CN108805822B - Twin-stage data cloud calculation and analysis methods - Google Patents
Twin-stage data cloud calculation and analysis methods Download PDFInfo
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- CN108805822B CN108805822B CN201810275194.4A CN201810275194A CN108805822B CN 108805822 B CN108805822 B CN 108805822B CN 201810275194 A CN201810275194 A CN 201810275194A CN 108805822 B CN108805822 B CN 108805822B
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- 238000004458 analytical method Methods 0.000 title claims abstract description 34
- 238000004364 calculation method Methods 0.000 title claims abstract description 24
- 238000007789 sealing Methods 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims abstract description 7
- 238000012545 processing Methods 0.000 claims description 56
- 238000009499 grossing Methods 0.000 claims description 38
- 239000012634 fragment Substances 0.000 claims description 23
- 238000001514 detection method Methods 0.000 claims description 13
- 238000003707 image sharpening Methods 0.000 claims description 10
- 238000013481 data capture Methods 0.000 claims description 8
- 238000011065 in-situ storage Methods 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 description 4
- 230000007246 mechanism Effects 0.000 description 4
- 238000010191 image analysis Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 1
- 238000009412 basement excavation Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
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- DMBHHRLKUKUOEG-UHFFFAOYSA-N diphenylamine Chemical compound C=1C=CC=CC=1NC1=CC=CC=C1 DMBHHRLKUKUOEG-UHFFFAOYSA-N 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20182—Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
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- Engineering & Computer Science (AREA)
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- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Image Processing (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
The present invention relates to a kind of twin-stage data cloud calculation and analysis methods, the method includes use twin-stage data cloud Calculation and Analysis Platform with the bounce of the sealing surface based on elastic force acquisition collected, from train the car door of equipment judge Train door currently whether trapping human.By means of the invention it is possible to which the accident for effectively detecting Train door trapping human occurs.
Description
Technical field
The present invention relates to field of cloud calculation more particularly to a kind of twin-stage data cloud calculation and analysis methods.
Background technique
Technically, big data is inseparable just as the front and back sides of one piece of coin with the relationship of cloud computing.Big number
According to can not necessarily be handled with the computer of separate unit, it is necessary to use distributed computing architecture.Its characteristic is to magnanimity number
According to excavation, but it must rely on distributed treatment, distributed data base, cloud storage and the virtualization technology of cloud computing.
Cloud computing can consider the service including following level: infrastructure services (IaaS), and platform services
(PaaS) and software services (SaaS).
Summary of the invention
To solve the above-mentioned problems, the present invention provides a kind of twin-stage data cloud calculation and analysis methods, to live image
On the basis of data accurately parse, the image analysis of Train door trapping human is carried out only for non-flaw image, simultaneously also
More direct elastic force analysis mechanisms are introduced, to improve the judgement accuracy and speed of Train door trapping human.
The present invention at least has following important inventive point:
(1) in order to improve the validity of flaw image detection, image to be processed is carried out based on image sharpening degree first
Smoothing processing, it is later determined that it is each it is smooth after in image multiple images fragment deviation, with determination it is each it is smooth after image
It whether is flaw image;
(2) elastic force acquisition equipment and each image processing equipment are referred to, the twin-stage of image analysis, elastic force analysis is established
Analysis mechanisms improve the detection accuracy of Train door trapping human and the security level of train.
According to an aspect of the present invention, a kind of twin-stage data cloud calculation and analysis methods are provided, the method includes using
Twin-stage data cloud Calculation and Analysis Platform is with the rebound of the sealing surface based on elastic force acquisition collected, from train the car door of equipment
Power judge Train door currently whether trapping human, the twin-stage data cloud Calculation and Analysis Platform includes:
Car door data capture device, is arranged in the compartment of train and close to door position, for the door position
High-definition image capture is carried out, to obtain and export image around continuous multiple car doors;
Car door detection device, setting beyond the clouds, are connect with the car door data capture device, for obtaining the car door week
Image is enclosed, based on car door upper limit gray threshold and car door lower limit gray threshold from obtaining car door region around the car door in image
Pattern, and export the car door zone map;
Skin analysis equipment is connect with the car door detection device, for receiving the car door zone map, is based on personnel
Colour of skin characteristics of image parses colour of skin subregion from the car door zone map, and exports the colour of skin subregion;
Embedded processing equipment is connect with the skin analysis equipment, for receiving the colour of skin subregion, and is being formed
When the sum of the pixel of the colour of skin subregion is more than or equal to default limitation, accidentally folder pre-warning signal is issued;
Smoothing processing equipment executes base to image around each car door for receiving image around the multiple car door
In the smoothing processing of image sharpening degree, to obtain the corresponding smoothing processing image of image around each car door;Wherein, to every
Around one car door image execute the smoothing processing based on image sharpening degree include: around car door image sharpening degree it is higher,
The smoothing processing intensity executed to image around car door is bigger;
Flaw positioning device is connect with the smoothing processing equipment, for receiving the multiple smoothing processing image, to every
One smoothing processing image executes the image dividing processing of same size piecemeal, corresponding to obtain each smoothing processing image
Multiple images fragment;It is also used to execute each smoothing processing image following processing: determining wherein each images fragment
The sum of mean value of the H channel value of each pixel, channel S value and channel B value is determined using the characteristic value as the images fragment
The absolute value of the difference of the characteristic value and surrounding images fragment characteristic value mean value of each images fragment is using as the images fragment
Deviation;And the flaw positioning device is when there are the deviations of the images fragment of a certain position in the smoothing processing image
When value is more than or equal to predetermined deviation threshold value, determine that image is flaw image around the corresponding car door of the smoothing processing image.
Specific embodiment
Embodiment of the present invention will be described in detail below.
Under system normal operation mode, train arrival and when being parked in the error range of permission, screen door is connect
The switch of dodge gate is controlled after by signal system command or train operator's confirmation.
On the one hand, under opening door operation, after train dwelling, in train stopping position allowed band, train operator to
After signal system issues opening Train door instruction, system issues door open command by shield door main controller, and door machine controller connects
After receiving door opening command, the operation such as unlock, enabling is executed.
On the other hand, under door-closing operation, when train preparation is dispatched a car, signal system receives driver and closes train door instruction
Afterwards, automatic shield door main controller issues door close commands, executes the operation such as shutdown, locking.After the closing of all shield doors, to signal
System issues all signals for closing locking, allows train departure.Driver confirms that all shield doors do not press from both sides people and press from both sides object, all close
In the case where closing, dispatch a car leaving from station.
In the prior art, lack direct, the effective judgment model to Train door trapping human, so that relevant operation is still
It needs to carry out using the collaboration of a variety of judgment models, the error of judgement and time are stretched, it is easy to delay rescue opportunity.
In order to overcome above-mentioned deficiency, the present invention has built a kind of twin-stage data cloud calculation and analysis methods, the method includes
Using twin-stage data cloud Calculation and Analysis Platform with the sealing surface based on elastic force acquisition collected, from train the car door of equipment
Bounce judge Train door currently whether trapping human, the twin-stage data cloud Calculation and Analysis Platform make Train door press from both sides people
The detection speed of accident gets a promotion.
Twin-stage data cloud Calculation and Analysis Platform according to embodiments of the present invention includes:
Car door data capture device, is arranged in the compartment of train and close to door position, for the door position
High-definition image capture is carried out, to obtain and export image around continuous multiple car doors;
Car door detection device, setting beyond the clouds, are connect with the car door data capture device, for obtaining the car door week
Image is enclosed, based on car door upper limit gray threshold and car door lower limit gray threshold from obtaining car door region around the car door in image
Pattern, and export the car door zone map;
Skin analysis equipment is connect with the car door detection device, for receiving the car door zone map, is based on personnel
Colour of skin characteristics of image parses colour of skin subregion from the car door zone map, and exports the colour of skin subregion;
Embedded processing equipment is connect with the skin analysis equipment, for receiving the colour of skin subregion, and is being formed
When the sum of the pixel of the colour of skin subregion is more than or equal to default limitation, accidentally folder pre-warning signal is issued.
Then, continue that the specific structure of twin-stage data cloud Calculation and Analysis Platform of the invention is further detailed.
Can also include: in the twin-stage data cloud Calculation and Analysis Platform
Smoothing processing equipment executes base to image around each car door for receiving image around the multiple car door
In the smoothing processing of image sharpening degree, to obtain the corresponding smoothing processing image of image around each car door;Wherein, to every
Around one car door image execute the smoothing processing based on image sharpening degree include: around car door image sharpening degree it is higher,
The smoothing processing intensity executed to image around car door is bigger;
Flaw positioning device is connect with the smoothing processing equipment, for receiving the multiple smoothing processing image, to every
One smoothing processing image executes the image dividing processing of same size piecemeal, corresponding to obtain each smoothing processing image
Multiple images fragment;It is also used to execute each smoothing processing image following processing: determining wherein each images fragment
The sum of mean value of the H channel value of each pixel, channel S value and channel B value is determined using the characteristic value as the images fragment
The absolute value of the difference of the characteristic value and surrounding images fragment characteristic value mean value of each images fragment is using as the images fragment
Deviation;And the flaw positioning device is when there are the deviations of the images fragment of a certain position in the smoothing processing image
When value is more than or equal to predetermined deviation threshold value, determine that image is flaw image around the corresponding car door of the smoothing processing image;
Image eliminating equipment is connect with the car door data capture device and the flaw positioning device respectively, for from
Go each image obtained after flaw image unless each defeated as multiple high-quality monitoring images around the multiple car door in image
Out;
Elastic force acquires equipment, is arranged on the sealing surface of the car door of train, connect, be used for the embedded processing equipment
When receiving the accidentally folder pre-warning signal, the bounce of the sealing surface of the car door from train is acquired, is rebounded based on collecting
Power numerical value judges that the received bounce of the sealing surface of the car door of train is the car door that composition train is also come from from human body
The rubber bodies of sealing surface, correspondingly to send human body rebound signal or rubber rebound signal;
State switching equipment is connect with elastic force acquisition equipment, for controlling when receiving the human body rebound signal
Make the train and integrally enter on the alert, be also used to receiving rubber rebound signal, control the train it is whole into
Enter conventional sense;
Braking equipment is connect with the state switching equipment, stuck for when the train integrally enters on the alert
The driving wheel of the train is to keep in situ, being also used to release when the train integrally enters conventional sense the train
Put the driving wheel of the train;
The front end of the train is arranged in instrument display panel, acquires respectively with the embedded processing equipment, the elastic force
Equipment and the state switching equipment, for distinguish embedded processing equipment described in real-time display, the elastic force acquisition equipment and
The output data of the state switching equipment.
Can also include: in the twin-stage data cloud Calculation and Analysis Platform
Reversed pushing equipment is connect with elastic force acquisition equipment, for when the train integrally enters on the alert,
The reversed car door for pushing train is also used to opening car door when the train integrally enters conventional sense, is stopped to train
The reversed promotion of car door.
In the twin-stage data cloud Calculation and Analysis Platform:
In the car door detection device, car door upper limit gray threshold and car door lower limit gray threshold are based on from the car door
In surrounding image obtain car door zone map include: by around the car door in image gray value in the car door upper limit gray scale threshold
Pixel between value and the car door lower limit gray threshold is as car door pixel, the pattern that the car door pixel is formed
The car door zone map is obtained after being fitted.
And in the twin-stage data cloud Calculation and Analysis Platform:
The embedded processing equipment is also used to be less than in the sum for forming the pixel of the colour of skin subregion and limit in advance
When amount, issues and close pass signal.
In addition, the twin-stage data cloud Calculation and Analysis Platform can also include satellite navigation, the vehicle of train is set
In compartment and close to door position, the current navigation position in the compartment for providing train.
Satellite navigation (Satellite navigation) refers to using navigation satellite to ground, ocean, aerial and space
The technology of user's progress navigator fix.Common GPS navigation, the Big Dipper navigation etc. is satellite navigation.
The technology of navigator fix is carried out to ground, ocean, aerial and spatial user using navigation satellite.Utilize the sun, the moon
Ball and other natural coelonavigations have thousands of years of history, although by artificial object navigation imagination early in latter half in 19th century just
It has been proposed that but just starting to realize until the 1960s.The U.S. in 1964 builds up " meridian instrument " satellite navigation system, and hands over
It pays naval to use, start within 1967 civilian.Start within 1973 to develop " nautical star " global positioning system again.The Soviet Union also establishes class
As satellite navigation system.France, Japan, the Chinese research and experiment work for also having carried out satellite navigation.Satellite navigation is comprehensive
The advantages of conventional navigation systems, is truly realized under various weather conditions global high-precision passive type navigator fix.Especially
Time measurlng range satellite navigation system can not only provide the whole world and the covering of terrestrial space continuous stereo, high-precision three-dimensional positioning and survey
Speed, and strong antijamming capability.
Using twin-stage data cloud Calculation and Analysis Platform of the invention, for shortage Train door trapping human in the prior art
Fast detection mechanism the technical issues of, in order to improve the validity of flaw image detection, first to image to be processed carry out base
In the smoothing processing of image sharpening degree, it is later determined that it is each it is smooth after in image multiple images fragment deviation, with determination
Whether each smooth rear image is flaw image, particular, it is important that also referring to elastic force acquisition equipment and each image procossing
Equipment establishes the twin-stage analysis mechanisms of image analysis, elastic force analysis, to efficiently solve above-mentioned technical problem.
It is understood that although the present invention has been disclosed in the preferred embodiments as above, above-described embodiment not to
Limit the present invention.For any person skilled in the art, without departing from the scope of the technical proposal of the invention,
Many possible changes and modifications all are made to technical solution of the present invention using the technology contents of the disclosure above, or are revised as
With the equivalent embodiment of variation.Therefore, anything that does not depart from the technical scheme of the invention are right according to the technical essence of the invention
Any simple modifications, equivalents, and modifications made for any of the above embodiments still fall within the range of technical solution of the present invention protection
It is interior.
Claims (3)
1. a kind of twin-stage data cloud calculation and analysis methods, the method includes using twin-stage data cloud Calculation and Analysis Platform to be based on
The bounce of the sealing surface of elastic force acquisition collected, from train the car door of equipment judges whether Train door currently clamps people
Body, which is characterized in that the twin-stage data cloud Calculation and Analysis Platform includes:
Car door data capture device, is arranged in the compartment of train and close to door position, for carrying out to the door position
High-definition image capture, to obtain and export image around continuous multiple car doors;
Car door detection device, setting beyond the clouds, connect with the car door data capture device, scheme around the car door for obtaining
Picture, based on car door upper limit gray threshold and car door lower limit gray threshold from obtaining car door administrative division map around the car door in image
Case, and export the car door zone map;
Skin analysis equipment is connect with the car door detection device, for receiving the car door zone map, is based on personnel's colour of skin
Characteristics of image parses colour of skin subregion from the car door zone map, and exports the colour of skin subregion;
Embedded processing equipment is connect with the skin analysis equipment, for receiving the colour of skin subregion, and described in the composition
When the sum of the pixel of colour of skin subregion is more than or equal to default limitation, accidentally folder pre-warning signal is issued;
Smoothing processing equipment executes based on figure image around each car door for receiving image around the multiple car door
As the smoothing processing of sharpness, to obtain the corresponding smoothing processing image of image around each car door;Wherein, to each
Around car door image execute the smoothing processing based on image sharpening degree include: around car door image sharpening degree it is higher, to vehicle
The smoothing processing intensity that door surrounding image executes is bigger;
Flaw positioning device is connect with the smoothing processing equipment, for receiving the multiple smoothing processing image, to each
Smoothing processing image executes the image dividing processing of same size piecemeal, corresponding multiple to obtain each smoothing processing image
Images fragment;It is also used to execute each smoothing processing image following processing: determining each of wherein each images fragment
The sum of mean value of the H channel value of pixel, channel S value and channel B value is using the characteristic value as the images fragment, and determination is each
The absolute value of the characteristic value of a images fragment and the difference of surrounding images fragment characteristic value mean value is using as the inclined of the images fragment
Difference;And the flaw positioning device is when there are the deviation of the images fragment of a certain position is big in the smoothing processing image
When being equal to predetermined deviation threshold value, determine that image is flaw image around the corresponding car door of the smoothing processing image;
Image eliminating equipment is connect with the car door data capture device and the flaw positioning device respectively, is used for from described
The each image obtained after flaw image unless each is gone to export around multiple car doors as multiple high-quality monitoring images in image;
Elastic force acquires equipment, is arranged on the sealing surface of the car door of train, connect with the embedded processing equipment, for connecing
When receiving the accidentally folder pre-warning signal, the bounce of the sealing surface of the car door from train is acquired, based on collecting bounce number
Value judges that the received bounce of the sealing surface of the car door of train is that the closing of the car door of composition train is also come from from human body
The rubber bodies in face, correspondingly to send human body rebound signal or rubber rebound signal;
State switching equipment is connect with elastic force acquisition equipment, for controlling institute when receiving the human body rebound signal
It states train and integrally enters on the alert, be also used to receiving rubber rebound signal, control the train and integrally enter often
Rule state;
Braking equipment is connect with the state switching equipment, stuck described for when the train integrally enters on the alert
The driving wheel of train discharges institute to keep in situ, being also used to when the train integrally enters conventional sense the train
State the driving wheel of train;
The front end of the train is arranged in instrument display panel, acquires equipment with the embedded processing equipment, the elastic force respectively
With the state switching equipment, for distinguishing embedded processing equipment described in real-time display, the elastic force acquires equipment and described
The output data of state switching equipment;
In the car door detection device, based on car door upper limit gray threshold and car door lower limit gray threshold around the car door
Obtained in image car door zone map include: by around the car door in image gray value in the car door upper limit gray threshold and
Pixel between the car door lower limit gray threshold carries out the pattern of car door pixel composition as car door pixel
The car door zone map is obtained after fitting.
2. the method as described in claim 1, which is characterized in that the platform further include:
Reversed pushing equipment is connect, for when the train integrally enters on the alert, reversely with elastic force acquisition equipment
It pushes the car door of train to open car door, is also used to when the train integrally enters conventional sense, stop the car door to train
Reversed promotion.
3. method according to claim 2, it is characterised in that:
The embedded processing equipment is also used to when forming the sum of pixel of the colour of skin subregion less than default limitation,
It issues and closes pass signal.
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