CN110407045A - A kind of method and Intelligent lift system showing elevator interior personnel distributed intelligence - Google Patents
A kind of method and Intelligent lift system showing elevator interior personnel distributed intelligence Download PDFInfo
- Publication number
- CN110407045A CN110407045A CN201910704007.4A CN201910704007A CN110407045A CN 110407045 A CN110407045 A CN 110407045A CN 201910704007 A CN201910704007 A CN 201910704007A CN 110407045 A CN110407045 A CN 110407045A
- Authority
- CN
- China
- Prior art keywords
- image
- elevator
- personnel
- value
- distributed intelligence
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 239000002245 particle Substances 0.000 claims abstract description 31
- 238000001914 filtration Methods 0.000 claims description 22
- 238000002790 cross-validation Methods 0.000 claims description 19
- 238000012545 processing Methods 0.000 claims description 15
- 238000006243 chemical reaction Methods 0.000 claims description 13
- 230000005540 biological transmission Effects 0.000 claims description 12
- 238000004891 communication Methods 0.000 claims description 11
- 238000003708 edge detection Methods 0.000 claims description 11
- 230000009466 transformation Effects 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 9
- 230000002452 interceptive effect Effects 0.000 claims description 7
- 238000004804 winding Methods 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 6
- 230000010354 integration Effects 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 238000000354 decomposition reaction Methods 0.000 claims description 4
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 2
- 238000005070 sampling Methods 0.000 abstract description 3
- 230000003044 adaptive effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000005611 electricity Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B1/00—Control systems of elevators in general
- B66B1/34—Details, e.g. call counting devices, data transmission from car to control system, devices giving information to the control system
- B66B1/3476—Load weighing or car passenger counting devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B3/00—Applications of devices for indicating or signalling operating conditions of elevators
- B66B3/002—Indicators
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B2201/00—Aspects of control systems of elevators
- B66B2201/20—Details of the evaluation method for the allocation of a call to an elevator car
- B66B2201/222—Taking into account the number of passengers present in the elevator car to be allocated
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Mechanical Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
Abstract
The present invention relates to a kind of methods and Intelligent lift system for showing elevator interior personnel distributed intelligence, by the inner tip in elevator case, multiple industrial cameras are set, industrial camera is taken pictures sampling with preset frequency, each frame picture all respectively by noise reduction, the mode extracted edge contour, convert particle, is eventually displayed on display screen.When people are in awaiting elevator, in real time and it can be visually observed that personnel's distribution situation of current elevator interior, these personnel's distribution situations are reduced to representing an elevator rectangular space, with inside having representative red particle.Pass through aforesaid operations, people can easily observe how many people in current elevator, remaining space is also enough to be gone successively to, this intuitive ways of presentation avoids elevator after corresponding floor comes to a complete stop enabling, time multiplies people and finds that space not enough cannot be introduced into, and the awkward situation that do not take is selected, improve the elevator operating efficiency of peak period.
Description
Technical field
The present invention relates to a kind of elevator devices, and in particular to a kind of method and intelligence for showing elevator interior personnel distributed intelligence
It can elevator device.
Background technique
Elevator be people vertically walk about in building it is most important take tool, elevator device is widely used, give people
Bring many convenience and benefit.With the development of society, the building of live ladder is more more and more universal.In cell, market, write
In the densely populated building such as word building, the utilization rate of elevator is very high, especially in equal peak times on and off duty, it usually needs in
Stop repeatedly people's on-board and off-board for different floors on way.
In the elevator device being nowadays widely present, usually have following defect urgently to be resolved: when being fully loaded in elevator,
Can not continue it is upper visitor when, stand floor waiting people and be unaware of current elevator interior personnel be distributed and load state, elevator
After stop, new visitor is accommodated because that can not continue due to continues traveling of closing the door, this process undoubtedly wastes passenger and waits the time for multiplying people,
The high efficiency for being unfavorable for elevator device is advanced.In brief, present elevator device can not multiply people's offer real-time update to time
Internal information, time multiplies people and can not choose whether to take this class of elevator according to the actual situation.
Summary of the invention
Goal of the invention: providing a kind of method for showing elevator interior personnel distributed intelligence, of the existing technology to solve
The above problem.Further objective is that providing a kind of Intelligent lift system for realizing the above method.
Technical solution: a method of showing elevator interior personnel distributed intelligence, comprising the following steps:
Step 1, the personnel's distributed intelligence for collecting elevator interior；
Step 2 carries out image procossing to personnel's distributed intelligence, removes background interference, obtains and exist including personnel's profile, elevator boundary
Interior image data；
Step 3, to the further edge detection of personnel's profile obtained in step 2, exclude noise jamming, and be reduced to particle；
Step 4, by treated in step 3, information is sent to display screen, and the personnel of current elevator interior are shown by display screen
Distribution situation, the visual angle of personnel's distribution situation are to overlook angle of field, are refreshed every one second primary.
In a further embodiment, the step 1 is further are as follows:
Step 11, Image Acquisition: multiple industrial cameras by being mounted on ceiling in elevator carry out captured in real-time, and will shooting
To dynamic menu real-time Transmission to middle control machine；
Step 12, image rectification: multiple industrial cameras carry out including trapezoidal according to self-position and the region taken to image
Image rectification including correction；
Step 13, image integration: middle control machine carries out the image data that multiple industrial cameras return according to image rectification algorithm whole
It closes, multiple images is integrated into single-frame images；
Step 14, gateway remote control: the shutter of multiple industrial cameras, exposure, aperture information are identical, and are controlled by control gateway is unified
Make its shooting, it is ensured that the shooting time of each industrial camera is consistent with frequency.
In a further embodiment, the step 2 is further are as follows:
Step 21, picture noise estimation: calculating the noise figure of image by Generalized Cross Validation algorithm, and Generalized Cross Validation is calculated
Method formula is
Wherein,yExpression needs to carry out the image of noise estimation,The characteristic value of expression, D areTriangular matrix, n are pixel
Points,Indicate theiThe discrete cosine transform of a element,sIt indicates to obtain when minimizing by Generalized Cross Validation algorithm score
The parameter value taken；
Step 22, adapting to image filtering: it divides the image intoMultiple regions, obtain the Gaussian Profile in each region
Matched subordinating degree function, calculation formula are
Wherein,It indicatesThe mean value of every pixel value and center value differences in region,It indicates
The variance of every pixel value and center value differences in region,It indicatesCoordinate in region at center.
In a further embodiment, the step 3 is further are as follows:
Step 31,2-d discrete wavelet decompose: on the basis of the original image that step 2 obtains line by line, by column decompose low frequency system
Number part, is decomposed respectively to the horizontal direction of image and vertical direction uniform scanning every time；
Step 32, low-pass filtering treatment: by picture signal by low-pass filter, the data for being similar to original signal are obtained；
Step 33, high-pass filtering processing: by picture signal by high-pass filter, the image data of edge details is obtained；
Step 34, gray value processing: greyscale transformation is carried out to the image after high-pass filter, calculation formula is
In formula,For the gray value of image,For gray value of imageProbability density function,Become for the brightness of image
Exchange the letters number,For the new gray value of image；
Step 35, binary conversion treatment: setting 0 or 255 for the gray value of the pixel on image, so that whole image presentation is black
White effect, so that the contrast of image border and background colour reaches predetermined value；
Step 36, particle simplify: in image after the edge detection of the contours extract of step 2 and step 3, extracting the several of image
What central point is used as particle, the position of the white pixel of image after statistics binary conversion treatment, according to white pixel point and black picture
The position of vegetarian refreshments calculates the center of bianry image.
In a further embodiment, the step 4 is further are as follows:
Step 41, industrial camera, which pass through image to establish between GigE interface and middle control machine, to be communicated, and the GigE interface is based on thousand
Mbit ethernet communication protocol；
Step 42, middle control machine are established by CoaXPress interface and display screen and are communicated；
Shown in step 43, display screen with the consistent rectangle closed space of the practical length-width ratio of elevator interior, by the people in elevator
Member is shown as red dot, rgb value 255,0,0 after being reduced to particle；It is 255 that the background colour of rectangle closed space, which is set as rgb value,
255,255 pure white.
A kind of Intelligent lift system, it is characterized in that including:
The elevator case in the elevator, and the connection elevator is arranged in foundation structure, including elevator, vertical sliding
With the traction component of elevator case；
Velocity-measuring system, including the Hall velocity sensor being connect with the output end of the traction component；
Display systems are loaded, including the multiple industrial cameras being mounted at the top quadrangle and center of the elevator case；
Man-machine interactive system, including the display screen at corresponding floor is arranged in；
Middle control component, including the middle control machine being built at the elevator；
The velocity-measuring system loads and establishes communication between display systems, man-machine interactive system between the middle control machine and share
Data.
In a further embodiment, the elevator includes the sliding rail being vertically arranged, and the two sides of the elevator case are equipped with
Pulley, the elevator case, which is slided by pulley along the sliding rail, to be arranged；The traction component includes being fixed on the elevator head
The rack at tail both ends is fixed on the elevator host of the upper rack, the coaxially connected volume with the output shaft of the elevator host
Drum, the clump weight being slidably arranged on the elevator, and be wound around on the winding roll, one end and the elevator case connect
It connects, the traction rope that the other end is connect with the clump weight；The output shaft of the Hall velocity sensor and the elevator host is same
Axis connection.
In a further embodiment, the Intelligent lift system further includes following module:
For collecting the industrial camera module of personnel's distributed intelligence of elevator interior；
For carrying out image procossing to personnel's distributed intelligence, background interference is removed, is obtained including personnel's profile, elevator boundary
Image data image outline preprocessing module；
For excluding noise jamming to the further edge detection of personnel's profile, and it is reduced to the image border advanced treating of particle
Module；
For will treated that information is sent to display screen, personnel's distribution situation of current elevator interior is shown by display screen
Internet of Things transmission module.
In a further embodiment, it is whole to be further used for Image Acquisition, image rectification, image for the industrial camera module
It closes and gateway is remotely controlled, further, multiple industrial cameras by being mounted on ceiling in elevator carry out captured in real-time,
And by the dynamic menu real-time Transmission taken to middle control machine；Multiple industrial cameras are according to self-position and the region pair taken
Image carries out the image rectification including keystone；What middle control machine returned multiple industrial cameras according to image rectification algorithm
Image data is integrated, and multiple images are integrated into single-frame images；The shutter of multiple industrial cameras, exposure, aperture information
It is identical, and its shooting is uniformly controlled by control gateway, it is ensured that the shooting time of each industrial camera is consistent with frequency.
In a further embodiment, described image profile preprocessing module be further used for picture noise estimation, it is adaptive
Answer image filtering, further,
The noise figure of image is calculated by Generalized Cross Validation algorithm, Generalized Cross Validation algorithmic formula is
Wherein,yExpression needs to carry out the image of noise estimation,It indicatesCharacteristic value, D isTriangular matrix, n are
Pixel number,Indicate theiThe discrete cosine transform of a element,sIt indicates to minimize by Generalized Cross Validation algorithm score
When the parameter value that obtains；
It divides the image intoMultiple regions, obtain the matched subordinating degree function of Gaussian Profile in each region, calculate public
Formula is
Wherein,It indicatesThe mean value of every pixel value and center value differences in region,It indicates
The variance of every pixel value and center value differences in region,It indicatesCoordinate in region at center；
Described image edge advanced treating module is further used for 2-d discrete wavelet decomposition, low-pass filtering treatment, high-pass filtering
Processing, gray value processing, binary conversion treatment and particle simplify, further,
On the basis of original image line by line, by column decompose low frequency coefficient part, every time decompose respectively to the horizontal direction of image
With vertical direction uniform scanning；
By picture signal by low-pass filter, the data for being similar to original signal are obtained；
By picture signal by high-pass filter, the image data of edge details is obtained；
Greyscale transformation is carried out to the image after high-pass filter, calculation formula is
In formula,For the gray value of image,For gray value of imageProbability density function,For the luminance transformation of image
Function,For the new gray value of image；
0 or 255 are set by the gray value of the pixel on image, so that black and white effect is presented in whole image, so that image side
The contrast of edge and background colour reaches predetermined value；
Extract image geometric center point be used as particle, statistics binary conversion treatment after image white pixel position, according to white
The position of colour vegetarian refreshments and black pixel point calculates the center of bianry image；
Image further is passed through to establish between GigE interface and middle control machine by the Internet of Things transmission module by industrial camera to be communicated,
The GigE interface is based on gigabit Ethernet communication protocol；It is established and is communicated by CoaXPress interface and display screen by middle control machine；
Shown on display screen with the consistent rectangle closed space of the practical length-width ratio of elevator interior, the personnel in elevator are reduced to particle
After be shown as red dot, rgb value 255,0,0；By the background colour of rectangle closed space be set as rgb value be 255,255,255 it is pure
White.
The utility model has the advantages that the present invention relates to a kind of method and Intelligent lift system for showing elevator interior personnel distributed intelligence,
Multiple industrial cameras are set by the inner tip in elevator case, industrial camera is taken pictures sampling with preset frequency, each frame picture
All it is eventually displayed on display screen by noise reduction, the mode extracted edge contour, convert particle respectively.When people are in waiting electricity
When terraced, in real time and it can be visually observed that personnel's distribution situation of current elevator interior, these personnel's distribution situations are reduced to
One with representing elevator rectangular space, with inside having representative red particle.By aforesaid operations, people can easily be observed
How many people in current elevator, remaining space is also enough to be gone successively to, and this intuitive ways of presentation avoids elevator right
Floor is answered to come to a complete stop after enabling, time multiplies people and finds that space not enough cannot be introduced into, and selects the awkward situation that do not take, and improves peak
The elevator operating efficiency of period.Time, which multiplies people, can choose whether to take this class of elevator according to actual person distribution situation, if judgement is empty
Between not enough, can not continue to take and then actively select clearance elevator, it is not necessary to allow elevator sky to stop and waste time, this is on and off duty
Peak period is undoubtedly very useful.
Detailed description of the invention
Fig. 1 is a kind of flow chart for the method for showing elevator interior personnel distributed intelligence of the present invention.
Fig. 2 is the detail flowchart of step 1 in a kind of method for showing elevator interior personnel distributed intelligence of the present invention.
Fig. 3 is the detail flowchart of step 2 in a kind of method for showing elevator interior personnel distributed intelligence of the present invention.
Fig. 4 is the detail flowchart of step 3 in a kind of method for showing elevator interior personnel distributed intelligence of the present invention.
Fig. 5 is the detail flowchart of step 4 in a kind of method for showing elevator interior personnel distributed intelligence of the present invention.
Fig. 6 is the content schematic diagram that screen display is shown in the present invention (this state is that can not continue to accommodate).
Fig. 7 is the content schematic diagram that screen display is shown in the present invention (this state is that can continue to accommodate).
Fig. 8 is the filtering obtained after 2-d discrete wavelet decomposes using MATLAB program to original image in the present invention
Image.
Fig. 9 is the image obtained after extracting profile and noise reduction using MATLAB program to original image in the present invention.
Figure 10 is the present invention to the histogram obtained after original image gray proces equalization.
Figure 11 is the flow chart that the present invention carries out discontinuous edge detection algorithm to original image.
Figure 12 is multiple industrial camera coverage schematic diagrames in the present invention.
Figure 13 is a kind of external structure of Intelligent lift system in the present invention.
Each appended drawing reference in figure are as follows: clump weight 1, elevator 2, traction rope 3, elevator host 4, winding roll 5, rack 6, elevator
Case 7, corresponding floor 8, industrial camera 9.
Specific embodiment
In the following description, a large amount of concrete details are given so as to provide a more thorough understanding of the present invention.So
And it is obvious to the skilled person that the present invention may not need one or more of these details and be able to
Implement.In other examples, in order to avoid confusion with the present invention, for some technical characteristics well known in the art not into
Row description.
In the description of the present invention, it should be noted that term " center ", "upper", "lower", "left", "right", "vertical",
The orientation or positional relationship of the instructions such as "horizontal", "inner", "outside" be based on the orientation or positional relationship shown in the drawings, merely to
Convenient for description the present invention and simplify description, rather than the device or element of indication or suggestion meaning must have a particular orientation,
It is constructed and operated in a specific orientation, therefore is not considered as limiting the invention.In addition, term " first ", " second ",
" third " is used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance.
As shown in figure 1 to figure 13, the invention discloses a kind of methods and intelligence for showing elevator interior personnel distributed intelligence
Elevator device.The Intelligent lift system includes foundation structure, velocity-measuring system, load display systems, man-machine interactive system, middle control group
Five part of part, the velocity-measuring system, load display systems, established between the middle control machine between man-machine interactive system communication,
And shared data.The foundation structure includes elevator 2, elevator case 7, traction component, and 7 vertical sliding of the elevator case setting exists
In the elevator 2, the traction component connects the elevator 2 and elevator case 7.The velocity-measuring system includes that Hall tests the speed biography
Sensor, the Hall velocity sensor are connect with the output end of the traction component.The load display systems include being mounted on
The top quadrangle of the elevator case 7 and multiple industrial cameras 9 at center.The man-machine interactive system includes setting in corresponding building
Display screen at layer 8.The middle control component includes the middle control machine for being built in 2 pre-position of elevator.The industry phase
Machine 9, which passes through, establishes communication between GigE interface and middle control machine, the GigE interface is based on gigabit Ethernet communication protocol；In described
Control machine is established by CoaXPress interface and display screen and is communicated.
As a preferred embodiment, the elevator 2 includes the sliding rail being vertically arranged, and the two sides of the elevator case 7 are equipped with
Pulley, the elevator case 7, which is slided by pulley along the sliding rail, to be arranged；The traction component includes being fixed on the elevator 2
The rack 6 at head and the tail both ends is fixed on the elevator host 4 on 6 top of rack, coaxially connects with the output shaft of the elevator host 4
The winding roll 5 connect, the clump weight 1 being slidably arranged on the elevator 2, and be wound around on the winding roll 5, one end and institute
State the connection of elevator case 7, the traction rope 3 that the other end is connect with the clump weight 1；The Hall velocity sensor and the elevator master
The output shaft of machine 4 is coaxially connected.
As a preferred embodiment, the Intelligent lift system further includes following module:
For collecting 9 module of industrial camera of personnel's distributed intelligence of elevator interior；
For carrying out image procossing to personnel's distributed intelligence, background interference is removed, is obtained including personnel's profile, elevator boundary
Image data image outline preprocessing module；
For excluding noise jamming to the further edge detection of personnel's profile, and it is reduced to the image border advanced treating of particle
Module；
For will treated that information is sent to display screen, personnel's distribution situation of current elevator interior is shown by display screen
Internet of Things transmission module.
As a preferred embodiment, it is whole that 9 module of industrial camera is further used for Image Acquisition, image rectification, image
It closes and gateway is remotely controlled, further, multiple industrial cameras 9 by being mounted on ceiling in elevator carry out captured in real-time,
And by the dynamic menu real-time Transmission taken to middle control machine；Multiple industrial cameras 9 are according to self-position and the region taken
Image rectification including keystone is carried out to image；Middle control machine returns multiple industrial cameras 9 according to image rectification algorithm
The image data of biography is integrated, and multiple images are integrated into single-frame images；Shutter, exposure, the aperture of multiple industrial cameras 9
Information is identical, and is uniformly controlled its shooting by control gateway, it is ensured that the shooting time of each industrial camera 9 is consistent with frequency.
As a preferred embodiment, described image profile preprocessing module is further used for picture noise and estimates, is adaptive
Image filtering, further,
The noise figure of image is calculated by Generalized Cross Validation algorithm, Generalized Cross Validation algorithmic formula is
Wherein,yExpression needs to carry out the image of noise estimation,It indicatesCharacteristic value, D isTriangular matrix, n are
Pixel number,Indicate theiThe discrete cosine transform of a element,sIt indicates to minimize by Generalized Cross Validation algorithm score
When the parameter value that obtains；
It divides the image intoMultiple regions, obtain the matched subordinating degree function of Gaussian Profile in each region, calculate public
Formula is
Wherein,It indicatesThe mean value of every pixel value and center value differences in region,It indicates
The variance of every pixel value and center value differences in region,Indicate the coordinate in region at center；
Described image edge advanced treating module is further used for 2-d discrete wavelet decomposition, low-pass filtering treatment, high-pass filtering
Processing, gray value processing, binary conversion treatment and particle simplify, further,
On the basis of original image line by line, by column decompose low frequency coefficient part, every time decompose respectively to the horizontal direction of image
With vertical direction uniform scanning；
By picture signal by low-pass filter, the data for being similar to original signal are obtained；
By picture signal by high-pass filter, the image data of edge details is obtained；
Greyscale transformation is carried out to the image after high-pass filter, calculation formula is
In formula,For the gray value of image,For gray value of imageProbability density function, be image luminance transformation
Function,For the new gray value of image；
0 or 255 are set by the gray value of the pixel on image, so that black and white effect is presented in whole image, so that image side
The contrast of edge and background colour reaches predetermined value；
Extract image geometric center point be used as particle, statistics binary conversion treatment after image white pixel position, according to white
The position of colour vegetarian refreshments and black pixel point calculates the center of bianry image；
Image further is passed through to establish between GigE interface and middle control machine by the Internet of Things transmission module by industrial camera 9 to be led to
News, the GigE interface are based on gigabit Ethernet communication protocol；It is established and is led to by CoaXPress interface and display screen by middle control machine
News；Shown on display screen with the consistent rectangle closed space of the practical length-width ratio of elevator interior, the personnel in elevator are reduced to
Red dot, rgb value 255,0,0 are shown as after particle；It is 255,255,255 that the background colour of rectangle closed space, which is set as rgb value,
Pure white.
It is noted that identifying that the personnel in elevator case 7 are distributed using industrial camera 9 in this Intelligent lift system
Situation, and shown on a display screen after a series of images Processing Algorithm, for user's reference；It is tested the speed sensing using Hall
Device is by the turn signal pick-up of winding roll 5 to sensor, then reaches console, calculates electricity according to the velocity of rotation of winding roll 5
The lifting speed of terraced case 7, and show that on a display screen, lifting speed is shown using the international unit of m/s.
Based on above-mentioned Intelligent lift system, the present invention proposes a kind of method for showing elevator interior personnel distributed intelligence, with
Solve problems and shortcoming of the existing technology.Specifically, a kind of side for showing elevator interior personnel distributed intelligence
Method the following steps are included:
Step 1, the personnel's distributed intelligence for collecting elevator interior；Further, step 1 can be subdivided into Image Acquisition, image calibration again
Just, image integration and gateway are remotely controlled four substeps:
Image Acquisition: multiple industrial cameras 9 by being mounted on ceiling in elevator carry out captured in real-time, and dynamic by what is taken
State picture real-time Transmission is to middle control machine；
Image rectification: multiple industrial cameras 9 carry out including that keystone exists according to self-position and the region taken to image
Interior image rectification；
Image integration: middle control machine is integrated according to the image data that image rectification algorithm returns multiple industrial cameras 9, will be more
A image integration is at single-frame images；
Gateway remote control: the shutter of multiple industrial cameras 9, exposure, aperture information are identical, and are uniformly controlled its bat by control gateway
It takes the photograph, it is ensured that the shooting time of each industrial camera 9 is consistent with frequency.
Step 2 carries out image procossing to personnel's distributed intelligence, removes background interference, obtains including personnel's profile, escalator edge
Image data including boundary；Further, step 2 can be subdivided into picture noise estimation again and adapting to image filters two
Step by step:
Picture noise estimation: the noise figure of image, Generalized Cross Validation algorithmic formula are calculated by Generalized Cross Validation algorithm
For
Wherein,yExpression needs to carry out the image of noise estimation,It indicatesCharacteristic value, D isTriangular matrix, n are
Pixel number,Indicate theiThe discrete cosine transform of a element,sIt indicates to minimize by Generalized Cross Validation algorithm score
When the parameter value that obtains；
Adapting to image filtering: it divides the image intoMultiple regions, obtain the matched person in servitude of Gaussian Profile in each region
Category degree function, calculation formula are
Wherein,It indicatesThe mean value of every pixel value and center value differences in region,It indicates
The variance of every pixel value and center value differences in region,It indicatesCoordinate in region at center.
Step 3, to the further edge detection of personnel's profile obtained in step 2, exclude noise jamming, and be reduced to matter
Point；Further, step 3 can be subdivided into 2-d discrete wavelet decomposition, low-pass filtering treatment, high-pass filtering processing, gray value again
Processing, binary conversion treatment and particle simplify six substeps:
2-d discrete wavelet decompose: on the basis of the original image that step 2 obtains line by line, by column decompose low frequency coefficient part,
It decomposes every time respectively to the horizontal direction of image and vertical direction uniform scanning；
Low-pass filtering treatment: by picture signal by low-pass filter, the data for being similar to original signal are obtained；
High-pass filtering processing: by picture signal by high-pass filter, the image data of edge details is obtained；
Gray value processing: greyscale transformation is carried out to the image after high-pass filter, calculation formula is
In formula,For the gray value of image,For gray value of imageProbability density function,Become for the brightness of image
Exchange the letters number,For the new gray value of image；
Binary conversion treatment: setting 0 or 255 for the gray value of the pixel on image, so that black and white effect is presented in whole image,
So that the contrast of image border and background colour reaches predetermined value；
Particle simplifies: in image after the edge detection of the contours extract of step 2 and step 3, extracting the geometric center of image
Point is used as particle, the position of the white pixel of image after binary conversion treatment is counted, according to white pixel point and black pixel point
Position calculates the center of bianry image.
Step 4, by treated in step 3, information is sent to display screen, shows current elevator interior by display screen
Personnel's distribution situation, the visual angle of personnel's distribution situation are to overlook angle of field, are refreshed every one second primary.Further, step 4
Following steps can be subdivided into again: be communicated firstly, industrial camera 9 passes through image to establish between GigE interface and middle control machine, it is described
GigE interface is based on gigabit Ethernet communication protocol；Then, middle control machine is established by CoaXPress interface and display screen and is communicated；
Finally, shown on display screen with the consistent rectangle closed space of the practical length-width ratio of elevator interior, by elevator personnel simplify
To be shown as red dot, rgb value 255,0,0 after particle；It is 255,255 that the background colour of rectangle closed space, which is set as rgb value,
255 pure white.
For above-mentioned steps, it is worth mentioning at this point that, followed when being detected in the present invention to the discontinuous edge of blurred picture with
Lower process: it is estimated first with noise of the cross validation criterion to image, estimates the variance yields, then by the noise side
Difference and threshold comparison carry out fuzzy discontinuous edge detection, need using adaptive if the variance yields judged is greater than threshold value
Answer image filtering；If the variance yields judged is not more than threshold value, edge detecting operation is carried out.
Under above-mentioned technical proposal, the present invention it is specific use process is as follows: when elevator is when operating normally, be arranged in electricity
Multiple industrial cameras 9 of terraced 7 inner top of case are taken pictures sampling with preset frequency, which preferably refreshed every one second primary.For
Ensure that the shooting time of each industrial camera 9 is consistent with frequency, the shutter of multiple industrial cameras 9, exposure, aperture information phase
Together, and by control gateway it is uniformly controlled its shooting.Each frame picture that industrial camera 9 takes is all respectively by noise reduction, extraction
Edge contour, the mode for converting particle, are eventually displayed on display screen.When people are in awaiting elevator, can be observed in real time
Personnel's distribution situation of current elevator interior, these personnel's distribution situations are reduced to a rectangular space, inside there is red particle, square
Shape space represents the space of elevator case 7, and red particle representative, the length-width ratio and elevator running case 7 of rectangular space are unanimously.Pass through
Aforesaid operations, people can easily observe how many people in current elevator, and remaining space is also enough to be gone successively to, this
Intuitive ways of presentation avoids elevator after corresponding floor 8 comes to a complete stop enabling, not unapproachable enough the awkward situation in discovery space,
The elevator operating efficiency of peak period is also improved simultaneously.
As described above, must not be explained although the present invention has been indicated and described referring to specific preferred embodiment
For the limitation to invention itself.It without prejudice to the spirit and scope of the invention as defined in the appended claims, can be right
It makes a variety of changes in the form and details.
Claims (10)
1. a kind of method for showing elevator interior personnel distributed intelligence, it is characterized in that the following steps are included:
Step 1, the personnel's distributed intelligence for collecting elevator interior；
Step 2 carries out image procossing to personnel's distributed intelligence, removes background interference, obtains and exist including personnel's profile, elevator boundary
Interior image data；
Step 3, to the further edge detection of personnel's profile obtained in step 2, exclude noise jamming, and be reduced to particle；
Step 4, by treated in step 3, information is sent to display screen, and the personnel of current elevator interior are shown by display screen
Distribution situation, the visual angle of personnel's distribution situation are to overlook angle of field, are refreshed every one second primary.
2. a kind of method for showing elevator interior personnel distributed intelligence according to claim 1, which is characterized in that the step
Rapid 1 further are as follows:
Step 11, Image Acquisition: multiple industrial cameras by being mounted on ceiling in elevator carry out captured in real-time, and will shooting
To dynamic menu real-time Transmission to middle control machine；
Step 12, image rectification: multiple industrial cameras carry out including trapezoidal according to self-position and the region taken to image
Image rectification including correction；
Step 13, image integration: middle control machine carries out the image data that multiple industrial cameras return according to image rectification algorithm whole
It closes, multiple images is integrated into single-frame images；
Step 14, gateway remote control: the shutter of multiple industrial cameras, exposure, aperture information are identical, and are controlled by control gateway is unified
Make its shooting, it is ensured that the shooting time of each industrial camera is consistent with frequency.
3. a kind of method for showing elevator interior personnel distributed intelligence according to claim 1, which is characterized in that described
Step 2 is further are as follows:
Step 21, picture noise estimation: calculating the noise figure of image by Generalized Cross Validation algorithm, and Generalized Cross Validation is calculated
Method formula is
Wherein,yExpression needs to carry out the image of noise estimation,It indicatesCharacteristic value, D isTriangular matrix, n are
Pixel number,Indicate theiThe discrete cosine transform of a element,sIt indicates to minimize by Generalized Cross Validation algorithm score
When the parameter value that obtains；
Step 22, adapting to image filtering: it divides the image intoMultiple regions, obtain the Gaussian Profile in each region
The subordinating degree function matched, calculation formula are
Wherein,It indicatesThe mean value of every pixel value and center value differences in region,It indicates
The variance of every pixel value and center value differences in region,It indicatesCoordinate in region at center.
4. a kind of method for showing elevator interior personnel distributed intelligence according to claim 1, which is characterized in that the step
Rapid 3 further are as follows:
Step 31,2-d discrete wavelet decompose: on the basis of the original image that step 2 obtains line by line, by column decompose low frequency system
Number part, is decomposed respectively to the horizontal direction of image and vertical direction uniform scanning every time；
Step 32, low-pass filtering treatment: by picture signal by low-pass filter, the data for being similar to original signal are obtained；
Step 33, high-pass filtering processing: by picture signal by high-pass filter, the image data of edge details is obtained；
Step 34, gray value processing: greyscale transformation is carried out to the image after high-pass filter, calculation formula is
In formula,For the gray value of image,For gray value of imageProbability density function,For the luminance transformation of image
Function,For the new gray value of image；
Step 35, binary conversion treatment: setting 0 or 255 for the gray value of the pixel on image, so that whole image presentation is black
White effect, so that the contrast of image border and background colour reaches predetermined value；
Step 36, particle simplify: in image after the edge detection of the contours extract of step 2 and step 3, extracting the several of image
What central point is used as particle, the position of the white pixel of image after statistics binary conversion treatment, according to white pixel point and black picture
The position of vegetarian refreshments calculates the center of bianry image.
5. a kind of method for showing elevator interior personnel distributed intelligence according to claim 1, it is characterised in that: the step
Rapid 4 further are as follows:
Step 41, industrial camera, which pass through image to establish between GigE interface and middle control machine, to be communicated, and the GigE interface is based on thousand
Mbit ethernet communication protocol；
Step 42, middle control machine are established by CoaXPress interface and display screen and are communicated；
Shown in step 43, display screen with the consistent rectangle closed space of the practical length-width ratio of elevator interior, by the people in elevator
Member is shown as red dot, rgb value 255,0,0 after being reduced to particle；It is 255 that the background colour of rectangle closed space, which is set as rgb value,
255,255 pure white.
6. a kind of Intelligent lift system, it is characterized in that including:
The elevator case in the elevator, and the connection elevator is arranged in foundation structure, including elevator, vertical sliding
With the traction component of elevator case；
Velocity-measuring system, including the Hall velocity sensor being connect with the output end of the traction component；
Display systems are loaded, including the multiple industrial cameras being mounted at the top quadrangle and center of the elevator case；
Man-machine interactive system, including the display screen at corresponding floor is arranged in；
Middle control component, including the middle control machine being built at the elevator；
The velocity-measuring system loads and establishes communication between display systems, man-machine interactive system between the middle control machine and share
Data.
7. a kind of Intelligent lift system according to claim 6, it is characterised in that: the elevator includes being vertically arranged
Sliding rail, the two sides of the elevator case are equipped with pulley, and the elevator case, which is slided by pulley along the sliding rail, to be arranged；The draw groups
Part includes the rack for being fixed on elevator head and the tail both ends, is fixed on the elevator host of the upper rack, with the elevator
The coaxially connected winding roll of the output shaft of host, the clump weight being slidably arranged on the elevator, and it is wound around the volume
On drum, one end connect with the elevator case, the traction rope that the other end is connect with the clump weight；The Hall velocity sensor
It is coaxially connected with the output shaft of the elevator host.
8. a kind of Intelligent lift system according to claim 6, it is characterised in that: the Intelligent lift system further include as
Lower module:
For collecting the industrial camera module of personnel's distributed intelligence of elevator interior；
For carrying out image procossing to personnel's distributed intelligence, background interference is removed, is obtained including personnel's profile, elevator boundary
Image data image outline preprocessing module；
For excluding noise jamming to the further edge detection of personnel's profile, and it is reduced to the image border advanced treating of particle
Module；
For will treated that information is sent to display screen, personnel's distribution situation of current elevator interior is shown by display screen
Internet of Things transmission module.
9. a kind of Intelligent lift system according to claim 8, it is characterised in that: the industrial camera module is further used
It is remotely controlled in Image Acquisition, image rectification, image integration and gateway, further, by being mounted on ceiling in elevator
Multiple industrial cameras carry out captured in real-time, and by the dynamic menu real-time Transmission taken to middle control machine；Multiple industrial camera roots
The image rectification including keystone is carried out to image according to self-position and the region taken；Middle control machine is according to image calibration
The image data that normal operation method returns multiple industrial cameras is integrated, and multiple images are integrated into single-frame images；Multiple industry
The shutter of camera, exposure, aperture information are identical, and are uniformly controlled its shooting by control gateway, it is ensured that each industrial camera
Shooting time is consistent with frequency.
10. a kind of Intelligent lift system according to claim 8, which is characterized in that
Described image profile preprocessing module is further used for picture noise estimation, adapting to image filtering, further,
The noise figure of image is calculated by Generalized Cross Validation algorithm, Generalized Cross Validation algorithmic formula is
Wherein,yExpression needs to carry out the image of noise estimation,It indicatesCharacteristic value, D isTriangular matrix, n are
Pixel number,Indicate theiThe discrete cosine transform of a element,sIt indicates to minimize by Generalized Cross Validation algorithm score
When the parameter value that obtains；
It divides the image intoMultiple regions, obtain the matched subordinating degree function of Gaussian Profile in each region, calculate public
Formula is
Wherein,It indicatesThe mean value of every pixel value and center value differences in region,It indicates
The variance of every pixel value and center value differences in region,It indicatesCoordinate in region at center；
Described image edge advanced treating module is further used for 2-d discrete wavelet decomposition, low-pass filtering treatment, high-pass filtering
Processing, gray value processing, binary conversion treatment and particle simplify, further,
On the basis of original image line by line, by column decompose low frequency coefficient part, every time decompose respectively to the horizontal direction of image
With vertical direction uniform scanning；
By picture signal by low-pass filter, the data for being similar to original signal are obtained；
By picture signal by high-pass filter, the image data of edge details is obtained；
Greyscale transformation is carried out to the image after high-pass filter, calculation formula is
In formula,For the gray value of image,For gray value of imageProbability density function,For the luminance transformation of image
Function,For the new gray value of image；
0 or 255 are set by the gray value of the pixel on image, so that black and white effect is presented in whole image, so that image side
The contrast of edge and background colour reaches predetermined value；
Extract image geometric center point be used as particle, statistics binary conversion treatment after image white pixel position, according to white
The position of colour vegetarian refreshments and black pixel point calculates the center of bianry image；
Image further is passed through to establish between GigE interface and middle control machine by the Internet of Things transmission module by industrial camera to be communicated,
The GigE interface is based on gigabit Ethernet communication protocol；It is established and is communicated by CoaXPress interface and display screen by middle control machine；
Shown on display screen with the consistent rectangle closed space of the practical length-width ratio of elevator interior, the personnel in elevator are reduced to particle
After be shown as red dot, rgb value 255,0,0；By the background colour of rectangle closed space be set as rgb value be 255,255,255 it is pure
White.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910704007.4A CN110407045B (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator and intelligent elevator system |
| CN202010265444.3A CN111573450A (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910704007.4A CN110407045B (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator and intelligent elevator system |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010265444.3A Division CN111573450A (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110407045A true CN110407045A (en) | 2019-11-05 |
| CN110407045B CN110407045B (en) | 2020-05-19 |
Family
ID=68364933
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910704007.4A Active CN110407045B (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator and intelligent elevator system |
| CN202010265444.3A Withdrawn CN111573450A (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010265444.3A Withdrawn CN111573450A (en) | 2019-07-31 | 2019-07-31 | Method for displaying personnel distribution information in elevator |
Country Status (1)
| Country | Link |
|---|---|
| CN (2) | CN110407045B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112520524A (en) * | 2021-01-13 | 2021-03-19 | 大连理工大学 | Intelligent elevator control interaction device and control method based on gesture recognition technology |
| CN115108426A (en) * | 2022-05-25 | 2022-09-27 | 浙江大华技术股份有限公司 | Elevator control method, elevator control device, computer equipment and readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101723226A (en) * | 2009-12-24 | 2010-06-09 | 杭州优迈科技有限公司 | System and method of machine vision three-dimensional detection elevator light curtain |
| CN106161961A (en) * | 2016-08-27 | 2016-11-23 | 山东万博科技股份有限公司 | The camera video supervising device of a kind of dead zone-eliminating and method |
| WO2017164287A1 (en) * | 2016-03-23 | 2017-09-28 | 日本電気株式会社 | Information processing system, information processing method and program |
| CN110002291A (en) * | 2019-03-25 | 2019-07-12 | 上海富士电梯有限公司 | Elevator intelligent based on image recognition cuts vehicle control |
-
2019
- 2019-07-31 CN CN201910704007.4A patent/CN110407045B/en active Active
- 2019-07-31 CN CN202010265444.3A patent/CN111573450A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101723226A (en) * | 2009-12-24 | 2010-06-09 | 杭州优迈科技有限公司 | System and method of machine vision three-dimensional detection elevator light curtain |
| WO2017164287A1 (en) * | 2016-03-23 | 2017-09-28 | 日本電気株式会社 | Information processing system, information processing method and program |
| CN106161961A (en) * | 2016-08-27 | 2016-11-23 | 山东万博科技股份有限公司 | The camera video supervising device of a kind of dead zone-eliminating and method |
| CN110002291A (en) * | 2019-03-25 | 2019-07-12 | 上海富士电梯有限公司 | Elevator intelligent based on image recognition cuts vehicle control |
Non-Patent Citations (1)
| Title |
|---|
| 易三莉，郭贝贝，马磊，钱洁: "《改进的模糊推理规则图像边缘检测算法》", 《计算机工程与应用》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110407045B (en) | 2020-05-19 |
| CN111573450A (en) | 2020-08-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102663869B (en) | Indoor fire detection method based on video monitoring platform | |
| CN108320575A (en) | A kind of guiding of parking stall and reverse vehicle searching system and its parking space-detecting device, method | |
| CN102542572B (en) | Method for detecting moving object image in video sequence and image processing system | |
| CN103310422B (en) | Obtain the method and device of image | |
| GB2542467A (en) | Video-based system and method for parking occupancy detection | |
| CN110407045A (en) | A kind of method and Intelligent lift system showing elevator interior personnel distributed intelligence | |
| WO2006008944A1 (en) | Image processor, image processing method, image processing program, and recording medium on which the program is recorded | |
| CN103581614A (en) | Method and system for tracking targets in video based on PTZ | |
| CN109409289A (en) | A kind of electric operating safety supervision robot security job identifying method and system | |
| CN107085707A (en) | A kind of license plate locating method based on Traffic Surveillance Video | |
| CN112016482B (en) | Method and device for distinguishing false face and computer equipment | |
| Choeychuen | Available car parking space detection from webcam by using adaptive mixing features | |
| CN104700405A (en) | Foreground detection method and system | |
| CN110503017A (en) | Wisdom energy conservation occupancy detection system and method based on image procossing | |
| CN110728212B (en) | Road well lid monitoring device and monitoring method based on computer vision | |
| CN102509414B (en) | Smog detection method based on computer vision | |
| CN101411190A (en) | Spurious motion filter | |
| CN107610106B (en) | Detection method, detection device, electronic equipment and computer-readable storage medium | |
| CN112651962A (en) | AI intelligent diagnosis system platform | |
| CN112991665A (en) | Smoke detection method, smoke detection device, and smoke detection system | |
| CN115294486B (en) | Method for identifying and judging illegal garbage based on unmanned aerial vehicle and artificial intelligence | |
| CN106056730A (en) | Community garage intelligent access control system based on license plate detection and application method thereof | |
| CN102542304B (en) | Region segmentation skin-color algorithm for identifying WAP (Wireless Application Protocol) mobile porn image | |
| JP2004030225A (en) | White smoke detection method and apparatus | |
| JP2007164375A (en) | Three-dimensional object detection device and method, computer readable medium and three-dimensional object management 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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20210430 Address after: 211100 300 Chi Hui Road, Qilin science and Technology Innovation Park, Jiangning District, Nanjing, Jiangsu Patentee after: NANJING HANXIYUE AUTOMATION TECHNOLOGY Co.,Ltd. Address before: 211100 room 610, 266 Chuangyan Road, Qilin hi tech Industrial Development Zone, Jiangning District, Nanjing City, Jiangsu Province Patentee before: Nanjing kaimengshi Electronic Technology Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221129 Address after: 20th Floor, Building B, National Intellectual Property Creative Industry Pilot Park, No. 60 Guoji Road, Jinshui District, Zhengzhou City, Henan Province 450000 Patentee after: Henan Radio and Television Technology Co.,Ltd. Address before: 211100 300 Chi Hui Road, Qilin science and Technology Innovation Park, Jiangning District, Nanjing, Jiangsu Patentee before: NANJING HANXIYUE AUTOMATION TECHNOLOGY Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230116 Address after: No. 256, Chaoyang Road, Zhonghe Town, Shuangliu District, Chengdu, Sichuan, 610213 Patentee after: Li Zhengmao Address before: 20th Floor, Building B, National Intellectual Property Creative Industry Pilot Park, No. 60 Guoji Road, Jinshui District, Zhengzhou City, Henan Province 450000 Patentee before: Henan Radio and Television Technology Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230423 Address after: F130, 13th Floor, Building F, Huidong International, No. 16 Jinpu Road, Nanning City, Guangxi Zhuang Autonomous Region, 530000 Patentee after: Guangxi ouri Elevator Service Group Co.,Ltd. Address before: No. 256, Chaoyang Road, Zhonghe Town, Shuangliu District, Chengdu, Sichuan, 610213 Patentee before: Li Zhengmao |