less than or equal to default snr threshold and target mean square error is more than default mean deviation threshold, is used
The second sub- equipment of filtering performs filtering process to outdoor scene image to obtain processing image, is more than default letter in target signal to noise ratio
Make an uproar when being more than or equal to default mean deviation threshold than threshold value and target mean square error, using the first sub- equipment of filtering to outdoor scene image
Filtering process is performed to obtain processing image, is more than default snr threshold in target signal to noise ratio and target mean square error is less than default
During mean deviation threshold, perform filtering process to outdoor scene image to obtain processing figure using the sub- equipment of adaptive recursive filtering
Picture；
Wherein, the filtered image is received, the analysis of personage's track detection is performed to the filtered image to judge the filter
The personage track whether the personage track after ripple in image belongs to dangerous person includes：The processing image is received, to the place
Reason image performs whether the analysis of personage's track detection belongs to dangerous person's with the personage track judged in the filtered image
Personage track.
5. adaptive big data management method as claimed in claim 4, it is characterised in that also include：
Prestore default snr threshold and default mean deviation threshold.
6. adaptive big data management method as claimed in claim 5, it is characterised in that：
Whether the analysis of personage's track detection is belonged to the personage track judged in the filtered image is performed to the processing image
Include in the personage track of dangerous person：Personage track is performed based on dangerous person's baseline locomotor track to the processing image to examine
Survey the personage track whether analysis belongs to dangerous person with the personage track judged in the filtered image.
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