CN108537834A - A kind of volume measuring method, system and depth camera based on depth image - Google Patents
A kind of volume measuring method, system and depth camera based on depth image Download PDFInfo
- Publication number
- CN108537834A CN108537834A CN201810225912.7A CN201810225912A CN108537834A CN 108537834 A CN108537834 A CN 108537834A CN 201810225912 A CN201810225912 A CN 201810225912A CN 108537834 A CN108537834 A CN 108537834A
- Authority
- CN
- China
- Prior art keywords
- coordinate
- determinand
- point cloud
- depth
- scene
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention belongs to logistics and volume measurement techniques field, and in particular to a kind of volume measuring method, system and depth camera based on depth image include the following steps：S1 obtains the scene depth figure containing determinand, obtains scene point cloud coordinate；S2 converts scene point cloud coordinate, obtains the scene point cloud coordinate under depth camera coordinate system；S3 handles the scene point cloud coordinate under depth camera coordinate system, obtains the coordinate set of determinand；S4 calculates length, width and the height of determinand according to the coordinate set of determinand, and length, width are multiplied to obtain the volume of determinand with height.The present invention can be realized, cost is relatively low compared to existing flow volume measurement scheme in hardware aspect with depth camera common on the market；Under camera heeling condition, it still is able to the volume of real-time and accurate measurement determinand.
Description
Technical field
The invention belongs to logistics and volume measurement techniques field, and in particular to a kind of cubing side based on depth image
Method, system and depth camera.
Background technology
In recent years, with the fast development of economic globalization, a large amount of goods and materials need between zones frequently flowing, especially
It is the rise of the e-commerce generated along with information technology revolution so that logistic industry is drastically developed rapidly, logistics
Competition between enterprise is also growing more intense, and how to reduce human cost, and it is that acquirement competition is excellent that express mail, which is efficiently sent to destination,
The key of gesture.
In logistics and warehousing management, the volume attribute of article optimizes receive storage, sorting, packaging and hair to logistics center
Fortune management is most important, therefore realizes accurately measuring for automation by size, the volume to article, can greatly improve stored goods
The efficiency of stream and the intelligence of logistics system and automatization level.
Existing cubing equipment is scanned based on light curtain or linear array laser, it is necessary to coordinate conveyer belt encoder ability
Calculate volume.This technology is although more mature, but expensive, and system complexity is higher.
Invention content
For the defects in the prior art, the volume measuring method that the present invention provides a kind of based on depth image, system
And depth camera, compared to existing flow volume measurement scheme, in hardware aspect, utilization common depth camera on the market
It realizes, cost is relatively low；Under camera heeling condition, it still is able to the volume of real-time and accurate measurement determinand.
In a first aspect, the present invention provides a kind of volume measuring method based on depth image, include the following steps：
S1 obtains the scene depth figure containing determinand, obtains scene point cloud coordinate；
S2 converts scene point cloud coordinate, obtains the scene point cloud coordinate under depth camera coordinate system；
S3 handles the scene point cloud coordinate under depth camera coordinate system, obtains the coordinate set of determinand；
S4 calculates length, width and the height of determinand according to the coordinate set of determinand, by length, width and height
Multiplication obtains the volume of determinand.
Preferably, the step S2 is specially：
S21, the reference planes in scene set depth map；
S22 calculates the lateral attitude data of depth camera according to the reference planes；
S23 converts scene point cloud coordinate according to lateral attitude data, obtains under depth camera coordinate system
Scene point cloud coordinate.
Preferably, the S22 is specially：
S221, setting depth camera X-axis, the angular range of Y-axis and reference planes normal, if including in the angular range
Dry X-axis angle thetaxWith with Y-axis angle thetay；
S222 traverses each X-axis angle and each Y-axis angle, using coordinate transform formula in reference planes
ZCKCoordinate is converted, and the Z after several transformation is obtainedCKCoordinate, the transformation for mula are：
Z'=Y0*sinθx+Z0cosθx；
Zck=Z'*cos θy-X0sinθy；
Wherein X0、Y0、Z0For the original coordinates point of reference planes, ZCKFor the Z after transformationCKCoordinate；
S223 calculates the Z after all transformationCKThe average value Zmean and minimum variance Zsigma of coordinate；
S224, by the corresponding X-axis angle thetas of minimum variance ZsigmaxX-axis slanted angle α as depth camerax, corresponding
Y-axis angle thetayY-axis slanted angle α as depth cameray, to obtain lateral attitude data：ZCKThe average value of coordinate
Zmean, minimum variance Zsigma, X-axis slanted angle αxWith Y-axis slanted angle αy。
Preferably, the S23 is specially：
According to X-axis slanted angle αxWith Y-axis slanted angle αy, scene point cloud coordinate is converted using transformation for mula, is obtained
Scene point cloud coordinate under to depth camera coordinate system, transformation for mula are：
Z'i=Yio*sinαx+Ziocosαx；
Xi=Z'i*sinαy+Xiocosαy；
Yi=Yio*cosαy-Ziosinαy；
Zi=Z'i*cosαy-Xiosinαy；
Wherein Xio、Yio、ZioFor original scene point cloud coordinate, Xi、Yi、ZiFor the scene point cloud under depth camera coordinate system
Coordinate.
Preferably, the S3 is specially：
According to screening formula qualified determinand is filtered out from the scene cloud coordinate under depth camera coordinate system
Xi、Yi、ZiCoordinate point set, screening formula are：
| Zi-Zmean | ＞ N*Zsigma, wherein N are positive number.
Preferably, the S4 is specially：
S41 calculates the X of determinand according to preset grid precisioni、YiCoordinate points project to corresponding net in reference planes
Lattice region carries out connected region calibration to net region and counts each connected region size；
S42 chooses the corresponding X of the maximum connected region of areai、YiCoordinate point set is calculated by Principal Component Analysis and is selected
The X takeni、YiThe corresponding minimum bounding rectangle of coordinate points, obtains the length and width that determinand projects in reference planes；
S43 calculates ZiThe height of determinand is obtained with Zmean maximum differences, length, width are multiplied with height and waited for
Survey object product.
Second aspect, the present invention provides a kind of volume measuring systems based on depth image, are suitable for first aspect institute
The volume measuring method based on depth image stated, including：
Scene collecting unit obtains scene point cloud coordinate for obtaining the scene depth figure containing determinand；
Coordinate transformation unit obtains the scene point under depth camera coordinate system for being converted to scene point cloud coordinate
Cloud coordinate；
Determinand extraction unit obtains to be measured for handling the scene point cloud coordinate under depth camera coordinate system
The coordinate set of object；
Volume computing unit, length, width and height for calculating determinand according to the coordinate set of determinand, will grow
Degree, width are multiplied to obtain the volume of determinand with height.
The third aspect, the present invention provides a kind of depth cameras, including processor, input equipment, output equipment and storage
Device, the processor, input equipment, output equipment and memory are connected with each other, and the memory is used to store computer program,
The computer program includes program instruction, and the processor is configured for calling described program instruction, executes such as first party
Method described in face.
Beneficial effects of the present invention are：Compared to existing flow volume measurement scheme, in hardware aspect, utilization is general on the market
Logical depth camera can be realized, and cost is relatively low；Under camera heeling condition, it still is able to the body of real-time and accurate measurement determinand
Product.
Description of the drawings
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art are briefly described.In all the appended drawings, similar element
Or part is generally identified by similar reference numeral.In attached drawing, each element or part might not be drawn according to actual ratio.
Fig. 1 is the flow chart of the volume measuring method based on depth image in the present embodiment；
Fig. 2 is the structure chart of the volume measuring system based on depth image in the present embodiment.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
It should be appreciated that ought use in this specification and in the appended claims, term " comprising " and "comprising" instruction
Described feature, entirety, operation, the presence of element and/or component, but one or more of the other feature, entirety, behaviour is not precluded
The presence or addition of work, element, component and/or its set.
It is also understood that the term used in this description of the invention is merely for the sake of the mesh for describing specific embodiment
And be not intended to limit the present invention.As description of the invention and it is used in the attached claims, unless on
Other situations are hereafter clearly indicated, otherwise " one " of singulative, "one" and "the" are intended to include plural form.
It will be further appreciated that the term "and/or" used in description of the invention and the appended claims is
Refer to any combinations and all possible combinations of one or more of associated item listed, and includes these combinations.
Embodiment one：
Present embodiments provide a kind of volume measuring method based on depth image, as shown in Figure 1, including following S1, S2,
S3, S4 totally four steps：
S1 obtains the scene depth figure containing determinand, obtains scene point cloud coordinate.The present embodiment obtains scene depth figure
Light time-of-flight, structure light principle, binocular range measurement principle etc. can be used.The coordinate set of depth map, that is, depth Z axis, depth
Figure is also referred to as range image, refers to the figure by the distance (depth) of each point in from image acquisition device to scene as pixel value
Picture, it directly reflects the geometry of each object visible surface in scene.Depth map may be calculated field by coordinate conversion
The image acquisition device of scape point cloud data, the present embodiment is depth camera, and depth camera sampling depth figure can apply the light flight time
Principle, structure light principle, binocular range measurement principle etc..
S2 converts scene point cloud coordinate, obtains the scene point cloud coordinate under depth camera coordinate system.
The step S2 specifically includes S21, S22, S23 totally three steps：
S21, the reference planes in scene set depth map.
S22 calculates the lateral attitude data of depth camera according to the reference planes.The S22 specifically include S221,
S222, S223, S224 totally four steps：
S221, setting depth camera X-axis, the angular range of Y-axis and reference planes normal, if including in the angular range
Dry X-axis angle thetaxWith with Y-axis angle thetay；
S222 traverses each X-axis angle and each Y-axis angle, using coordinate transform formula in reference planes
ZCKCoordinate is converted, and the Z after several transformation is obtainedCKCoordinate, the transformation for mula are：
Z'=Y0*sinθx+Z0cosθx；
Zck=Z'*cos θy-X0sinθy；
Wherein X0、Y0、Z0For the original coordinates point of reference planes, ZCKFor the Z after transformationCKCoordinate；
S223 calculates the Z after all transformationCKThe average value Zmean and minimum variance Zsigma of coordinate；
S224, by the corresponding X-axis angle thetas of minimum variance ZsigmaxX-axis slanted angle α as depth camerax, corresponding
Y-axis angle thetayY-axis slanted angle α as depth cameray, to obtain lateral attitude data：ZCKThe average value of coordinate
Zmean, minimum variance Zsigma, X-axis slanted angle αxWith Y-axis slanted angle αy。
In the present embodiment according to step S22 obtain the X-axis angle of depth camera and reference planes, Y-axis angle and with ginseng
Examine the distance of plane.
S23 converts scene point cloud coordinate according to lateral attitude data, obtains the scene under depth camera coordinate system
Point cloud coordinate.This step is specially：
According to X-axis slanted angle αxWith Y-axis slanted angle αy, scene point cloud coordinate is converted using transformation for mula, is obtained
Scene point cloud coordinate under to depth camera coordinate system, transformation for mula are：
Z'i=Yio*sinαx+Ziocosαx；
Xi=Z'i*sinαy+Xiocosαy；
Yi=Yio*cosαy-Ziosinαy；
Zi=Z'i*cosαy-Xiosinαy；
Wherein Xio、Yio、ZioFor original scene point cloud coordinate, Xi、Yi、ZiFor the scene point cloud under depth camera coordinate system
Coordinate.
S3 handles the scene point cloud coordinate under depth camera coordinate system, obtains the coordinate set of determinand.This step
It is rapid to be specially：
According to screening formula qualified determinand is filtered out from the scene cloud coordinate under depth camera coordinate system
Xi、Yi、ZiCoordinate point set, screening formula are：
| Zi-Zmean | ＞ N*Zsigma, wherein N are positive number.
The present embodiment step S3 is the relevant information for removing other objects in scene, extracts the number of coordinates of determinand
According to.
S4 calculates length, width and the height of determinand according to the coordinate set of determinand, by length, width and height
Multiplication obtains the volume of determinand.The S4 specifically includes two steps of S41, S42：
S41 calculates the X of determinand according to preset grid precisioni、YiCoordinate points project to corresponding net in reference planes
Lattice region carries out connected region calibration to net region and counts each connected region size；
S42 chooses the corresponding X of the maximum connected region of areai、YiCoordinate point set is calculated by Principal Component Analysis and is selected
The X takeni、YiThe corresponding minimum bounding rectangle of coordinate points, obtains the length and width that determinand projects in reference planes；
S43 calculates ZiThe height of determinand is obtained with Zmean maximum differences, length, width are multiplied with height and waited for
Survey the volume of object.
In conclusion the present embodiment is compared to existing flow volume measurement scheme, in hardware aspect, utilization is common on the market
Depth camera can be realized, cost is relatively low；Under camera heeling condition, it still is able to the volume of real-time and accurate measurement determinand.
The present embodiment shifts to an earlier date calibration for cameras lateral attitude, only needs multiplication, connected region calibration and principal component analysis in the process of running
Etc. committed steps, you can calculate the length, width and height of determinand, and then calculate determinand volume, can reach it is extraordinary measure it is real-time
Property.The present embodiment is supported to exist when camera installation and be tilted, and measurement range is easily installed and expands.Many high-precisions on existing market
The point cloud of depth camera output is non-structured, and the present embodiment does not require the structuring of point cloud data (point cloud coordinate),
Therefore it is easier to make for measuring apparatus type selecting.
Embodiment two：
A kind of volume measuring system based on depth image is present embodiments provided, as shown in Fig. 2, including：
Scene collecting unit obtains scene point cloud coordinate for obtaining the scene depth figure containing determinand；
Coordinate transformation unit obtains the scene point under depth camera coordinate system for being converted to scene point cloud coordinate
Cloud coordinate；
Determinand extraction unit obtains to be measured for handling the scene point cloud coordinate under depth camera coordinate system
The coordinate set of object；
Volume computing unit, length, width and height for calculating determinand according to the coordinate set of determinand, will grow
Degree, width are multiplied to obtain the volume of determinand with height.
This system be suitable for embodiment one described in the volume measuring method based on depth image, as shown in Figure 1, include with
Lower S1, S2, S3, S4 totally four steps：
S1 obtains the scene depth figure containing determinand, obtains scene point cloud coordinate.The present embodiment obtains scene depth figure
Light time-of-flight, structure light principle, binocular range measurement principle etc. can be used.The coordinate set of depth map, that is, depth Z axis, depth
Figure is also referred to as range image, refers to the figure by the distance (depth) of each point in from image acquisition device to scene as pixel value
Picture, it directly reflects the geometry of each object visible surface in scene.Depth map may be calculated field by coordinate conversion
The image acquisition device of scape point cloud data, the present embodiment is depth camera, and depth camera sampling depth figure can apply the light flight time
Principle, structure light principle, binocular range measurement principle etc..
S2 converts scene point cloud coordinate, obtains the scene point cloud coordinate under depth camera coordinate system.
The step S2 specifically includes S21, S22, S23 totally three steps：
S21, the reference planes in scene set depth map.
S22 calculates the lateral attitude data of depth camera according to the reference planes.The S22 specifically include S221,
S222, S223, S224 totally four steps：
S221, setting depth camera X-axis, the angular range of Y-axis and reference planes normal, if including in the angular range
Dry X-axis angle thetaxWith with Y-axis angle thetay；
S222 traverses each X-axis angle and each Y-axis angle, using coordinate transform formula in reference planes
ZCKCoordinate is converted, and the Z after several transformation is obtainedCKCoordinate, the transformation for mula are：
Z'=Y0*sinθx+Z0cosθx；
Zck=Z'*cos θy-X0sinθy；
Wherein X0、Y0、Z0For the original coordinates point of reference planes, ZCKFor the Z after transformationCKCoordinate；
S223 calculates the Z after all transformationCKThe average value Zmean and minimum variance Zsigma of coordinate；
S224, by the corresponding X-axis angle thetas of minimum variance ZsigmaxX-axis slanted angle α as depth camerax, corresponding
Y-axis angle thetayY-axis slanted angle α as depth cameray, to obtain lateral attitude data：ZCKThe average value of coordinate
Zmean, minimum variance Zsigma, X-axis slanted angle αxWith Y-axis slanted angle αy。
In the present embodiment according to step S22 obtain the X-axis angle of depth camera and reference planes, Y-axis angle and with ginseng
Examine the distance of plane.
S23 converts scene point cloud coordinate according to lateral attitude data, obtains the scene under depth camera coordinate system
Point cloud coordinate.This step is specially：
According to X-axis slanted angle αxWith Y-axis slanted angle αy, scene point cloud coordinate is converted using transformation for mula, is obtained
Scene point cloud coordinate under to depth camera coordinate system, transformation for mula are：
Z'i=Yio*sinαx+Ziocosαx；
Xi=Z'i*sinαy+Xiocosαy；
Yi=Yio*cosαy-Ziosinαy；
Zi=Z'i*cosαy-Xiosinαy；
Wherein Xio、Yio、ZioFor original scene point cloud coordinate, Xi、Yi、ZiFor the scene point cloud under depth camera coordinate system
Coordinate.
S3 handles the scene point cloud coordinate under depth camera coordinate system, obtains the coordinate set of determinand.This step
It is rapid to be specially：
According to screening formula qualified determinand is filtered out from the scene cloud coordinate under depth camera coordinate system
Xi、Yi、ZiCoordinate point set, screening formula are：
| Zi-Zmean | ＞ N*Zsigma, wherein N are positive number.
The present embodiment step S3 is the relevant information for removing other objects in scene, extracts the number of coordinates of determinand
According to.
S4 calculates length, width and the height of determinand according to the coordinate set of determinand, by length, width and height
Multiplication obtains the volume of determinand.The S4 specifically includes two steps of S41, S42：
S41 calculates the X of determinand according to preset grid precisioni、YiCoordinate points project to corresponding net in reference planes
Lattice region carries out connected region calibration to net region and counts each connected region size；
S42 chooses the corresponding X of the maximum connected region of areai、YiCoordinate point set is calculated by Principal Component Analysis and is selected
The X takeni、YiThe corresponding minimum bounding rectangle of coordinate points, obtains the length and width that determinand projects in reference planes；
S43 calculates ZiThe height of determinand is obtained with Zmean maximum differences, length, width are multiplied with height and waited for
Survey the volume of object.
In conclusion the present embodiment is compared to existing flow volume measurement scheme, in hardware aspect, utilization is common on the market
Depth camera can be realized, cost is relatively low；Under camera heeling condition, it still is able to the volume of real-time and accurate measurement determinand.
The present embodiment shifts to an earlier date calibration for cameras lateral attitude, only needs multiplication, connected region calibration and principal component analysis in the process of running
Etc. committed steps, you can calculate the length, width and height of determinand, and then calculate determinand volume, can reach it is extraordinary measure it is real-time
Property.The present embodiment is supported to exist when camera installation and be tilted, and measurement range is easily installed and expands.Many high-precisions on existing market
The point cloud of depth camera output is non-structured, and the present embodiment does not require the structuring of point cloud data (point cloud coordinate),
Therefore it is easier to make for measuring apparatus type selecting.
Those of ordinary skill in the art may realize that lists described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and method and step, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware
With the interchangeability of software, each exemplary composition and step are generally described according to function in the above description.This
A little functions are implemented in hardware or software actually, depend on the specific application and design constraint of technical solution.Specially
Industry technical staff can use different methods to achieve the described function each specific application, but this realization is not
It is considered as beyond the scope of this invention.
In several embodiments provided herein, it should be understood that disclosed method and system can pass through it
Its mode is realized.For example, in addition the division of the above unit, only a kind of division of logic function can have in actual implementation
Dividing mode, such as multiple units or component can be combined or can be integrated into another system or some features can be with
Ignore, or does not execute.Said units may or may not be physically separated, and the component shown as unit can be with
It is or may not be physical unit, you can be located at a place, or may be distributed over multiple network units.It can
The purpose of the embodiment of the present invention is realized to select according to the actual needs some or all of unit therein.
Embodiment three：
A kind of depth camera, including processor, input equipment, output equipment and memory are present embodiments provided, it is described
Processor, input equipment, output equipment and memory are connected with each other, and the memory is for storing computer program, the meter
Calculation machine program includes program instruction, and the processor is configured for calling described program instruction, executes described in embodiment one
Method.
The present embodiment is compared to existing flow volume measurement scheme, in hardware aspect, utilization common depth phase on the market
Machine can be realized, and cost is relatively low；Under camera heeling condition, it still is able to the volume of real-time and accurate measurement determinand.The present embodiment
Calibration for cameras lateral attitude in advance only needs multiplication, the key steps such as connected region calibration and principal component analysis in the process of running
Suddenly, you can calculate the length, width and height of determinand, and then calculate determinand volume, extraordinary measurement real-time can be reached.This reality
It applies example and supports there is inclination when camera installation, be easily installed and expand measurement range.Many high accuracy depth phases on existing market
The point cloud of machine output is non-structured, and the present embodiment does not require the structuring of point cloud data (point cloud coordinate), therefore more
It is easy to measure lectotype selection.
It should be appreciated that in the present embodiment, alleged processor can be central processing unit (Central Processing
Unit, CPU), which can also be other general processors, digital signal processor (Digital Signal
Processor, DSP), it is application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), existing
At programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete
Door or transistor logic, discrete hardware components etc..General processor can be that microprocessor or the processor also may be used
To be any conventional processor etc..
Input equipment may include image capture device, and output equipment may include display (LCD etc.), loud speaker etc..
The memory may include read-only memory and random access memory, and provide instruction and data to processor.
The a part of of memory can also include nonvolatile RAM.For example, memory can be with storage device type
Information.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme should all cover in the claim of the present invention and the range of specification.
Claims (8)
1. a kind of volume measuring method based on depth image, which is characterized in that include the following steps：
S1 obtains the scene depth figure containing determinand, obtains scene point cloud coordinate；
S2 converts scene point cloud coordinate, obtains the scene point cloud coordinate under depth camera coordinate system；
S3 handles the scene point cloud coordinate under depth camera coordinate system, obtains the coordinate set of determinand；
S4 calculates length, width and the height of determinand according to the coordinate set of determinand, and length, width are multiplied with height
Obtain the volume of determinand.
2. a kind of volume measuring method based on depth image according to right 1, which is characterized in that the step S2 is specific
For：
S21, the reference planes in scene set depth map；
S22 calculates the lateral attitude data of depth camera according to the reference planes；
S23 converts scene point cloud coordinate according to lateral attitude data, obtains the scene point cloud under depth camera coordinate system
Coordinate.
3. a kind of volume measuring method based on depth image according to claim 2, which is characterized in that the S22 tools
Body is：
S221, setting depth camera X-axis, the angular range of Y-axis and reference planes normal, the interior angular range includes several
X-axis angle thetaxWith with Y-axis angle thetay；
S222 traverses each X-axis angle and each Y-axis angle, using coordinate transform formula to the Z in reference planesCKIt sits
Mark is converted, and the Z after several transformation is obtainedCKCoordinate, the transformation for mula are：
Z'=Y0*sinθx+Z0cosθx；
Zck=Z'*cos θy-X0sinθy；
Wherein X0、Y0、Z0For the original coordinates point of reference planes, ZCKFor the Z after transformationCKCoordinate；
S223 calculates the Z after all transformationCKThe average value Zmean and minimum variance Zsigma of coordinate；
S224, by the corresponding X-axis angle thetas of minimum variance ZsigmaxX-axis slanted angle α as depth camerax, corresponding Y-axis
Angle thetayY-axis slanted angle α as depth cameray, to obtain lateral attitude data：ZCKThe average value Zmean of coordinate, most
Small variance Zsigma, X-axis slanted angle αxWith Y-axis slanted angle αy。
4. a kind of volume measuring method based on depth image according to claim 3, which is characterized in that the S23 tools
Body is：
According to X-axis slanted angle αxWith Y-axis slanted angle αy, scene point cloud coordinate is converted using transformation for mula, obtains depth
The scene point cloud coordinate under camera coordinates system is spent, transformation for mula is：
Z'i=Yio*sinαx+Ziocosαx；
Xi=Z'i*sinαy+Xiocosαy；
Yi=Yio*cosαy-Ziosinαy；
Zi=Z'i*cosαy-Xiosinαy；
Wherein Xio、Yio、ZioFor original scene point cloud coordinate, Xi、Yi、ZiIt is sat for the scene point cloud under depth camera coordinate system
Mark.
5. a kind of volume measuring method based on depth image according to claim 4, which is characterized in that the S3 is specific
For：
According to screening formula the X of qualified determinand is filtered out from the scene cloud coordinate under depth camera coordinate systemi、
Yi、ZiCoordinate point set, screening formula are：
| Zi-Zmean | ＞ N*Zsigma, wherein N are positive number.
6. a kind of volume measuring method based on depth image according to claim 5, which is characterized in that the S4 is specific
For：
S41 calculates the X of determinand according to preset grid precisioni、YiCoordinate points project to corresponding grid regions in reference planes
Domain carries out connected region calibration to net region and counts each connected region size；
S42 chooses the corresponding X of the maximum connected region of areai、YiCoordinate point set calculates selection by Principal Component Analysis
Xi、YiThe corresponding minimum bounding rectangle of coordinate points, obtains the length and width that determinand projects in reference planes；
S43 calculates ZiThe height of determinand is obtained with Zmean maximum differences, length, width are multiplied to obtain determinand with height
Volume.
7. a kind of volume measuring system based on depth image is suitable for claim 1-6 any one of them and is based on depth map
The volume measuring method of picture, including：
Scene collecting unit obtains scene point cloud coordinate for obtaining the scene depth figure containing determinand；
Coordinate transformation unit, for being converted to scene point cloud coordinate, the scene point cloud obtained under depth camera coordinate system is sat
Mark；
Determinand extraction unit obtains determinand for handling the scene point cloud coordinate under depth camera coordinate system
Coordinate set；
Volume computing unit, the length, width and height for calculating determinand according to the coordinate set of determinand, length, width and height are multiplied to obtain
The volume of determinand.
8. a kind of depth camera, which is characterized in that including processor, input equipment, output equipment and memory, the processing
Device, input equipment, output equipment and memory are connected with each other, and the memory is for storing computer program, the computer
Program includes program instruction, which is characterized in that the processor is configured for calling described program instruction, executes as right is wanted
Seek 1-6 any one of them methods.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810225912.7A CN108537834B (en) | 2018-03-19 | 2018-03-19 | Volume measurement method and system based on depth image and depth camera |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810225912.7A CN108537834B (en) | 2018-03-19 | 2018-03-19 | Volume measurement method and system based on depth image and depth camera |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108537834A true CN108537834A (en) | 2018-09-14 |
| CN108537834B CN108537834B (en) | 2020-05-01 |
Family
ID=63484983
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810225912.7A Active CN108537834B (en) | 2018-03-19 | 2018-03-19 | Volume measurement method and system based on depth image and depth camera |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108537834B (en) |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109376791A (en) * | 2018-11-05 | 2019-02-22 | 北京旷视科技有限公司 | Depth arithmetic accuracy calculation method, device, electronic equipment, readable storage medium storing program for executing |
| CN109448045A (en) * | 2018-10-23 | 2019-03-08 | 南京华捷艾米软件科技有限公司 | Plane polygon object measuring method and machine readable storage medium based on SLAM |
| CN109587875A (en) * | 2018-11-16 | 2019-04-05 | 厦门盈趣科技股份有限公司 | A kind of intelligent desk lamp and its adjusting method |
| CN109631764A (en) * | 2018-11-22 | 2019-04-16 | 南京理工大学 | Size Measuring System and method based on RealSense camera |
| CN109886961A (en) * | 2019-03-27 | 2019-06-14 | 重庆交通大学 | Medium-and-large-sized measurement of cargo measurement method based on depth image |
| CN109916302A (en) * | 2019-03-27 | 2019-06-21 | 青岛小鸟看看科技有限公司 | A kind of volume measuring method and system of freight container |
| CN109993785A (en) * | 2019-03-27 | 2019-07-09 | 青岛小鸟看看科技有限公司 | A kind of container volume measuring method and depth camera mould group |
| CN110006343A (en) * | 2019-04-15 | 2019-07-12 | Oppo广东移动通信有限公司 | Measurement method, device and the terminal of object geometric parameter |
| CN110296747A (en) * | 2019-08-12 | 2019-10-01 | 深圳市知维智能科技有限公司 | The measurement method and system of the volume of storage content |
| CN110310459A (en) * | 2019-04-04 | 2019-10-08 | 桑尼环保（江苏）有限公司 | Multi-parameter extract real-time system |
| CN110309561A (en) * | 2019-06-14 | 2019-10-08 | 吉旗物联科技（上海）有限公司 | Goods space volume measuring method and device |
| CN110349205A (en) * | 2019-07-22 | 2019-10-18 | 杭州光珀智能科技有限公司 | A kind of measurement method and device of object volume |
| CN110425980A (en) * | 2019-08-12 | 2019-11-08 | 深圳市知维智能科技有限公司 | The measurement method and system of the volume of storage facilities content |
| CN110766744A (en) * | 2019-11-05 | 2020-02-07 | 北京华捷艾米科技有限公司 | MR volume measurement method and device based on 3D depth camera |
| CN111095024A (en) * | 2018-09-18 | 2020-05-01 | 深圳市大疆创新科技有限公司 | Height determination method, height determination device, electronic equipment and computer-readable storage medium |
| CN111561872A (en) * | 2020-05-25 | 2020-08-21 | 中科微至智能制造科技江苏股份有限公司 | Method, device and system for measuring package volume based on speckle coding structured light |
| CN111696152A (en) * | 2020-06-12 | 2020-09-22 | 杭州海康机器人技术有限公司 | Method, device, computing equipment, system and storage medium for detecting package stacking |
| CN111986250A (en) * | 2019-05-22 | 2020-11-24 | 顺丰科技有限公司 | Object volume measuring method, device, measuring equipment and storage medium |
| CN112254635A (en) * | 2020-09-23 | 2021-01-22 | 洛伦兹（北京）科技有限公司 | Volume measurement method, device and system |
| CN113418467A (en) * | 2021-06-16 | 2021-09-21 | 厦门硅谷动能信息技术有限公司 | Method for detecting general and black luggage size based on ToF point cloud data |
| CN114264277A (en) * | 2021-12-31 | 2022-04-01 | 英特尔产品（成都）有限公司 | Method and device for detecting flatness abnormality of chip substrate |
| CN114494404A (en) * | 2022-02-14 | 2022-05-13 | 云从科技集团股份有限公司 | Object volume measurement method, system, device and medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7037263B2 (en) * | 2003-08-20 | 2006-05-02 | Siemens Medical Solutions Usa, Inc. | Computing spatial derivatives for medical diagnostic imaging methods and systems |
| CN101266131A (en) * | 2008-04-08 | 2008-09-17 | 长安大学 | Volume measurement device based on image and its measurement method |
| CN106225678A (en) * | 2016-09-27 | 2016-12-14 | 北京正安维视科技股份有限公司 | Dynamic object based on 3D camera location and volume measuring method |
| CN106813568A (en) * | 2015-11-27 | 2017-06-09 | 阿里巴巴集团控股有限公司 | object measuring method and device |
| CN106839975A (en) * | 2015-12-03 | 2017-06-13 | 杭州海康威视数字技术股份有限公司 | Volume measuring method and its system based on depth camera |
| CN107067394A (en) * | 2017-04-18 | 2017-08-18 | 中国电子科技集团公司电子科学研究院 | A kind of oblique photograph obtains the method and device of point cloud coordinate |
-
2018
- 2018-03-19 CN CN201810225912.7A patent/CN108537834B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7037263B2 (en) * | 2003-08-20 | 2006-05-02 | Siemens Medical Solutions Usa, Inc. | Computing spatial derivatives for medical diagnostic imaging methods and systems |
| CN101266131A (en) * | 2008-04-08 | 2008-09-17 | 长安大学 | Volume measurement device based on image and its measurement method |
| CN106813568A (en) * | 2015-11-27 | 2017-06-09 | 阿里巴巴集团控股有限公司 | object measuring method and device |
| CN106839975A (en) * | 2015-12-03 | 2017-06-13 | 杭州海康威视数字技术股份有限公司 | Volume measuring method and its system based on depth camera |
| CN106225678A (en) * | 2016-09-27 | 2016-12-14 | 北京正安维视科技股份有限公司 | Dynamic object based on 3D camera location and volume measuring method |
| CN107067394A (en) * | 2017-04-18 | 2017-08-18 | 中国电子科技集团公司电子科学研究院 | A kind of oblique photograph obtains the method and device of point cloud coordinate |
Non-Patent Citations (6)
| Title |
|---|
| BREWIN,MA ET AL: "《Accuracy of scaling and DLT reconstruction techniques for planar motion analyses》", 《JOURNAL OF APPLIED BIOMECHANICS》 * |
| D DOYLE ET AL: "《Optical flow background estimation for real-time pan/tilt camera object tracking》", 《MEASUREMENT》 * |
| 丁亚林: "《基于像面旋转的画幅遥感相机姿态像移计算》", 《光学精密工程》 * |
| 丁亚林: "《应用数学坐标变换方法计算航空相机像面旋转》", 《光学仪器》 * |
| 丁立军: "《基于摄影原理的文物表面纹理重建技术研究》", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 翟林培: "《考虑飞机姿态角时倾斜航空相机像移速度计算》", 《光学精密工程》 * |
Cited By (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111095024A (en) * | 2018-09-18 | 2020-05-01 | 深圳市大疆创新科技有限公司 | Height determination method, height determination device, electronic equipment and computer-readable storage medium |
| CN109448045A (en) * | 2018-10-23 | 2019-03-08 | 南京华捷艾米软件科技有限公司 | Plane polygon object measuring method and machine readable storage medium based on SLAM |
| CN109376791A (en) * | 2018-11-05 | 2019-02-22 | 北京旷视科技有限公司 | Depth arithmetic accuracy calculation method, device, electronic equipment, readable storage medium storing program for executing |
| CN109376791B (en) * | 2018-11-05 | 2020-11-24 | 北京旷视科技有限公司 | Depth algorithm precision calculation method and device, electronic equipment and readable storage medium |
| CN109587875A (en) * | 2018-11-16 | 2019-04-05 | 厦门盈趣科技股份有限公司 | A kind of intelligent desk lamp and its adjusting method |
| CN109631764A (en) * | 2018-11-22 | 2019-04-16 | 南京理工大学 | Size Measuring System and method based on RealSense camera |
| CN109886961A (en) * | 2019-03-27 | 2019-06-14 | 重庆交通大学 | Medium-and-large-sized measurement of cargo measurement method based on depth image |
| CN109916302A (en) * | 2019-03-27 | 2019-06-21 | 青岛小鸟看看科技有限公司 | A kind of volume measuring method and system of freight container |
| CN109993785A (en) * | 2019-03-27 | 2019-07-09 | 青岛小鸟看看科技有限公司 | A kind of container volume measuring method and depth camera mould group |
| CN109886961B (en) * | 2019-03-27 | 2023-04-11 | 重庆交通大学 | Medium and large cargo volume measuring method based on depth image |
| CN109993785B (en) * | 2019-03-27 | 2020-11-17 | 青岛小鸟看看科技有限公司 | Method for measuring volume of goods loaded in container and depth camera module |
| CN110310459A (en) * | 2019-04-04 | 2019-10-08 | 桑尼环保（江苏）有限公司 | Multi-parameter extract real-time system |
| CN110006343A (en) * | 2019-04-15 | 2019-07-12 | Oppo广东移动通信有限公司 | Measurement method, device and the terminal of object geometric parameter |
| US12117284B2 (en) | 2019-04-15 | 2024-10-15 | Guangdong Oppo Mobile Telecommunications Corp. Ltd. | Method and apparatus for measuring geometric parameter of object, and terminal |
| CN111986250A (en) * | 2019-05-22 | 2020-11-24 | 顺丰科技有限公司 | Object volume measuring method, device, measuring equipment and storage medium |
| CN111986250B (en) * | 2019-05-22 | 2024-08-20 | 顺丰科技有限公司 | Object volume measuring method, device, measuring equipment and storage medium |
| CN110309561A (en) * | 2019-06-14 | 2019-10-08 | 吉旗物联科技（上海）有限公司 | Goods space volume measuring method and device |
| CN110349205B (en) * | 2019-07-22 | 2021-05-28 | 浙江光珀智能科技有限公司 | Method and device for measuring volume of object |
| CN110349205A (en) * | 2019-07-22 | 2019-10-18 | 杭州光珀智能科技有限公司 | A kind of measurement method and device of object volume |
| CN110296747A (en) * | 2019-08-12 | 2019-10-01 | 深圳市知维智能科技有限公司 | The measurement method and system of the volume of storage content |
| CN110425980A (en) * | 2019-08-12 | 2019-11-08 | 深圳市知维智能科技有限公司 | The measurement method and system of the volume of storage facilities content |
| CN110766744A (en) * | 2019-11-05 | 2020-02-07 | 北京华捷艾米科技有限公司 | MR volume measurement method and device based on 3D depth camera |
| CN110766744B (en) * | 2019-11-05 | 2022-06-10 | 北京华捷艾米科技有限公司 | MR volume measurement method and device based on 3D depth camera |
| CN111561872A (en) * | 2020-05-25 | 2020-08-21 | 中科微至智能制造科技江苏股份有限公司 | Method, device and system for measuring package volume based on speckle coding structured light |
| CN111696152A (en) * | 2020-06-12 | 2020-09-22 | 杭州海康机器人技术有限公司 | Method, device, computing equipment, system and storage medium for detecting package stacking |
| CN112254635A (en) * | 2020-09-23 | 2021-01-22 | 洛伦兹（北京）科技有限公司 | Volume measurement method, device and system |
| CN112254635B (en) * | 2020-09-23 | 2022-06-28 | 洛伦兹（北京）科技有限公司 | Volume measurement method, device and system |
| CN113418467A (en) * | 2021-06-16 | 2021-09-21 | 厦门硅谷动能信息技术有限公司 | Method for detecting general and black luggage size based on ToF point cloud data |
| CN114264277A (en) * | 2021-12-31 | 2022-04-01 | 英特尔产品（成都）有限公司 | Method and device for detecting flatness abnormality of chip substrate |
| CN114494404A (en) * | 2022-02-14 | 2022-05-13 | 云从科技集团股份有限公司 | Object volume measurement method, system, device and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108537834B (en) | 2020-05-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108537834A (en) | A kind of volume measuring method, system and depth camera based on depth image | |
| US10268917B2 (en) | Pre-segment point cloud data to run real-time shape extraction faster | |
| CN104048744B (en) | A kind of contactless real-time online vibration measurement method based on image | |
| CN104052976B (en) | Projecting method and device | |
| CN110174056A (en) | A kind of object volume measurement method, device and mobile terminal | |
| CN110503718B (en) | Three-dimensional engineering model lightweight display method | |
| US8587586B2 (en) | Electronic device and method for meshing curved surface | |
| JP2015156136A (en) | Calculation device, method and program | |
| CN111159451B (en) | Power line point cloud dynamic monomer method based on spatial database | |
| Kucheruk et al. | Definition of dynamic characteristics of pointer measuring devices on the basis of automatic indications determination | |
| CN115063473A (en) | Object height detection method and device, computer equipment and storage medium | |
| CN108107471A (en) | The acquisition methods and device of a kind of point of orientation first arrival data volume | |
| CN110435154A (en) | For the image processing method of 3D printing, device, electronic equipment and storage medium | |
| CN109492573A (en) | A kind of pointer read method and device | |
| CN111985266B (en) | Scale map determining method, device, equipment and storage medium | |
| US20230228883A1 (en) | Z-plane identification and box dimensioning using three-dimensional time-of-flight imaging | |
| CN109000560B (en) | Method, device and equipment for detecting package size based on three-dimensional camera | |
| US8630477B2 (en) | Electronic device and method for outputting measurement data | |
| CN111915666A (en) | Volume measurement method and device based on mobile terminal | |
| CN112907164A (en) | Object positioning method and device | |
| CN114882059A (en) | Dimension measuring method, device and equipment based on image analysis and storage medium | |
| CN115456983A (en) | Water surface floater detection method, system, equipment and medium | |
| CN108278988A (en) | Measure the method and device of blade area | |
| JP2005043135A (en) | Method and apparatus for setting building data of air diffusion simulation system | |
| Mundhenk et al. | PanDAR: a wide-area, frame-rate, and full color lidar with foveated region using backfilling interpolation upsampling |
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 | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A volume measurement method, system and depth camera based on depth image Effective date of registration: 20220412 Granted publication date: 20200501 Pledgee: Zhejiang Mintai Commercial Bank Co.,Ltd. Hangzhou Binjiang small and micro enterprise franchise sub branch Pledgor: HANGZHOU AIXIN INTELLIGENT TECHNOLOGY CO.,LTD. Registration number: Y2022330000495 |