CN110223350A - A kind of building blocks automatic sorting method and system based on binocular vision - Google Patents

A kind of building blocks automatic sorting method and system based on binocular vision Download PDF

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Publication number
CN110223350A
CN110223350A CN201910432830.4A CN201910432830A CN110223350A CN 110223350 A CN110223350 A CN 110223350A CN 201910432830 A CN201910432830 A CN 201910432830A CN 110223350 A CN110223350 A CN 110223350A
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Prior art keywords
building blocks
sorting
color
image
information
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包能胜
方海涛
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Shantou University
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Shantou University
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1694Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
    • B25J9/1697Vision controlled systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/70Determining position or orientation of objects or cameras
    • G06T7/73Determining position or orientation of objects or cameras using feature-based methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/90Determination of colour characteristics
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20024Filtering details
    • G06T2207/20032Median filtering

Abstract

The invention discloses a kind of building blocks automatic sorting method and system based on binocular vision, wherein this method comprises: being demarcated to camera;The building blocks on line conveyor are acquired by calibrated camera, generate building blocks figure;The building blocks figure is pre-processed, pretreated building blocks figure is obtained;Image conversion is carried out to the pretreated building blocks figure, determines the color of building blocks;Image after determining building blocks color is handled, spatial positional information locating for the building blocks is obtained;The picture of camera acquisition is handled, the building blocks information as sorting target is obtained;The spatial positional information and the building blocks information as sorting target are sent to robot and carry out building blocks sorting.In embodiments of the present invention, building blocks spatial position is identified using the method for binocular vision and automatically grab building blocks, realize the identification of building blocks in industrial building blocks production and automatically grabbed, to solve the problems, such as that low efficiency, accuracy rate are low in building blocks sorting.

Description

A kind of building blocks automatic sorting method and system based on binocular vision
Technical field
The present invention relates to industrial automation identification and technical field of machine vision more particularly to a kind of based on binocular vision Building blocks automatic sorting method and system.
Background technique
In industrial automation identification technology development process, workpiece sorting is a cumbersome job, initial sorting side Method is manual sorting, and the speed and accuracy of sorting both depend on proficiency of workers, tired degree and working attitude.Together When, the sorting of certain industries has certain risk or has strict demand to the sanitary conditions of sorting environment.Therefore, it realizes The sorting automation of workpiece has great importance.The accessory that type, shape, the color of building blocks are various and numerous also gives building blocks Sorting bring a great deal of trouble trouble.
Can the key that realize workpiece sorting automation be the specific location that accurately identify to grabbing workpiece, and quickly quasi- Really grab and place workpiece.In terms of non-cpntact measurement, mainly there are laser depth measurement, radar surveying etc..Laser measurement is Object is measured by high-frequency laser pluses, such mode is expensive, is not suitable for the three-dimensional localization to workpiece;Radar Ranging is then to analyze the identification that the reflected signal of target workpiece carries out distance by issuing radar signal, and the method is held Vulnerable to influence of noise, on the more workpiece sorting production line of noise and it is not suitable for.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, and the present invention provides a kind of building blocks based on binocular vision Automatic sorting method and system in the production of industrial building blocks, it can be achieved that the identification of building blocks and automatically grab, to solve building blocks sorting The low problem of middle low efficiency, accuracy rate.
To solve the above-mentioned problems, the invention proposes a kind of building blocks automatic sorting method based on binocular vision, it is described Method includes:
Camera is demarcated;
The building blocks on line conveyor are acquired by calibrated camera, generate building blocks figure;
The building blocks figure is pre-processed, pretreated building blocks figure is obtained;
Image conversion is carried out to the pretreated building blocks figure, determines the color of building blocks;
Image after determining building blocks color is handled, spatial positional information locating for the building blocks is obtained;
The picture of camera acquisition is handled, the building blocks information as sorting target is obtained;
The spatial positional information and the building blocks information as sorting target are sent to robot and carry out building blocks sorting.
Preferably, described the step of is carried out by image conversion, determines the color of building blocks for the pretreated building blocks figure, packet It includes:
HSV image is converted by RGB image to the pretreated building blocks figure;
The regularity of distribution according to building blocks in HSV space distinguishes the color of the building blocks in building blocks figure, determines building blocks Color.
Preferably, the image after described pair of determining building blocks color is handled, and obtains space bit confidence locating for the building blocks The step of breath, comprising:
Corresponding world coordinate system is calculated with the relationship of world coordinate system according to image coordinate system, obtains the building blocks institute The spatial positional information at place.
Preferably, the picture to camera acquisition is handled, and obtains the building blocks information as sorting target Step, comprising:
Simultaneously gray proces are corrected to the picture of camera acquisition, obtain gray scale picture;
The gray scale picture is handled, the building blocks of overlapping building blocks the top is chosen as sorting target, obtains conduct Sort the building blocks information of target.
Preferably, the described the step of building blocks figure is pre-processed, obtains pretreated building blocks figure, comprising:
The building blocks figure is pre-processed using median filter method, the building blocks figure after being filtered.
Correspondingly, the present invention also provides a kind of building blocks Automated Sorting System based on binocular vision, the system comprises:
Camera calibration module, for being demarcated to camera;
Image generation module generates building blocks figure for acquiring the building blocks on line conveyor by calibrated camera;
Preprocessing module obtains pretreated building blocks figure for pre-processing to the building blocks figure;
Color determination module determines the color of building blocks for carrying out image conversion to the pretreated building blocks figure;
Spatial position obtains module, for handling the image after determining building blocks color, obtains locating for the building blocks Spatial positional information;
Information determination module is sorted, the picture for acquiring to the camera is handled, and is obtained as sorting target Building blocks information;
Sending module, for by the spatial positional information and as sorting target building blocks information be sent to robot into The sorting of row building blocks.
Preferably, the color determination module includes:
Conversion unit, for being converted into HSV image by RGB image to the pretreated building blocks figure;
Discrimination unit carries out area to the color of the building blocks in building blocks figure for the regularity of distribution according to building blocks in HSV space Point, determine the color of building blocks.
Preferably, the spatial position obtains module and is also used to be calculated according to the relationship of image coordinate system and world coordinate system Corresponding world coordinate system out obtains spatial positional information locating for the building blocks.
Preferably, the sorting information determination module includes:
Gray scale processing unit, the picture for acquiring to the camera is corrected and gray proces, obtains gray scale picture;
Object selection unit chooses the building blocks conduct of overlapping building blocks the top for handling the gray scale picture Target is sorted, the building blocks information as sorting target is obtained.
Preferably, the preprocessing module is also used for median filter method and pre-processes to the building blocks figure, obtains Building blocks figure after must being filtered.
In embodiments of the present invention, building blocks spatial position is identified using the method for binocular vision and automatically grab building blocks, It realizes the identification of building blocks in industrial building blocks production and automatically grabs, to solve that low efficiency in building blocks sorting, accuracy rate is low asks Topic, and can continuously sort and not influenced by work human efficiency;Meanwhile it being combined using binocular vision and mechanical arm Mode, stability is high, at low cost, easy for installation.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the flow diagram of the building blocks automatic sorting method based on binocular vision of the embodiment of the present invention;
Fig. 2 is the flow diagram of the camera calibration of the embodiment of the present invention;
Fig. 3 is HSV model schematic in the embodiment of the present invention;
Fig. 4 is the structure composition schematic diagram of the building blocks Automated Sorting System based on binocular vision of the embodiment of the present invention.
Specific embodiment
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 description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall within the protection scope of the present invention.
Fig. 1 is the flow diagram of the building blocks automatic sorting method based on binocular vision of the embodiment of the present invention, such as Fig. 1 institute Show, this method comprises:
S1 demarcates camera;
S2 acquires the building blocks on line conveyor by calibrated camera, generates building blocks figure;
S3 pre-processes building blocks figure, obtains pretreated building blocks figure;
S4 carries out image conversion to pretreated building blocks figure, determines the color of building blocks;
S5 handles the image after determining building blocks color, obtains spatial positional information locating for the building blocks;
S6 handles the picture of camera acquisition, obtains the building blocks information as sorting target;
Spatial positional information and the building blocks information as sorting target are sent to robot and carry out building blocks sorting by S7.
In embodiments of the present invention, left and right camera is demarcated first, in Binocular Stereo Vision System, camera Calibration is primarily to solve the geometric parameter of camera, the inner parameter including camera model and the sky relative to target workpiece Between position external parameter.Three-dimensional information of the object in world coordinate system can be obtained by camera calibration.The present invention utilizes two dimension Scaling board carries out not having to angle and direction shooting, then carries out knowledge method for distinguishing to calibration.Calculated linear optimization Solution is carried out non-linear solution again by maximum likelihood method and obtains the parameter of camera.The flow chart of camera calibration is as shown in Figure 2: left, Right camera obtains picture respectively, completes the extraction of center picture point, respectively completes calibration, final to carry out double camera calibration.
In S3, it is preferable that pre-processed using median filter method to building blocks figure, the building blocks after being filtered Figure.
In specific implementation, to camera acquisition building blocks figure pre-process, can be used mean filter, gaussian filtering and in The methods of value filtering is pre-processed, and by comparison treated image, the processing result of median filter method is preferable, therefore, The present embodiment pre-processes building blocks image using median filtering.
S4 further comprises:
HSV image is converted by RGB image to pretreated building blocks figure;
The regularity of distribution according to building blocks in HSV space distinguishes the color of the building blocks in building blocks figure, determines building blocks Color.
In specific implementation, building blocks figure is converted into HSV image by RGB image, RGB (red, green, blue) is according to eye recognition The space that defines of color, can indicate most of color.But generally do not use rgb space because the component of rgb space with it is bright Spend closely related, as long as that is, brightness changes, 3 components all can correspondingly change therewith.HSV (hue, saturation, intensity) basis What the intuitive nature of color proposed, this space can react eyes for the sensing capability of color very well.Its model such as Fig. 3 institute Show.HSV model corresponds to a conical subset in cylindrical-coordinate system, and the top surface of circular cone corresponds to V=1.It includes RGB mould R=1 in type, G=1, tri- faces B=1, representative color are brighter.Color H around the rotation angle of V axis by giving.Red is corresponding In 0 ° of angle, green corresponds to 120 ° of angle, and blue corresponds to 240 ° of angle.In hsv color model, each color and it Complementary color differ 180 °.Saturation degree S value is from 0 to 1, so the radius of circular cone top surface is 1.
HSV space is converted to from rgb space.Its conversion formula is as follows:
R'=R/255;G'=G/255;B'=B/255;
Cmax=max (R', G', B');
Cmin=min (R', G', B');
Δ=Cmax-Cmin
V=Cmax
The value of color image RGB is Unit8 type originally, and the range of value is 0-255, for convenience of calculating, is converted into using RGB Double type, the range of value are 0-1, use R ', G ', B respectively ' it indicates, Cmax in formula, Cmin are respectively represented in (R ', G ', B ') Maximum value and minimum value after converting using rgb space, can carry out Threshold segmentation in information of the HSV space to H, S, V of image, So that it is determined that the different colours of building blocks.In specific implementation, according to building blocks HSV space the regularity of distribution, it is right in conjunction with Otsu algorithm The color of building blocks distinguishes in picture.The threshold value of various colors building blocks is as follows:
White: V > 0.88;S≤0.1;
Black: V≤0.18;
It is red: 9 π/5 < H≤2 π;V>0.18;S>0.17;
Green: 2 π/5 < H≤4 π/5;V>0.18;S>0.17;
Yellow: 3 π/10 < H≤2 π/5;V>0.18;S>0.17;
Blue: 10 π/9 < H≤4 π/3;V>0.18;S>0.17;
Wherein: H ∈ [0,2 π], V ∈ [0,1], S ∈ [0,1].
In S5, corresponding world coordinates is calculated with the relationship of world coordinate system according further to image coordinate system System, obtains spatial positional information locating for the building blocks.
By calculating the image analysis image coordinate system of acquisition, to calculate corresponding world coordinate system:
Wherein, (ul,vl),(ur,vr) it is coordinate value of the spatial point on the camera image of left and right;Ml,MrFor left and right camera Projection matrix, XW,YW,ZWFor the three-dimensional coordinate of spatial point to be asked, mlAnd mrRespectively MlAnd MrElement.To two formula simultaneous above Eliminate Zl,ZrIt can obtain:
Order matrix A is equal to:
Order matrix b is equal to:
Therefore:
AP=b
P=[XW YW ZW]T
The projection matrix of camera is it is known that if obtain (u after calibrationl,vl),(ur,vr) then according to least square method, P point can be obtained Coordinate:
P=(AA)-1ATb
Further, S6 includes:
Simultaneously gray proces are corrected to the picture of camera acquisition, obtain gray scale picture;
Gray scale picture is handled, the building blocks of overlapping building blocks the top is chosen as sorting target, obtains as sorting The building blocks information of target.
After the real space location information for obtaining building blocks through the above way, it is thus necessary to determine that the sorting sequence of building blocks, in product Before wood sorting process, it should first be determined which building blocks is building blocks to be sorted.By being re-shoot after sorting every time Image, to determine new building blocks to be sorted.It recycles according to this, completes sorting one by one.The present invention passes through the picture that two cameras obtain, After picture corrects, it is reconverted into gray scale picture, gray scale picture is handled respectively, chooses the product of overlapping building blocks the top Carpentery workshop is sorting target.Its process is as follows:
(1) based on picture gray value, its gray value is extended into 0~255 range;
(2) target area is split by the method that region increases, the region collection by gray value mean square deviation less than 5 Combination and segmentation comes out;
(3) mean value of the gray value in picture is calculated, and Threshold segmentation is carried out to image according to the size of mean value;
(4) screening that area is carried out to the region after Threshold segmentation, removes zone errors;
(5) maximum gradation value in the region that calculating sifting goes out.It is split using this gray value as threshold value, obtains maximum ash The region of angle value.Building blocks representated by this region are then building blocks to be sorted.
It in embodiments of the present invention, further include robot (mechanical arm) according to spatial positional information and work after S7 It automatically grabs building blocks to sort the building blocks information of target and is put into specified place.
In embodiments of the present invention, building blocks spatial position is identified using the method for binocular vision and automatically grab building blocks, It realizes the identification of building blocks in industrial building blocks production and automatically grabs, to solve that low efficiency in building blocks sorting, accuracy rate is low asks Topic, and can continuously sort and not influenced by work human efficiency;Meanwhile it being combined using binocular vision and mechanical arm Mode, stability is high, at low cost, easy for installation.
Correspondingly, the embodiment of the present invention also provides a kind of building blocks Automated Sorting System based on binocular vision, such as Fig. 4 institute Show, which includes:
Camera calibration module 1, for being demarcated to camera;
Image generation module 2 generates building blocks for acquiring the building blocks on line conveyor by calibrated camera Figure;
Preprocessing module 3 obtains pretreated building blocks figure for pre-processing to building blocks figure;
Color determination module 4 determines the color of building blocks for carrying out image conversion to pretreated building blocks figure;
Spatial position obtains module 5, for handling the image after determining building blocks color, obtains locating for the building blocks Spatial positional information;
Information determination module 6 is sorted, for handling the picture that camera acquires, obtains the building blocks as sorting target Information;
Sending module 7, for being sent to robot progress by spatial positional information and as the building blocks information for sorting target Building blocks sorting.
In embodiments of the present invention, left and right camera is demarcated first, in Binocular Stereo Vision System, camera Calibration is primarily to solve the geometric parameter of camera, the inner parameter including camera model and the sky relative to target workpiece Between position external parameter.Three-dimensional information of the object in world coordinate system can be obtained by camera calibration.The present invention utilizes two dimension Scaling board carries out not having to angle and direction shooting, then carries out knowledge method for distinguishing to calibration.Calculated linear optimization Solution is carried out non-linear solution again by maximum likelihood method and obtains the parameter of camera.
Preprocessing module 3 pre-processes building blocks figure using median filter method, the building blocks figure after being filtered.
Further, color determination module 4 includes:
Conversion unit, for being converted into HSV image by RGB image to pretreated building blocks figure;
Discrimination unit carries out area to the color of the building blocks in building blocks figure for the regularity of distribution according to building blocks in HSV space Point, determine the color of building blocks.
Specific color determination process can be found in the detailed description of S4 in embodiment of the method.
Further, spatial position obtains module 5 and is also used to be calculated according to the relationship of image coordinate system and world coordinate system Corresponding world coordinate system out obtains spatial positional information locating for the building blocks.Specific spatial position determination process can join See the detailed description of S5 in embodiment of the method.
Further, sorting information determination module 6 includes:
Gray scale processing unit obtains gray scale picture for being corrected simultaneously gray proces to the picture that camera acquires;
Object selection unit chooses the building blocks of overlapping building blocks the top as sorting for handling gray scale picture Target obtains the building blocks information as sorting target.
After the real space location information for obtaining building blocks through the above way, it is thus necessary to determine that the sorting sequence of building blocks, in product Before wood sorting process, it should first be determined which building blocks is building blocks to be sorted.By being re-shoot after sorting every time Image, to determine new building blocks to be sorted.It recycles according to this, completes sorting one by one.The present invention passes through the picture that two cameras obtain, After picture corrects, it is reconverted into gray scale picture, gray scale picture is handled respectively, chooses the product of overlapping building blocks the top Carpentery workshop is sorting target.Its process is as follows:
(1) based on picture gray value, its gray value is extended into 0~255 range;
(2) target area is split by the method that region increases, the region collection by gray value mean square deviation less than 5 Combination and segmentation comes out;
(3) mean value of the gray value in picture is calculated, and Threshold segmentation is carried out to image according to the size of mean value;
(4) screening that area is carried out to the region after Threshold segmentation, removes zone errors;
(5) maximum gradation value in the region that calculating sifting goes out.It is split using this gray value as threshold value, obtains maximum ash The region of angle value.Building blocks representated by this region are then building blocks to be sorted.
Specifically, the working principle of present system related function module can be found in the phase of the realization process of embodiment of the method Description is closed, which is not described herein again.
In present system embodiment, building blocks spatial position is identified using the method for binocular vision and automatically grabs product Wood is realized the identification of building blocks in industrial building blocks production and is automatically grabbed, so that it is low to solve low efficiency, accuracy rate in building blocks sorting Problem, and can continuously sort and not influenced by work human efficiency;Meanwhile using binocular vision and mechanical arm knot The mode of conjunction, stability is high, at low cost, easy for installation.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can It is completed with instructing relevant hardware by program, which can be stored in a computer readable storage medium, storage Medium may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), disk or CD etc..
In addition, be provided for the embodiments of the invention above building blocks automatic sorting method based on binocular vision and system into It has gone and has been discussed in detail, used herein a specific example illustrates the principle and implementation of the invention, the above implementation The explanation of example is merely used to help understand method and its core concept of the invention;Meanwhile for the general technology people of this field Member, according to the thought of the present invention, there will be changes in the specific implementation manner and application range, in conclusion this explanation Book content should not be construed as limiting the invention.

Claims (10)

1. a kind of building blocks automatic sorting method based on binocular vision, which is characterized in that the described method includes:
Camera is demarcated;
The building blocks on line conveyor are acquired by calibrated camera, generate building blocks figure;
The building blocks figure is pre-processed, pretreated building blocks figure is obtained;
Image conversion is carried out to the pretreated building blocks figure, determines the color of building blocks;
Image after determining building blocks color is handled, spatial positional information locating for the building blocks is obtained;
The picture of camera acquisition is handled, the building blocks information as sorting target is obtained;
The spatial positional information and the building blocks information as sorting target are sent to robot and carry out building blocks sorting.
2. the building blocks automatic sorting method based on binocular vision as described in claim 1, which is characterized in that described to described pre- The step of treated, and building blocks figure carries out image conversion, determines the color of building blocks, comprising:
HSV image is converted by RGB image to the pretreated building blocks figure;
The regularity of distribution according to building blocks in HSV space distinguishes the color of the building blocks in building blocks figure, determines the color of building blocks.
3. the building blocks automatic sorting method based on binocular vision as claimed in claim 1 or 2, which is characterized in that described to true The step of image after constant volume wood color is handled, obtains spatial positional information locating for the building blocks, comprising:
Corresponding world coordinate system is calculated with the relationship of world coordinate system according to image coordinate system, is obtained locating for the building blocks Spatial positional information.
4. the building blocks automatic sorting method based on binocular vision as described in claim 1, which is characterized in that described to the phase The step of picture of machine acquisition is handled, and the building blocks information as sorting target is obtained, comprising:
Simultaneously gray proces are corrected to the picture of camera acquisition, obtain gray scale picture;
The gray scale picture is handled, the building blocks of overlapping building blocks the top is chosen as sorting target, obtains as sorting The building blocks information of target.
5. the building blocks automatic sorting method based on binocular vision as described in claim 1, which is characterized in that described to the product The step of wooden figure is pre-processed, and pretreated building blocks figure is obtained, comprising:
The building blocks figure is pre-processed using median filter method, the building blocks figure after being filtered.
6. a kind of building blocks Automated Sorting System based on binocular vision, which is characterized in that the system comprises:
Camera calibration module, for being demarcated to camera;
Image generation module generates building blocks figure for acquiring the building blocks on line conveyor by calibrated camera;
Preprocessing module obtains pretreated building blocks figure for pre-processing to the building blocks figure;
Color determination module determines the color of building blocks for carrying out image conversion to the pretreated building blocks figure;
Spatial position obtains module, for handling the image after determining building blocks color, obtains space locating for the building blocks Location information;
Information determination module is sorted, the picture for acquiring to the camera is handled, and obtains the building blocks as sorting target Information;
Sending module, for the spatial positional information and building blocks information as sorting target to be sent to robot and accumulate Wood sorting.
7. the building blocks Automated Sorting System based on binocular vision as claimed in claim 6, which is characterized in that the color determines Module includes:
Conversion unit, for being converted into HSV image by RGB image to the pretreated building blocks figure;
Discrimination unit distinguishes the color of the building blocks in building blocks figure for the regularity of distribution according to building blocks in HSV space, really The color of constant volume wood.
8. the building blocks Automated Sorting System based on binocular vision as claimed in claim 6, which is characterized in that the spatial position It obtains module to be also used to calculate corresponding world coordinate system with the relationship of world coordinate system according to image coordinate system, be somebody's turn to do Spatial positional information locating for building blocks.
9. the building blocks Automated Sorting System based on binocular vision as claimed in claim 6, which is characterized in that the sorting information Determining module includes:
Gray scale processing unit, the picture for acquiring to the camera is corrected and gray proces, obtains gray scale picture;
Object selection unit chooses the building blocks of overlapping building blocks the top as sorting for handling the gray scale picture Target obtains the building blocks information as sorting target.
10. the building blocks Automated Sorting System based on binocular vision as claimed in claim 6, which is characterized in that the pretreatment Module is also used for median filter method and pre-processes to the building blocks figure, the building blocks figure after being filtered.
CN201910432830.4A 2019-05-23 2019-05-23 A kind of building blocks automatic sorting method and system based on binocular vision Pending CN110223350A (en)

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