CN110411530A - A kind of intelligent identification Method of container residual volume - Google Patents
A kind of intelligent identification Method of container residual volume Download PDFInfo
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- CN110411530A CN110411530A CN201910215638.XA CN201910215638A CN110411530A CN 110411530 A CN110411530 A CN 110411530A CN 201910215638 A CN201910215638 A CN 201910215638A CN 110411530 A CN110411530 A CN 110411530A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F17/00—Methods or apparatus for determining the capacity of containers or cavities, or the volume of solid bodies
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Abstract
The invention discloses a kind of intelligent identification Methods of container residual volume.It takes pictures first with camera and boxcar leading portion and most of bottom surface is included in image, camera internal parameter matrix M then is passed through to image1With distortion correction parameter k1、k2Carry out distortion correction.Image carries out example dividing processing in remote server compartment, identify region shared by each cargo and profile, it finally can determine the pixel coordinate of each characteristic point, the world coordinates of cargo characteristic point can be calculated by cargo characteristic point pixel coordinate, world coordinates can calculate the volume of cargo in compartment after determining.The present invention automatically understands the freight volume and spare space of each lorry convenient for logistics center's accurate quick, timely update cargo loading pattern, arranged rational scheduling is carried out to lorry, improve lorry remaining space and loading object to be installed mismatches caused logistic resources wasting phenomenon, improves the conevying efficiency of lorry.
Description
Technical field
The invention belongs to material handling management technical fields, and in particular to a kind of intelligent recognition side of container residual volume
Method.
Background technique
With the development of economy, logistics capacity is being gradually increased, especially in special red-letter day, to increase transport lorry
The freight volume of quantity and lorry.Cargo loading pattern influences whether the efficiency of loading of lorry, and then influences transportation cost, delivery
Period and resource utilization.So reasonable cargo loading pattern can bring bigger economic benefit to highway transportation.Currently,
Cargo loading pattern is formulated by logistics distribution center, the logistics center relatively low for intelligent construction degree, the utilization of resources and
Working efficiency is low, obtains quantity in stock and truckload and still manually reports to complete, especially truckload, works as object
When flow is huge, manual report is time-consuming and laborious, and is difficult to accurately estimate boxcar remaining space, and information processing is also very numerous
It is trivial, be easy to cause acquisition of information not in time, the problems such as error is big, bring problem to storehouse management and logistics transportation.
The present invention, which focuses on, provides a kind of method for identifying boxcar remaining space for logistics distribution, acquires goods using camera
Vehicle interior situation judges the volume for calculating stacked goods in boxcar by image, to obtain compartment remaining space
Volume, logistics center is passed to by network, the freight volume of each lorry is accurately and quickly understood convenient for logistics center, in time
Cargo loading pattern is updated, arranged rational scheduling is carried out to lorry, improves Freight Transport amount and is unevenly distributed and the remaining sky in compartment
Between with loading object to be installed mismatch cause logistic resources to waste the phenomenon that, improve the conevying efficiency of lorry, make transport truck
Allotment more convenient and quicker it is reasonable.
Summary of the invention
The present invention is directed to the status of logistics transportation, provides a kind of container residual volume recognition methods, it uses camera and figure
As the volume of processing technique calculating boxcar remaining space inside, data are transmitted using network, monitor logistics center in real time
The freight volume and residue of lorry can bearing capacity, it is convenient that lorry is carried out reasonable to arrange scheduling.
The purpose of the present invention is achieved through the following technical solutions: a kind of container residual volume recognition methods, including
Logistics center, camera, server.Server is connect with camera, logistics center, and server is image processing workstations, is acted on and is
Analyze image and transmitting data.The step of technical solution, is as follows:
The first step selects focal length that can carry out the camera of infrared night vision shooting suitably, under half-light environment, keeps camera clear
It is clear that completely boxcar leading portion and most of bottom surface are included in image.Camera carries wireless network, and camera can be by more
Kind mode is connect with server, such as mobile network GPRS, mobile phone hot spot WIFI or city wireless WIFI, is convenient for server pair
In the monitoring of camera, timely the angle of camera can be adjusted to perfect condition.
Second step calculates camera intrinsic parameter, and the camera internal of camera is needed when calculating by camera linear imaging model
Parameter matrix M1, therefore calculating instrument pair is used to the uncalibrated image of scaling board shooting certain amount different angle using camera
Uncalibrated image, which carries out processing, can be obtained camera internal parameter matrix M1With distortion correction parameter k1、k2, the distortion school that obtains herein
Positive parameter k1、k2With camera internal parameter matrix M1It will be used for the calculating of the distortion correction to all shooting images of camera.It utilizes
The distortion correction parameter k of acquisition1、k2Distortion correction is carried out to all uncalibrated images, the uncalibrated image after being corrected, then pass through
Tool carries out the calculating of inner parameter matrix, can obtain camera internal parameter matrix M1’。
Third step calculates camera external parameter, in order to realize the conversion by world coordinate system coordinate and image pixel coordinates
Also need to obtain camera external parameter matrix M2, camera external parameter matrix M2By the world coordinate system coordinate x of camera photocentrec0、
yc0、zc0This six parameters are determined with setting angle α, β, γ of camera.Since when camera is installed, camera photocentre is difficult to really
Fixed, the setting angle of camera is influenced by installation accuracy and is difficult to measure, it is therefore desirable to be determined outside camera by calculating to obtain
Portion parameter matrix M2Six parameters, and then determine camera external parameter matrix M2.First to do not include cargo empty wagons compartment in clap
Taking the photograph a photo or shooting has the image of complete compartment profile, and carries out distortion correction to image, then passes through deep learning
The profile information for obtaining compartment determines compartment characteristic point, obtains camera external parameter matrix M by optimization computation2。
4th step, measurement of cargo identification calculates in compartment, completes to install in camera and has obtained M1、M1’、M2、k1、k2Deng
It can be calculated into measurement of cargo identification in compartment after parameter.Camera takes pictures to interior, then passes through M to image1And k1、
k2Distortion correction is carried out, after image is corrected, correcting image is transferred to remote server.It is docked in remote server
Image carries out example dividing processing in the compartment received, and identifies region shared by each cargo and profile, finally can determine each characteristic point
Pixel coordinate, the world coordinates of cargo characteristic point can be calculated by cargo characteristic point pixel coordinate, world coordinates can after determining
To calculate the volume of cargo in compartment.
It is preferred that camera starts to take pictures after chamber door is shut in compartment, it is ensured that compartment characteristic point in scheme operation
It is accurate complete, so as to calculate accurate camera external parameter matrix M2。
It is preferred that the camera of infrared night vision shooting can be carried out by being chosen under half-light environment, and it be furnished with flash lamp, In
When ambient black shoots also unintelligible using infrared night vision in compartment, camera automatic identification when taking pictures enables flash lamp.
It is preferred that since camera is mounted in compartment, with the operation of lorry, setting angle α, β, γ of camera
With the world coordinate system coordinate x of camera photocentrec0、yc0、zc0Subtle change, this six parameters can occur due to jolting or colliding
Variation can change camera external parameter matrix M2, finally will affect the result of entire scheme.Therefore, periodically camera should be carried out
The world coordinates of repair and maintenance, the setting angle and camera photocentre that guarantee camera is fixed, to camera external parameter matrix M2In time
Amendment.Lorry uneven for transit route can be arranged on camera and shake alarm, and the shaking range of a permission is arranged,
It goes beyond the scope once super with regard to alarm, signal is sent to logistics center, logistics center sends staff to handle in time to pacify again
Fill fixing camera.
The invention has the benefit that logistics center can monitor the useful load and traffic condition of each lorry in real time, side
Just arrangement scheduling is carried out to lorry, the lorry that freight volume can be arranged in time few goes to other warehouses to load cargo, improves lorry
Conevying efficiency keeps the allotment more convenient and quicker of transport truck reasonable.Meanwhile method for distinguishing is known to judge using space geometry
Lorry space is than artificial more accurate and more efficient, various mistakes caused by can also avoiding due to artificial.
Detailed description of the invention
Fig. 1 is flow diagram of the invention；
Fig. 2 is each coordinate system of camera linear imaging model；
Arrangement of Fig. 3 coordinate system in compartment；
Fig. 4 is compartment front end features point；
Fig. 5 is cargo image in compartment；
Fig. 6 is the identification of cargo feature；
Specific embodiment
Present invention is further described in detail with reference to the accompanying drawing.
It is linear using camera present invention relates particularly to a kind of container residual volume recognition methods based on space geometry identification
Imaging model, pixel in two dimensional image coordinate system captured by the coordinate and camera by the object under three-dimensional scenic coordinate system into
Row connection.The conversion being related between a variety of coordinate systems in camera linear imaging model, including world coordinate system OW-XWYWZW, phase
Machine coordinate system OC-XCYCZC, image physical coordinates system O1- xy and image pixel coordinates system O0-uv.It is each in camera linear imaging model
Coordinate system is as shown in Figure 1.Arrangement of each coordinate system in compartment is as shown in Figure 2.
World coordinate system O is arranged in the simulation compartment of 2200mm wide 1250mm high 1750mm one longW-XWYWZW, camera
Coordinate system OC-XCYCZC, image physical coordinates system O1- xy and image pixel coordinates system O0- uv, camera installation site world coordinates is about
For (0,2100,1650).The geological information of cargo in compartment profile and compartment can be led to by world coordinate system visual representation
It crosses translation matrix and the conversion of world coordinate system to camera coordinates system may be implemented in spin matrix, then pass through the similar original of triangle
Reason can convert camera coordinates system to image physical coordinates system, then pass through following formula
Image pixel coordinates system is converted by image physical coordinates system.Therefore, world coordinate system can be converted by following formula
For image pixel coordinates system.
In formula: fx、fyPixel focal length respectively on the direction u, v；M1Referred to as camera internal parameter matrix, inner parameter
Matrix is determined by focal length, the principal point coordinate etc. of camera, is just had determined or using tool in camera production to calibration maps
It can be obtained inner parameter matrix M as carrying out processing1；M2The referred to as external parameter matrix of camera, by camera in world coordinate system
In installation site setting angle determine, after camera install in compartment determination.
Using camera to the uncalibrated image of scaling board shooting certain amount different angle, uncalibrated image is passed through using tool
Following formula
Carrying out processing can be obtained camera internal parameter matrix M1With distortion correction parameter k1、k2, the distortion school that obtains herein
Positive parameter k1、k2With camera internal parameter matrix M1It will be used for the calculating of the distortion correction to all shooting images of camera.It utilizes
The distortion correction parameter k of acquisition1、k2Distortion correction is carried out to all uncalibrated images, the uncalibrated image after being corrected, then pass through
Calculating instrument carries out the calculating of inner parameter matrix, can obtain camera internal parameter matrix M1' be shown below.
In order to realize that the conversion by world coordinate system coordinate and image pixel coordinates also needs to obtain camera external parameter square
Battle array M2, camera external parameter matrix M2By the world coordinate system coordinate x of camera photocentrec0、yc0、zc0With setting angle α, β of camera,
This six parameters of γ are determined.Since when camera is installed, camera photocentre is difficult to determine, the setting angle of camera is by installation accuracy
Influence and be difficult to measure, it is therefore desirable to pass through calculate obtain determine camera external parameter matrix M2Six parameters, in turn
Determine camera external parameter matrix M2.There is entire vehicle to one photo of shooting in the empty wagons compartment for not including cargo or shooting first
The image of compartment profile, and distortion correction is carried out to image, the image after correction is as shown in figure 3, in an experiment by artificial direct
It determines characteristic point, finally can determine that each characteristic point pixel coordinate is respectively as follows: P1(1598,1643), P2(2383,1646), P3
(1336,220), P4(2599,220).Camera external parameter matrix M is set first2Initial value, six parameters are respectively xc0
=0, yc0=2090, zc0=1620, α=35, β=0, γ=0.The world coordinates of four characteristic points is brought into the world respectively to sit
Mark is converted into the formula of image pixel coordinates, wherein P1W(-625、0、0)、P2W(625、0、0)、P3W(-625、0、1750)、P4W
(- 625,0,1750), camera internal parameter matrix are M1', it can get in current M2Under characteristic point pixel coordinate P1’(u1, v1)、
P2’(u2, v2)、P3’(u3, v3)、P4’(u4, v4).Following formula
It is minimised as target, to camera external parameter matrix M2Six parameters carry out optimization computation.X can finally be obtainedc0
=64, yc0=2125, zc0=1649, α=34.65, β=- 1, γ=0.51.M2It is shown below.
It completes to install in camera and has obtained M1、M1’、M2、k1、k2Etc. can be into compartment (board house) interior cargo after parameters
Volume identification calculates.Cargo used by testing is the carton of long 420mm wide 210mm high 560mm, certain edge of carton exists
Carton is placed on different location in board house with different disposing ways by certain deformation, is recorded cargo when putting every time and is existed
Position in compartment has taken 22 pictures, as shown in Figure 4 altogether.
M is passed through to image1And k1、k2Distortion correction is carried out, after image is corrected, correcting image is transferred to distal end
Server.Example dividing processing is carried out to image in the compartment of receiving in remote server, identifies region shared by each cargo
With profile, as shown in Figure 5.Hereafter the edge for the cargo area being partitioned into is identified, 1 hexahedron cargo is needed
Identify the two principal outline line line1 and line2 and three characteristic point P of cargo1、P2、P3, finally can determine each feature
The pixel coordinate of point.It is M in known camera internal parameter matrix1', camera external parameter matrix is M2And object is in the picture
Pixel coordinate u, v when, for P1With P2Point is located at the z in its world coordinates of groundw=0, admittedly P can be solved1With P2The generation of point
Boundary coordinate xw、ywValue, can find out cargo rear end (y at a distance from compartment front endw1+yw2)/2 and cargo are along XWThe length in direction
xw2-xw1.Due to P1Point and P3The world coordinates x of pointw、ywBe worth it is identical, in known P1Point world coordinates xw1、yw1Value and P3Point is being schemed
Pixel coordinate u as in3、v3When, the formula that image pixel coordinates can be converted by world coordinates finds out P3The world of point is sat
Mark zw3, cargo can be found out along ZWThe height degree z in directionw3.The world coordinates of known each characteristic point of cargo can calculate shipment
The volume of object.
22 captured pictures are analyzed and can be obtained, by image to cargo cargo XWDirection length and cargo ZWSide
Prediction to height all has lesser relative error, to cargo cargo XWThe prediction maximum relative error of direction length is only
1.83%, to cargo ZWThe prediction maximum relative error of direction height is only 1.56%, and to cargo rear end and compartment front end
In the prediction of distance, occurring biggish relative error in the experiment that number is 18 is 7.28%, in addition to this second largest mistake
Difference is 3.9%.Calculating for volume, due to number be 18 experiment in cargo rear end occur at a distance from compartment front end it is larger
Error, so that the relative error calculated under this condition volume has reached 7.55%, in addition to this calculating of volume is second largest
Error is 5.31%, and the average value for the relative error that the volume of this 22 kinds of cargo placement positions calculates is 2.31%.
Claims (4)
1. a kind of intelligent identification Method of container residual volume, it is characterized in that it the following steps are included:
The first step selects focal length that can carry out the camera of infrared night vision shooting suitably, under half-light environment, keeps camera clear complete
Whole is included in boxcar leading portion and most of bottom surface in image.Camera carries wireless network, and camera can pass through a variety of sides
Formula is connect with server, such as mobile network GPRS, mobile phone hot spot WIFI or city wireless WIFI, convenient for server for taking the photograph
As the monitoring of head, timely the angle of camera can be adjusted to perfect condition.
Second step calculates camera intrinsic parameter, and the camera internal parameter of camera is needed when calculating by camera linear imaging model
Matrix M1, therefore using camera to the uncalibrated image of scaling board shooting certain amount different angle, using calculating instrument to calibration
Image, which carries out processing, can be obtained camera internal parameter matrix M1With distortion correction parameter k1、k2, obtain herein distortion correction ginseng
Number k1、k2With camera internal parameter matrix M1It will be used for the calculating of the distortion correction to all shooting images of camera.Utilize acquisition
Distortion correction parameter k1、k2Distortion correction is carried out to all uncalibrated images, the uncalibrated image after being corrected, then pass through tool
The calculating for carrying out inner parameter matrix, can obtain camera internal parameter matrix M1’。
Third step calculates camera external parameter, in order to realize that the conversion by world coordinate system coordinate and image pixel coordinates also needs
Obtain camera external parameter matrix M2, camera external parameter matrix M2By the world coordinate system coordinate x of camera photocentrec0、yc0、zc0
This six parameters are determined with setting angle α, β, γ of camera.Since when camera is installed, camera photocentre is difficult to determine, camera
Setting angle influenced by installation accuracy and be difficult to measure, it is therefore desirable to pass through calculate obtain determine camera external parameter square
Battle array M2Six parameters, and then determine camera external parameter matrix M2.First to do not include cargo empty wagons compartment in shoot a Zhang Zhao
Piece or shooting have the image of complete compartment profile, and carry out distortion correction to image, then obtain compartment by deep learning
Profile information determine compartment characteristic point, pass through optimization computation obtain camera external parameter matrix M2。
4th step, measurement of cargo identification calculates in compartment, completes to install in camera and has obtained M1、M1’、M2、k1、k2Etc. parameters
After can into compartment measurement of cargo identification calculate.Camera takes pictures to interior, then passes through M to image1And k1、k2Into
Line distortion correction, after image is corrected, correcting image is transferred to remote server.To receiving in remote server
Image carries out example dividing processing in compartment, identifies region shared by each cargo and profile, finally can determine the picture of each characteristic point
Plain coordinate, the world coordinates of cargo characteristic point can be calculated by cargo characteristic point pixel coordinate, and world coordinates can be counted after determining
Calculate the volume of cargo in compartment.
2. a kind of intelligent identification Method of container residual volume based on space geometry identification according to claim 1,
It is characterized in that: the conversion being related between a variety of coordinate systems in camera linear imaging model, including world coordinate system OW-XWYWZW、
Camera coordinates system OC-XCYCZC, image physical coordinates system O1- xy and image pixel coordinates system O0-uv.The world can be sat by following formula
Mark system coordinate (xc,yc,zc) it is converted into image pixel coordinates (u, v).
Wherein fx、fyPixel focal length respectively on the direction u, v；M1Referred to as camera internal parameter matrix, inner parameter matrix by
Focal length, principal point coordinate of camera etc. determine, and it just has determined when camera produces；M2The referred to as external parameter of camera
Matrix is determined by installation site setting angle of the camera in world coordinate system, is determined after camera is installed in compartment.
3. a kind of intelligent identification Method of container residual volume based on space geometry identification according to claim 1,
It is characterized in that: the external parameter matrix M of camera2By the world coordinate system coordinate x of camera photocentrec0、yc0、zc0With the installation of camera
Angle [alpha], β, γ this six parameters are determined, since the position of camera is monitored in real-time, so external parameter matrix M2
It can also be adjusted at any time.Camera in view of being mounted on compartment top may be jolted due to vehicle driving, or be touched
Touching causes camera photocentre and setting angle to change, therefore can periodically or detect in compartment when not having cargo, shooting
Image zooming-out characteristic point in compartment, to M2It is recalculated, and when detection discovery camera photocentre and setting angle changed
When big, capable of emitting notice request reinstalls fixing camera.
4. a kind of intelligent identification Method of container residual volume based on space geometry identification according to claim 1,
Be characterized in that: after shooting image is corrected, correction image is transferred to remote server.To receiving in remote server
Compartment in image carry out example dividing processing, identify region shared by each cargo and profile.
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|---|---|---|---|---|
| CN110827967A (en) * | 2019-11-14 | 2020-02-21 | 邓莉 | Platform, method and storage medium for identifying space occupation proportion of pharmacy |
| CN111652558A (en) * | 2020-06-05 | 2020-09-11 | 联想(北京)有限公司 | Object loading implementation method, device and system and computer equipment |
| WO2021197345A1 (en) * | 2020-03-30 | 2021-10-07 | 长沙智能驾驶研究院有限公司 | Method and apparatus for measuring remaining volume in closed space on basis of laser radar |
| CN113542392A (en) * | 2021-07-12 | 2021-10-22 | 安徽大学 | Cold chain vehicle operation environment monitoring method based on wireless communication |
| CN113869810A (en) * | 2020-06-30 | 2021-12-31 | 华晨宝马汽车有限公司 | Method, device, equipment and logistics system for determining number of transported objects |
| CN115170650A (en) * | 2022-07-11 | 2022-10-11 | 深圳市平方科技股份有限公司 | Container vehicle-mounted position identification method and device, electronic equipment and storage medium |
| CN115907600A (en) * | 2022-12-29 | 2023-04-04 | 广州捷世通物流股份有限公司 | Reverse logistics transportation method and system based on Internet of things |
| CN116307985A (en) * | 2023-03-06 | 2023-06-23 | 中天建设集团有限公司 | Energy-saving transportation method for building materials, computer equipment and medium |
| CN117764468A (en) * | 2023-12-06 | 2024-03-26 | 广州港股份有限公司 | Intelligent loading and plugging line control method and system based on Internet of things and machine vision |
| CN117910905A (en) * | 2024-01-30 | 2024-04-19 | 镇江全通供应链管理有限公司 | Intelligent management system for object transportation |
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| CN110827967A (en) * | 2019-11-14 | 2020-02-21 | 邓莉 | Platform, method and storage medium for identifying space occupation proportion of pharmacy |
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| CN113542392B (en) * | 2021-07-12 | 2024-05-03 | 安徽大学 | Cold chain vehicle operation environment monitoring method based on wireless communication |
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| CN115170650A (en) * | 2022-07-11 | 2022-10-11 | 深圳市平方科技股份有限公司 | Container vehicle-mounted position identification method and device, electronic equipment and storage medium |
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| CN116307985B (en) * | 2023-03-06 | 2024-01-26 | 北京中天北方建设有限公司 | Energy-saving transportation method for building materials, computer equipment and medium |
| CN116307985A (en) * | 2023-03-06 | 2023-06-23 | 中天建设集团有限公司 | Energy-saving transportation method for building materials, computer equipment and medium |
| CN117764468A (en) * | 2023-12-06 | 2024-03-26 | 广州港股份有限公司 | Intelligent loading and plugging line control method and system based on Internet of things and machine vision |
| CN117910905A (en) * | 2024-01-30 | 2024-04-19 | 镇江全通供应链管理有限公司 | Intelligent management system for object transportation |
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Application publication date: 20191105 |