CN110296992A - It is a kind of that rear wild cabbage inside and outside quality detection evaluating apparatus is adopted based on machine vision - Google Patents
It is a kind of that rear wild cabbage inside and outside quality detection evaluating apparatus is adopted based on machine vision Download PDFInfo
- Publication number
- CN110296992A CN110296992A CN201910751500.1A CN201910751500A CN110296992A CN 110296992 A CN110296992 A CN 110296992A CN 201910751500 A CN201910751500 A CN 201910751500A CN 110296992 A CN110296992 A CN 110296992A
- Authority
- CN
- China
- Prior art keywords
- wild cabbage
- quality detection
- machine vision
- roller
- evaluating apparatus
- 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.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 83
- 235000001169 Brassica oleracea var oleracea Nutrition 0.000 title claims abstract description 74
- 235000006008 Brassica napus var napus Nutrition 0.000 title claims abstract description 72
- 241001674939 Caulanthus Species 0.000 title claims abstract description 72
- 230000007246 mechanism Effects 0.000 claims abstract description 29
- 238000000034 method Methods 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims abstract description 6
- 238000013441 quality evaluation Methods 0.000 claims abstract description 5
- 230000000694 effects Effects 0.000 claims abstract description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000009434 installation Methods 0.000 claims description 3
- 230000002265 prevention Effects 0.000 claims description 3
- 238000003466 welding Methods 0.000 claims description 3
- 238000009966 trimming Methods 0.000 abstract description 4
- 230000001105 regulatory effect Effects 0.000 abstract description 2
- 238000011156 evaluation Methods 0.000 description 6
- 239000007787 solid Substances 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 240000007124 Brassica oleracea Species 0.000 description 2
- 235000003899 Brassica oleracea var acephala Nutrition 0.000 description 2
- 235000011301 Brassica oleracea var capitata Nutrition 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 235000012055 fruits and vegetables Nutrition 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000012856 packing Methods 0.000 description 2
- 241001062009 Indigofera Species 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000009987 spinning Methods 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000036642 wellbeing Effects 0.000 description 1
Classifications
-
- 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
- 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
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/255—Details, e.g. use of specially adapted sources, lighting or optical systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8806—Specially adapted optical and illumination features
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
- G01N2021/0106—General arrangement of respective parts
- G01N2021/0112—Apparatus in one mechanical, optical or electronic block
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention discloses a kind of to adopt rear wild cabbage inside and outside quality detection evaluating apparatus, including rack, the adjusted device being arranged on the rack, Quality Detection mechanism, motor and side plate based on machine vision.Motor is driven by sprocket wheel chain drives adjusted device at the uniform velocity to advance, while roller realizes rotary motion under rack-and-pinion side effect;Wild cabbage is acted on roller by frictional force and is rolled, because itself mono-symmetry characteristic realizes tuning operation;Subsequent wild cabbage enters Quality Detection mechanism, CCD camera, which is controlled, by photo-sensor signal completes comprehensive image acquisition, and then the appearance quality detections such as size, color and damage are carried out by image processing techniques, and inside quality prediction is carried out by prediction model on this basis, it is finally completed the quality evaluation for adopting rear wild cabbage.The present invention realizes the automatic direction regulating of wild cabbage and quickly, nondestructively inside and outside quality detects, and improves operating efficiency, and provide foundation for subsequent trimming and graded operation.
Description
Technical field
The present invention relates to after a kind of postharvest fruit and vegetable Quality Detection technical field more particularly to a kind of adopting based on machine vision
Wild cabbage inside and outside quality detects evaluating apparatus.
Background technique
China's wild cabbage cultivated area and yield rank first in the world, but due to lacking commercialized treatment after adopting, farmer's
Economic well-being of workers and staff is not satisfactory.With society and economic fast development, the consumption concept of resident also gradually turns to " green safe "
Become, and with the increase of the market demand and the support of national policy, selling by grade is rebuild after adopting and has been increasingly becoming market fruits and vegetables
The Main Patterns of sale.
Currently, wild cabbage rebuilds key technology after adopting and associated equipment research is gradually carried out, but it is wild cabbage sphere size, tight
The parameter differences such as solidity are larger, inevitably, need to carry out detection evaluation to the inside and outside quality for adopting rear wild cabbage.Due to there is not yet
Correlative study report improves detection rates quickly, nondestructively to carry out Cabbage Quality detection evaluation, needs to design one kind and is based on
Machine vision adopts rear wild cabbage inside and outside quality detection evaluating apparatus, while also emulating for subsequent trimming graded operation and wild cabbage
The research of model provides foundation.
Summary of the invention
To solve the above-mentioned problems, the present invention provides a kind of, and the rear wild cabbage inside and outside quality detection of adopting based on machine vision is commented
Valence device, the invention combination wild cabbage own physical characteristic and trimming graded operation demand are led in the structure basis of orderly tuning
It crosses machine vision technique and can realize and adopt the quick of rear Cabbage Quality, non-destructive testing and evaluation.
To achieve the goals above, the present invention provides a kind of, and the rear wild cabbage inside and outside quality detection of adopting based on machine vision is commented
Valence device, including rack, the adjusted device being arranged on the rack, Quality Detection mechanism, motor and side plate;Motor passes through sprocket chain
Item transmission drives adjusted device at the uniform velocity to advance, while roller realizes rotary motion under rack-and-pinion side effect;Wild cabbage is rubbed
Power is acted on roller and is rolled, because itself mono-symmetry characteristic realizes tuning operation;Subsequent wild cabbage enters Quality Detection mechanism, leads to
It crosses photo-sensor signal control vertical view CCD camera and side view CCD camera is completed comprehensive image and obtained, and then pass through image
Processing technique carries out the appearance quality detections such as size, color and damage, and carries out interior component by prediction model on this basis
Matter prediction, is finally completed the quality evaluation for adopting rear wild cabbage.
It is advanced optimized as of the invention, the adjusted device is provided with several equally distributed rollers, adjacent roller
Minimum spacing be 70mm, to guarantee that wild cabbage is not fallen out on roller.
It is advanced optimized as of the invention, the gear coaxial welding that the roller two sides are fixed with bearing with inside is solid
Fixed, gear is engaged with the rack gear being symmetrically arranged on the frame, and realizes the rotary motion of roller;And pass through roller fixing axle and chain
Connector is fixedly connected with chain, realizes the at the uniform velocity advance of roller.
It is advanced optimized as of the invention, the Quality Detection mechanism is provided with symmetrical shield, shield
Fixation is bolted with rack, with detection box by being welded and fixed, and at the top of detection box bottom and shield between
Gap is zero.
It is advanced optimized as of the invention, the Quality Detection mechanism is provided with detection box, positioned at the upper of shield
Side, the rear of rack gear.
It is advanced optimized as of the invention, the Quality Detection mechanism is provided at the top of detection box and side
LED light provides no shadow environment for image acquisition.
It is advanced optimized as of the invention, the Quality Detection mechanism, which is provided with, overlooks CCD camera to obtain top view
Picture is symmetrically set with side view CCD camera to obtain side elevation image.
It is advanced optimized as of the invention, the side view CCD camera is mounted in shield groove, and installed position
Central location below detection box.
It is advanced optimized as of the invention, installs and be provided on the outside of the shield groove of the side view CCD camera
Bright protective plate.
It is advanced optimized as of the invention, the Quality Detection mechanism is provided with photoelectric sensor, is located at side view CCD phase
The front of machine, and mounting height is slightly above roller highest point.
Present invention has an advantage that
(1) a kind of rear wild cabbage inside and outside quality detection evaluating apparatus of adopting based on machine vision of the invention is driven by sprocket wheel chain
And rack-and-pinion realizes at the uniform velocity advance and the spinning motion of roller, and then realizes the orderly tuning of wild cabbage, convenient for subsequent
The acquisition of wild cabbage omnidirectional images.
(2) a kind of rear wild cabbage inside and outside quality detection evaluating apparatus of adopting based on machine vision of the invention passes through image procossing
Technology obtains the exterior qualities information such as size, color, the damage of wild cabbage, and combines the wild cabbage inside quality analyzed based on data pre-
It surveys model and obtains the inside qualities information such as the wild cabbage degree of packing, improve the rate of wild cabbage inside and outside quality detection.
(3) it is of the invention it is a kind of based on machine vision adopt rear wild cabbage inside and outside quality detection evaluating apparatus be provided with tuning,
The mechanisms such as Quality Detection realize automatic direction regulating and the evaluation of quick, lossless Quality Detection of wild cabbage, have saved manual operation, more
Add convenient and efficient.
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 this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is a kind of overall structure diagram adopted rear wild cabbage inside and outside quality and detect evaluating apparatus based on machine vision.
Fig. 2 is that a kind of structure of adjusted device for adopting rear wild cabbage inside and outside quality detection evaluating apparatus based on machine vision is shown
It is intended to.
Fig. 3 is the partial enlarged view of the roller connection type at Fig. 2 adjusted device I.
Fig. 4 is a kind of knot adopted rear wild cabbage inside and outside quality and detect the Quality Detection mechanism of evaluating apparatus based on machine vision
Structure schematic diagram.
Fig. 5 is the structural representation side view of Quality Detection mechanism.
Fig. 6 is the A-A cross-sectional view of Fig. 5 Quality Detection mechanism.
Fig. 7 is a kind of flow chart for adopting rear wild cabbage inside and outside quality detection evaluation based on machine vision.
[appended drawing reference]
1. rack;2. adjusted device;201. drive shaft;202. sprocket wheel;203. chain;204. chain connector;205. rollers are solid
Dead axle;206. bearing;207. gear;208. roller;209. rack gear;210. wild cabbage;3. Quality Detection mechanism;301. shield;
302. detection box;303.LED lamp;304. overlook CCD camera;305. transparent prevention plate;306. side view CCD cameras;307. light
Electric transducer;4. motor;5. side plate.
Specific embodiment
In the following, the present invention is specifically described by illustrative embodiment.It should be appreciated, however, that not into one
In the case where step narration, element, structure and features in an embodiment can also be advantageously incorporated into other embodiments
In.
Before to present invention explanation, need to define, the heretofore described noun of locality, such as front, rear are
Using the traffic direction for adopting rear wild cabbage inside and outside quality detection evaluating apparatus based on machine vision a kind of in Fig. 1 as foundation, that is, work as inspection
When surveying evaluating apparatus work, rack-and-pinion is front end, and Quality Detection mechanism is rear end;Such as bottom, the top noun of locality are
Using the placement location of device normal operating conditions as shown in figure 1 as foundation.
Referring to Fig. 1 to Fig. 6, a kind of rear wild cabbage inside and outside quality of adopting based on machine vision of the invention detects evaluating apparatus,
Including rack 1, adjusted device 2, Quality Detection mechanism 3, motor 4 and side plate 5 in rack 1 are set;Motor 4 passes through sprocket wheel
The transmission of 202 chains 203 drives adjusted device 2 at the uniform velocity to advance, while roller 208 realizes rotation under 207 rack gear of gear, 209 side effect
Transhipment is dynamic;Wild cabbage 210 is acted on roller 208 by frictional force and is rolled, because itself mono-symmetry characteristic realizes tuning operation;Then
Wild cabbage 210 enters Quality Detection mechanism 3, is controlled by 307 signal of photoelectric sensor and overlooks CCD camera 304 and side view CCD camera
306, which complete comprehensive image, obtains, and then carries out the exterior qualities such as size, color and damage by image processing techniques and examine
It surveys, and inside quality prediction is carried out by prediction model on this basis, be finally completed the quality evaluation for adopting rear wild cabbage 210.
With continued reference to Fig. 1 to Fig. 6, a kind of of the invention adopts rear wild cabbage inside and outside quality detection evaluation dress based on machine vision
When setting normal operation, the job parameters such as 4 revolving speed of motor of the device are set by upper computer software, motor 4 passes through connection
Axis device is fixedly connected with drive shaft 201, and then band movable sprocket 202 and chain 203 carry out linear uniform motion;Make in rack gear 209
In industry stroke range, gear 207 is straight by forming 208 side of rack-and-pinion drive roller wheel with the rack gear 209 being arranged in rack 1
Line moves side rotary motion, and then drives wild cabbage 210 to be rolled by the frictional force between roller 208 and wild cabbage 210, Yin Gan
The mono-symmetry characteristic of indigo plant 210 itself realizes tuning operation;When roller 208 be detached from 209 job area of rack gear after, wild cabbage 210 because
It is self-possessed and frictional force acts on and forms stable state with roller 208, at the uniform velocity advances into Quality Detection machine backward with chain 203
Structure 3;Wherein, shield 301 and transparent prevention plate 305 are by the key such as sprocket wheel 202, chain 203, gear 207 and rack gear 209 zero
Package is completely covered in component, forms a stable transfer passage with roller 208, had both ensured the personal safety of operator,
The mechanical damage of wild cabbage 210 during transportation is reduced again;Meanwhile it being formed by shield 301, detection box 302 and side plate 5
More closed working space avoids influence of the complicated working environment background to the recognition detection precision of 210 image of wild cabbage,
It is aided with several LED light 303 simultaneously and provides one without shadow environment for image acquisition;When wild cabbage 210 is by photoelectric sensor 307,
Photoelectric sensor 307, which generates signal and controls, overlooks CCD camera 304 and the progress image taking of side view CCD camera 306, and in real time
Comprehensive image data is transmitted to computer terminal and saves simultaneously further progress image processing and analyzing.
Referring to Fig. 7, computer terminal, which receives to be controlled by photoelectric sensor 307, overlooks CCD camera 304 and side view CCD camera
After 210 images of wild cabbage of 306 shootings, carry out judging whether first can further recognition detection, if can not recognition detection, control
Corresponding CCD camera is made to re-shoot and cover respective image;If can carry out noise suppression preprocessing with recognition detection to image, lead to
It crosses Hough algorithm and carries out the extraction of target prospect feature to pretreated image, and carry out outer profile fitting to obtain its wheel
Wide edge feature, and then the foreground features in contour edge are carried out with the detection of size, color and damaged area, it obtains
Its exterior quality information.In addition, the statistical information and wild cabbage 210 that pass through the exterior qualities such as size, the color of several wild cabbages 210
The inside qualities statistical information such as degree of packing is fitted, and determines best-fit mathematics equation, adopts the interior of rear wild cabbage 210 to establish
Component matter prediction model, the exterior quality information obtained according to image procossing obtain the inside quality information of wild cabbage 210;Finally,
Processing analysis is carried out to the inside and outside quality information of wild cabbage 210 in conjunction with professional standard and the market demand, and then completes to adopt rear wild cabbage
210 quality evaluation, for subsequent 210 simulation model of trimming graded operation and wild cabbage for adopting rear wild cabbage 210 research provide according to
According to.
Referring to figs. 2 and 3, adjusted device 2 is provided with several equally distributed rollers 208, between the minimum of adjacent roller 208
Away from for 70mm, to guarantee that wild cabbage 210 is not fallen out on roller 208.
With continued reference to Fig. 2 and Fig. 3,207 coaxial welding of gear that 208 two sides of roller are fixed with bearing 206 with inside is solid
Fixed, gear 207 is engaged with the rack gear 209 being symmetricly set in rack 1, realizes the rotary motion of roller 208;And it is solid by roller
Dead axle 205 and chain connector 204 are fixedly connected with chain 203, realize the at the uniform velocity advance of roller 208.
Referring to fig. 4 to Fig. 6, Quality Detection mechanism 3 is provided with symmetrical shield 301, shield 301 and rack 1
Fixation is bolted, with detection box 302 by being welded and fixed, and 301 top of 302 bottom of detection box and shield
Gap is zero.
With continued reference to fig. 4 to fig. 6, Quality Detection mechanism 3 is provided with detection box 302, positioned at the top of shield 301,
The rear of rack gear 209.
With continued reference to fig. 4 to fig. 6, Quality Detection mechanism 3 is provided with LED light at the top of detection box 302 and side
303, no shadow environment is provided for image acquisition.
With continued reference to fig. 4 to fig. 6, Quality Detection mechanism 3, which is provided with, overlooks CCD camera 304 to obtain overhead view image, controls
Side view CCD camera 306 is symmetrically arranged with to obtain side elevation image.
With continued reference to fig. 4 to fig. 6, side view CCD camera 306 is mounted in 301 groove of shield, and installation site is in inspection
The central location of 302 lower section of measuring tank body.
With continued reference to fig. 4 to fig. 6, it is provided on the outside of 301 groove of shield of installation side view CCD camera 306 transparent anti-
Backplate 305.
With continued reference to fig. 4 to fig. 6, Quality Detection mechanism 3 is provided with photoelectric sensor 307, is located at side view CCD camera 306
Front, and mounting height is slightly above 208 highest point of roller.
The above embodiments are merely illustrative of the technical solutions of the present invention, rather than is limited;Although referring to aforementioned reality
Applying example, invention is explained in detail, for those of ordinary skill in the art, still can be to aforementioned implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features;And these are modified or replace
It changes, the spirit and scope for claimed technical solution of the invention that it does not separate the essence of the corresponding technical solution.
Claims (10)
1. a kind of adopt rear wild cabbage inside and outside quality detection evaluating apparatus, including rack (1) based on machine vision, it is arranged in rack
(1) adjusted device (2), Quality Detection mechanism (3), motor (4) and side plate (5) on, which is characterized in that motor (4) passes through chain
Wheel (202) chain (203) transmission drives adjusted device (2) at the uniform velocity to advance, while roller (208) is in gear (207) rack gear (209)
Rotary motion is realized under side effect;Wild cabbage (210) is acted on roller (208) by frictional force and is rolled, because of itself mono-symmetry spy
Property realize tuning operation;Subsequent wild cabbage (210) enters Quality Detection mechanism (3), is bowed by the control of photoelectric sensor (307) signal
Comprehensive image is completed depending on CCD camera (304) and side view CCD camera (306) to obtain, and then is carried out by image processing techniques
The appearance quality detections such as size, color and damage, and inside quality prediction is carried out by prediction model on this basis, it is final complete
The quality evaluation of Cheng Caihou wild cabbage (210).
2. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the adjusted device (2) is provided with several equally distributed rollers (208), and the minimum spacing of adjacent roller (208) is
70mm, to guarantee that wild cabbage (210) is not fallen out on roller (208).
3. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, gear (207) coaxial welding that roller (208) two sides are fixed with bearing (206) with inside is fixed, gear
(207) it is engaged with the rack gear (209) being symmetricly set on rack (1), realizes the rotary motion of roller (208);And pass through roller
Fixing axle (205) and chain connector (204) are fixedly connected with chain (203), realize the at the uniform velocity advance of roller (208).
4. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the Quality Detection mechanism (3) is provided with symmetrical shield (301), and shield (301) passes through with rack (1)
It is bolted fixation, with detection box (302) by being welded and fixed, and at the top of detection box (302) bottom and shield (301)
Gap be zero.
5. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the Quality Detection mechanism (3) is provided with detection box (302), it is located at the top of shield (301), rack gear (209)
Rear.
6. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the Quality Detection mechanism (3) is provided with LED light (303) at the top of detection box (302) and side, is image
It obtains and provides without shadow environment.
7. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the Quality Detection mechanism (3), which is provided with, overlooks CCD camera (304) to obtain overhead view image, is symmetrically set with side
Depending on CCD camera (306) to obtain side elevation image.
8. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the side view CCD camera (306) is mounted in shield (301) groove, and installation site is in detection box (302)
The central location of lower section.
9. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, installs and be provided with transparent prevention plate (305) on the outside of shield (301) groove of the side view CCD camera (306).
10. a kind of according to claim 1 adopt rear wild cabbage inside and outside quality detection evaluating apparatus, feature based on machine vision
It is, the Quality Detection mechanism (3) is provided with photoelectric sensor (307), is located at the front of side view CCD camera (306), and pacify
Dress height is slightly above roller (208) highest point.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910751500.1A CN110296992A (en) | 2019-08-15 | 2019-08-15 | It is a kind of that rear wild cabbage inside and outside quality detection evaluating apparatus is adopted based on machine vision |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910751500.1A CN110296992A (en) | 2019-08-15 | 2019-08-15 | It is a kind of that rear wild cabbage inside and outside quality detection evaluating apparatus is adopted based on machine vision |
Publications (1)
Publication Number | Publication Date |
---|---|
CN110296992A true CN110296992A (en) | 2019-10-01 |
Family
ID=68032925
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910751500.1A Pending CN110296992A (en) | 2019-08-15 | 2019-08-15 | It is a kind of that rear wild cabbage inside and outside quality detection evaluating apparatus is adopted based on machine vision |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110296992A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111203389A (en) * | 2020-01-15 | 2020-05-29 | 厦门瑞固科技有限公司 | Visual detection device and detection method |
US20220357634A1 (en) * | 2021-05-04 | 2022-11-10 | Purdue Research Foundation | Phenotyping imaging system with automatic leaf-handling mechanism |
CN117664975A (en) * | 2024-02-01 | 2024-03-08 | 黑龙江八一农垦大学 | Corn quality detection device and method based on machine vision |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101551341A (en) * | 2009-04-09 | 2009-10-07 | 浙江大学 | Meat online non-destructive testing method and apparatus based on fusion of image and spectrum information |
CN101949686A (en) * | 2010-08-02 | 2011-01-19 | 扬州福尔喜果蔬汁机械有限公司 | Online nondestructive testing (NDT) method and device for comprehensive internal/external qualities of fruits |
CN202057579U (en) * | 2011-04-02 | 2011-11-30 | 北京神农谷科技有限公司 | Optical system capable of on-line detecting internal quality of fruits |
CN103792235A (en) * | 2014-01-10 | 2014-05-14 | 内蒙古农业大学 | Diffuse transmission spectrum and image information fusion method for detecting internal quality of honeydew melons on line and device |
KR20170044933A (en) * | 2015-10-16 | 2017-04-26 | 라온피플 주식회사 | Image generating method and apparatus for machine vision test, method and apparatus for simulating machine vision test, and machine vision testing system |
CN109533891A (en) * | 2018-12-26 | 2019-03-29 | 西北农林科技大学 | A kind of elliposoidal wild cabbage tuning separate row device |
CN211043154U (en) * | 2019-08-15 | 2020-07-17 | 西北农林科技大学 | Machine vision-based device for detecting and evaluating internal and external quality of post-harvest cabbages |
-
2019
- 2019-08-15 CN CN201910751500.1A patent/CN110296992A/en active Pending
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101551341A (en) * | 2009-04-09 | 2009-10-07 | 浙江大学 | Meat online non-destructive testing method and apparatus based on fusion of image and spectrum information |
CN101949686A (en) * | 2010-08-02 | 2011-01-19 | 扬州福尔喜果蔬汁机械有限公司 | Online nondestructive testing (NDT) method and device for comprehensive internal/external qualities of fruits |
CN202057579U (en) * | 2011-04-02 | 2011-11-30 | 北京神农谷科技有限公司 | Optical system capable of on-line detecting internal quality of fruits |
CN103792235A (en) * | 2014-01-10 | 2014-05-14 | 内蒙古农业大学 | Diffuse transmission spectrum and image information fusion method for detecting internal quality of honeydew melons on line and device |
KR20170044933A (en) * | 2015-10-16 | 2017-04-26 | 라온피플 주식회사 | Image generating method and apparatus for machine vision test, method and apparatus for simulating machine vision test, and machine vision testing system |
CN109533891A (en) * | 2018-12-26 | 2019-03-29 | 西北农林科技大学 | A kind of elliposoidal wild cabbage tuning separate row device |
CN211043154U (en) * | 2019-08-15 | 2020-07-17 | 西北农林科技大学 | Machine vision-based device for detecting and evaluating internal and external quality of post-harvest cabbages |
Non-Patent Citations (2)
Title |
---|
孙宝霞;汤林越;何志良;邹湘军;熊俊涛;: "基于机器视觉的采后荔枝表皮微损伤实时检测", 农业机械学报, no. 07, 6 June 2016 (2016-06-06) * |
李龙;彭彦昆;李永玉;: "苹果内外品质在线无损检测分级***设计与试验", 农业工程学报, no. 09, 8 May 2018 (2018-05-08) * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111203389A (en) * | 2020-01-15 | 2020-05-29 | 厦门瑞固科技有限公司 | Visual detection device and detection method |
US20220357634A1 (en) * | 2021-05-04 | 2022-11-10 | Purdue Research Foundation | Phenotyping imaging system with automatic leaf-handling mechanism |
US11815788B2 (en) * | 2021-05-04 | 2023-11-14 | Purdue Research Foundation | Phenotyping imaging system with automatic leaf-handling mechanism |
CN117664975A (en) * | 2024-02-01 | 2024-03-08 | 黑龙江八一农垦大学 | Corn quality detection device and method based on machine vision |
CN117664975B (en) * | 2024-02-01 | 2024-04-26 | 黑龙江八一农垦大学 | Corn quality detection device and method based on machine vision |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110296992A (en) | It is a kind of that rear wild cabbage inside and outside quality detection evaluating apparatus is adopted based on machine vision | |
CN101486033B (en) | Device for sorting fruits and method for sorting Chinese chestnut | |
CN104895564B (en) | The Coal-Rock Interface Recognition device of coalcutter is used for based on machine vision | |
CN101949686A (en) | Online nondestructive testing (NDT) method and device for comprehensive internal/external qualities of fruits | |
CN109085170B (en) | Synchronous belt type corn kernel breaking rate online detection device and method | |
WO2016138675A1 (en) | Combine harvester self-adaptive cleaning control apparatus and self-adaptive cleaning method thereof | |
CN202057579U (en) | Optical system capable of on-line detecting internal quality of fruits | |
CN1868610B (en) | Small movable intelligent grading device for fruit and poultry egg | |
CN104174597A (en) | On-line rapid non-destructive detection and sorting device for slightly damaged fresh dates | |
CN205176871U (en) | Two -dimensional code check out test set | |
CN103636315A (en) | Hyperspectrum-based seed germination rate online-detection apparatus and method thereof | |
CN106370667A (en) | Visual detection apparatus and method for quality of corn kernel | |
WO2022027877A1 (en) | Method and apparatus for measuring movement speed of contact of vacuum switch | |
CN113111840A (en) | Method for early warning violation and dangerous behaviors of operators on fully mechanized coal mining face | |
CN102788806B (en) | Fruit peel defect detection method based on spheroidic brightness transformation | |
CN109570051A (en) | Chinese chestnut small holes caused by worms detection device based on machine vision, laser and acoustics | |
CN109380146A (en) | Live pig self-operated measuring unit and method | |
CN211043154U (en) | Machine vision-based device for detecting and evaluating internal and external quality of post-harvest cabbages | |
CN206879476U (en) | A kind of novel strawberry A seating picking machine | |
CN116686545A (en) | Litchi picking robot shade removing method based on machine vision control | |
CN114419011A (en) | Cotton foreign fiber online detection method and system | |
CN115719451A (en) | Kiwi fruit actinidia arguta maturity detection method and system | |
CN105548222B (en) | A kind of online pest and disease damage detection device of cereal crops | |
CN114627074A (en) | Ground shooting fan blade real-time monitoring method based on deep learning | |
CN109490314B (en) | Industrial machine vision system based on improved sensing detection device |
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 |