CN104813993B - Small agricultural pests automated watch-keeping facility and method based on machine vision - Google Patents
Small agricultural pests automated watch-keeping facility and method based on machine vision Download PDFInfo
- Publication number
- CN104813993B CN104813993B CN201510195638.XA CN201510195638A CN104813993B CN 104813993 B CN104813993 B CN 104813993B CN 201510195638 A CN201510195638 A CN 201510195638A CN 104813993 B CN104813993 B CN 104813993B
- Authority
- CN
- China
- Prior art keywords
- insect
- sticking plate
- mythimna separata
- agricultural pests
- image
- 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.)
- Active
Links
- 241000607479 Yersinia pestis Species 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000012544 monitoring process Methods 0.000 claims abstract description 37
- 241000238631 Hexapoda Species 0.000 claims abstract description 24
- 238000001514 detection method Methods 0.000 claims abstract description 20
- 241000409991 Mythimna separata Species 0.000 claims description 49
- 239000003795 chemical substances by application Substances 0.000 claims description 48
- 238000010422 painting Methods 0.000 claims description 15
- 238000003860 storage Methods 0.000 claims description 12
- 238000012216 screening Methods 0.000 claims description 9
- 230000009977 dual effect Effects 0.000 claims description 7
- 239000000945 filler Substances 0.000 claims description 5
- 238000012806 monitoring device Methods 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 241000894007 species Species 0.000 claims description 4
- 238000013473 artificial intelligence Methods 0.000 claims description 2
- 238000013528 artificial neural network Methods 0.000 claims description 2
- 238000006073 displacement reaction Methods 0.000 claims description 2
- 238000012549 training Methods 0.000 claims description 2
- 238000004040 coloring Methods 0.000 claims 1
- 239000000877 Sex Attractant Substances 0.000 abstract description 6
- 230000008901 benefit Effects 0.000 abstract description 3
- 230000036962 time dependent Effects 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 8
- 238000011835 investigation Methods 0.000 description 7
- 241001124076 Aphididae Species 0.000 description 3
- 241000254127 Bemisia tabaci Species 0.000 description 3
- 235000013399 edible fruits Nutrition 0.000 description 3
- 241001498622 Cixius wagneri Species 0.000 description 2
- 241000594033 Liriomyza bryoniae Species 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 241000255925 Diptera Species 0.000 description 1
- 241000258937 Hemiptera Species 0.000 description 1
- 238000012271 agricultural production Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000010339 dilation Effects 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 230000029305 taxis Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Landscapes
- Catching Or Destruction (AREA)
Abstract
The invention discloses a kind of small agricultural pests automated watch-keeping facility and method based on machine vision, the automated watch-keeping facility is mainly made up of the part such as small agricultural pests automatic trap, camera and computer；The automatic monitoring method mainly includes the following steps that, installs automated watch-keeping facility, updates insect-sticking plate, the image of one frame insect-sticking plate of collection, the image for waiting for a period of time, gathering a frame insect-sticking plate again, the two frame insect-sticking plate images for gathering recently carried out with Differential Detection, the result of Differential Detection is counted automatically and is classified, output result, judged whether to terminate monitoring, judge whether to update insect-sticking plate；It is an advantage of the invention that also can implement to trap in the case of without insect sex attractant and high-voltage fence to small agricultural pests automatically, and the insect that traps is counted automatically using machine vision technique and classified, the time dependent information of record pest trap value volume and range of product.
Description
Technical field
The present invention relates to agricultural pests automatic monitoring technical field, specifically a kind of small agricultural evil based on machine vision
Worm automated watch-keeping facility and method.
Background technology
In China's agricultural production, yield and economic benefit are affected larger small agricultural pests be mainly Homoptera and
Dipterous insect, including but not limited to：Aphid, plant hopper, Bemisia tabaci, liriomyza bryoniae, fruit bat etc..At present for these small agriculturals
The field investigation of insect still takes artificial range estimation investigation method, the method to waste time and energy, investigation result person under investigation person subjectivity shadow
Ring greatly, basic unit's plant protection personnel lack now in addition, field investigation task weight, and the artificial range estimation investigation method of this inefficiency is
The requirement of agricultural modernization can not be met.
In recent years, some new insect automatic monitoring technicals are constantly suggested, and monitoring technology main at present has infrared meter
Number technology, picture count technology etc., the development of these technology improve insect automatic identification and the efficiency for counting, and are greatly facilitated
The development of worm monitoring automation.As patent 201410128410.4 discloses a kind of pest trap counting device and counts system
System, the invention first pass through insect sex attractant and carry out trapping pests, then comprehensively using infrared counting technology and picture count technology
Insect is counted, but due to lacking corresponding insect sex attractant, the invention can't trap aphid, plant hopper, Bemisia tabaci,
The small agricultural pests such as liriomyza bryoniae, fruit bat, while the invention is also provided with high-voltage fence in trapper, even if there is small agricultural
Insect flies in trapper by mistake also can be by electric burnt, so as to can not be by accurate counting.
Content of the invention
In order to solve defect present in above-mentioned prior art, the invention provides a kind of small agriculture based on machine vision
Industry insect automated watch-keeping facility and method, can trap small agriculture in the case of without insect sex attractant and high-voltage fence automatically
Industry insect, and using machine vision technique to trapping to insect counted automatically and classified, record pest trap quantity and
The time dependent information of species.
The technical solution used in the present invention：A kind of small agricultural pests automated watch-keeping facility based on machine vision, including
Support, is fixed with an active roller bearing, driven roller bearing and the mythimna separata being wound on active roller bearing and driven roller bearing on described support
Plate；Mythimna separata agent painting brush is provided with above described insect-sticking plate, and lower section is provided with mythimna separata agent and removes brush；Described mythimna separata plate surface with viscous
Brush contact is removed in worm agent painting brush and mythimna separata agent；Described mythimna separata agent painting brush is connected with a mythimna separata agent storage bin；Described prison
Survey device to be additionally provided with for monitoring the camera and computer of insect-sticking plate.
According to a further aspect in the invention, there is provided a kind of small agricultural pests automatic monitoring method based on machine vision,
Comprise the steps：
S1：Small agricultural pests automated watch-keeping facility is installed, the monitoring device described in claim 1 is arranged on crops
Field, makes the bottom of insect-sticking plate higher than 10-20 centimetre at the top of crops；Mythimna separata agent is added by mythimna separata agent by mythimna separata agent filler
Storage bin；The focal length of camera is adjusted, makes monitoring range cover insect-sticking plate；
S2：Insect-sticking plate being updated, rotation instruction being sent from computer to active roller bearing, active roller bearing rotates, in driven roller bearing
Assistance under, insect-sticking plate is moved down towards the side of camera, and displacement exceed insect-sticking plate height, in insect-sticking plate
In moving process, mythimna separata agent painting brush by mythimna separata agent uniform application on insect-sticking plate, while mythimna separata agent remove brush by insect-sticking plate
Mythimna separata agent and adhere to superincumbent insect and debris are disposed together；
S3：After the completion of insect-sticking plate updates, camera gathers the image of a frame insect-sticking plate immediately；
S4：Wait for a period of time；
S5：Camera gathers the image of a frame insect-sticking plate；
S6：The two frame insect-sticking plate images for gathering recently are carried out with contrast stretching and gray processing is processed, then to two frames ash
Degreeization image carries out Differential Detection and binary conversion treatment；
S7：The binary image obtained by Differential Detection carries out mathematical morphology open operator, then mark UNICOM region, and
Dual threshold screening is carried out to UNICOM region, finally the figure spot that screening is obtained is counted and compressive classification automatically；
S8：The number of pest increased in output result, output unit time and species；
S9：Judge whether to terminate monitoring, if terminating monitoring, exit, if not terminating monitoring, continue executing with next
Step；
S10：Judge whether to update insect-sticking plate, if currently the gross area of capture insect exceedes the 60% of mythimna separata plate suqare,
Then execution step S2, otherwise execution step S4.
Beneficial effects of the present invention：The present invention announce the small agricultural pests automated watch-keeping facility based on machine vision and
Method, the investigation for small agricultural pests provide a kind of new automatic monitoring method.Not using conventional elder brother in this method
Worm sex attractant technology, but the taxis using small agricultural pests to particular color, design a kind of automatic trap, realize
The function of small agricultural pests can be also traped in the case of without sex attractant.Insect-sticking plate is provided with automatic trap certainly
Dynamic updating device, the device can solve artificial replacing insect-sticking plate time interval handle according to monitoring needs, timely replacement insect-sticking plate
Hold the problem of inaccurate, high labor intensive.Position of the present invention by the position of camera with insect-sticking plate is relatively fixed, and makes camera
Monitoring range just covers whole insect-sticking plate, reduces the difficulty of Differential Detection when insect counts automatically and classifies, improves difference
Efficiency and stability that go-on-go is surveyed.The present invention has used mathematics in based on the small agricultural pests automatic testing method of machine vision
Morphology opening operation, can disconnect tiny connection between figure spot, make counting automatically more accurate；Using artificial intelligence neural networks
Model is classified to insect image, and nicety of grading is high, good stability.
Description of the drawings
Fig. 1 is the structural representation of small agricultural pests automated watch-keeping facility of the invention；
Fig. 2 is the flow chart of small agricultural pests automatic monitoring method of the invention.
Specific embodiment
In order to preferably state the details and its advantage of technical solution of the present invention, it is described further in conjunction with accompanying drawing.
As shown in figure 1, a kind of small agricultural pests automated watch-keeping facility based on machine vision, including support, described
An active roller bearing 7, driven roller bearing 4 and the insect-sticking plate 5 being wound on active roller bearing 7 and driven roller bearing 4 is fixed with support；Described
Insect-sticking plate 5 above be provided with mythimna separata agent painting brush 2, lower section is provided with mythimna separata agent and removes brush 8；Described 5 surface of insect-sticking plate and mythimna separata
Agent painting brush 2 and mythimna separata agent are removed brush 8 and are contacted；Described mythimna separata agent painting brush 2 is connected with a mythimna separata agent storage bin 3；Described
Monitoring device is additionally provided with for monitoring the camera 9 and computer 15 of insect-sticking plate 5.
Wherein, described mythimna separata agent storage bin 3 is provided with mythimna separata agent filler 1, for filling mythimna separata agent, meanwhile, mythimna separata
Mythimna separata agent uniform application is arrived by the mythimna separata agent in agent storage bin 3 and 2 directly contact of mythimna separata agent painting brush by mythimna separata agent painting brush
On insect-sticking plate 5.
Motor is provided with described active roller bearing 7；Described motor is connected with computer 15 by roller bearing control line 6
Connect, execute rotation or halt instruction that computer 15 is assigned, and power supply is provided by calculation machine 15；Described camera 9 is by shooting
Head data wire 14 is connected with computer 15, is executed the collection image command that computer 15 is assigned, and is provided power supply by calculation machine 15.
Data wire used in embodiment, is USB interface data wire, can provide power supply while transmission information.Camera 9
5 image of insect-sticking plate of collection, is maintained in computer 15, and comprising acquisition time and number information, when needed, Ke Yisui
When have access to, so as to further ensure the accuracy of monitoring result.
Described support includes the A-frame 12 and the expansion link 11 being arranged on A-frame 12 positioned at bottom, described
Expansion link 11 be provided with fixing bolt 10；Described camera 9 is fixed on expansion link 11 by camera fixing support 13 and pushes up
End；Described insect-sticking plate 5, its color can select yellow, blue or white, the selection of insect-sticking plate 5 Huang in the present embodiment as needed
Color；Described active roller bearing 7, its girth slightly larger than 5 height of insect-sticking plate 1/3, therefore, when updating insect-sticking plate 5, only need to be controlled to lead
Dynamic roller bearing 7 rolls 3 circles and can complete 1 renewal.
As shown in Fig. 2 a kind of small agricultural pests automatic monitoring method based on machine vision, comprises the following steps that：
S1：Automated watch-keeping facility is installed, monitoring device is fixed on crops field, adjustable telescopic rod with A-frame 12
11, make 5 bottom of insect-sticking plate higher than 10-20 centimetre at the top of crops, then expansion link 11 is fixed with fixing bolt 10；Use roller bearing control
The connection active of line processed 6 roller bearing 7 and computer 15, connect monitoring camera 9 and computer 15 with data wire 14；By filler 1
Mythimna separata agent is filled into mythimna separata agent storage bin 3；The focal length of monitoring camera 9 is adjusted, just the monitoring range of monitoring camera 9 is made
Cover insect-sticking plate 5；
S2：Insect-sticking plate 5 is updated, rotation instruction, 7 average rate of active roller bearing rotation 3 are sent to active roller bearing 7 by computer 15
In week, under the assistance of driven roller bearing 4, active roller bearing 7 drives insect-sticking plate 5 to move down towards the side of camera, and mobile away from
From the height for exceeding insect-sticking plate 5；When painting brush 2, painting brush 2 is by the mythimna separata agent in mythimna separata agent storage bin 3 on insect-sticking plate 5 top
Uniform application is on insect-sticking plate 5；Brush 8 is removed by the mythimna separata agent on insect-sticking plate 5 and attached when removing brush 8 in 5 bottom of insect-sticking plate
The insect in mythimna separata agent is removed；
S3：After the completion of insect-sticking plate 5 updates, monitoring camera 9 gathers the image of an insect-sticking plate 5 immediately, and time domain is remembered
For ti(i=1), picture number is designated as mi(i=1), the storage format of gathered image is JPG forms, and color mode is RGB lattice
Formula；
S4：Wait for a period of time Δ t (span 1-600s), makes i=i+1；
S5：Monitoring camera 9 gathers the image of a frame insect-sticking plate 5 again, and time domain is designated as ti, picture number is designated as mi；
S6：Contrast stretching is carried out to the image of the two frame insect-sticking plates 5 for gathering recently and gray processing is processed, then to two frames
Gray level image carries out Differential Detection and binaryzation；
Contrast stretching, the RGB image m of two frame insect-sticking plates 5 before Differential Detection first to gathering recentlyiAnd mi-1Carry out
IHS is converted, and obtains brightness (Intensity, I), colourity (Hue, H), three components of saturation degree (Saturation, S), Ran Houqu
The luminance component I of the two field pictures after IHS conversioniAnd Ii-1, ask which to combine grey level histogram, according to joint histogram respectively to Ii
And Ii-1Contrast stretching is carried out, finally with the luminance component I ' after stretchingiWith I 'i-1Enter with respective colourity, saturation degree component
Row IHS inverse transformations, obtain the RGB image m ' after contrast stretchingiWith m 'i-1；
Image gray processing process, by RGB image m 'iWith m 'i-1Be converted to gray level image fiAnd fi-1, computing formula is：
F=r*0.299+g*0.587+b*0.114
Wherein, f is gray value, and r is red component, and g is green component, and b is blue component；
Differential Detection, for gray level image fiAnd fi-1Differential Detection is carried out as follows：
fΔt(x, y)=fi(x,y)-fi-1(x,y)
Wherein, Δ t=ti-ti-1, fΔt(x, y) is the gray scale difference that two frame gray level images are arranged in xth row, y；
Binary conversion treatment, sets rational threshold value T with maximum variance between clustersf, to Differential Detection result fΔtEnter
Row binaryzation, obtains the binary image B of Differential Detection resulti, binaryzation carried out by following equation：
Binary image B in Differential Detection resultiIntermediate value is the insect that 1 pixel is considered as new capture within the Δ t times,
It is worth and is considered as background or t for 0 pixeli-1The insect captured before moment；
S7：The binary image obtained by Differential Detection carries out mathematical morphology open operator, then mark UNICOM region, and
Dual threshold screening is carried out to UNICOM region, finally the figure spot that screening is obtained is counted and compressive classification automatically；
Mathematical morphology open operator, binaryzation figure spot Differential Detection obtained with the disc structure element that radius is 1 enter
Row mathematical morphology open operator, the i.e. computing of advanced line number morphological erosion are disconnecting tiny connection between figure spot, Ran Houzai
Carry out mathematical morphology dilation operation；
Mark UNICOM region, finds all UNICOM regions according to eight neighborhood, and marks respectively, each mark UNICOM region
All by as an alternative figure spot；
Dual threshold is screened, and sets 2 threshold values TBminAnd TBmax, represent lower limit and the upper limit of small agricultural pests area respectively,
All alternative figure spots are screened, and area are removed more than the upper limit or the figure spot less than lower limit；
Automatically count, the figure spot that dual threshold screening is obtained is counted automatically, the quantity of figure spot is exactly to lure in the Δ t times
The number of pest that catches；
Compressive classification, the figure spot that dual threshold screening is obtained obtain coloured image m ' as masking-outiIn each figure spot face
Color information, calculates 3 characteristic values such as color average, area and length-width ratio of each figure spot, and is entered into the people for training
Work intelligent Neural Network model is classified, and the insect that insect-sticking plate 5 is traped is divided into 4 classes by model, and wherein, type I is represented to be had
Wing aphid, Type II represent Bemisia tabaci, and type III represents fruit bat, and Type IV represents other；
S8：Output result, exports the number of pest and species increased on insect-sticking plate 5 in the current Δ t times；
S9：Judge whether to terminate monitoring, if terminating monitoring, exit, if not terminating monitoring, continue executing with next
Step；
S10：Judge whether to update insect-sticking plate 5, if the insect gross area of current capture exceedes 5 area of insect-sticking plate
60%, then execution step S2, otherwise execution step S4.
Claims (8)
1. a kind of small agricultural pests automated watch-keeping facility based on machine vision, it is characterised in that：Including support, described props up
An active roller bearing (7), driven roller bearing (4) and the insect-sticking plate being wound on active roller bearing (7) and driven roller bearing (4) is fixed with frame
(5)；Mythimna separata agent painting brush (2) is provided with above described insect-sticking plate (5), and lower section is provided with mythimna separata agent and removes brush (8)；Described mythimna separata
Brush (8) is removed with mythimna separata agent painting brush (2) and mythimna separata agent and is contacted in plate (5) surface；Described mythimna separata agent painting brush (2) is connected with one
Mythimna separata agent storage bin (3)；Described monitoring device is additionally provided with for monitoring the camera (9) and computer (15) of insect-sticking plate (5)；
Motor is provided with described active roller bearing (7)；Described motor is connected with computer (15) by roller bearing control line (6)
Connect, execute rotation or halt instruction that computer (15) is assigned, and power supply is provided by computer (15)；Described camera (9)
It is connected with computer (15) by camera data wire (14), the collection image command that execution computer (15) is assigned, and by
Computer (15) provides power supply；Described support include positioned at bottom A-frame (12) and be arranged on A-frame (12)
Expansion link (11)；Described camera (9) is fixed on the top of expansion link (11) by camera fixing support (13).
2. the small agricultural pests automated watch-keeping facility based on machine vision according to claim 1, it is characterised in that：Institute
Mythimna separata agent storage bin (3) that states is provided with mythimna separata agent filler (1).
3. the small agricultural pests automated watch-keeping facility based on machine vision according to claim 1, it is characterised in that：Institute
The expansion link (11) that states is provided with fixing bolt (10).
4. the small agricultural pests automated watch-keeping facility based on machine vision according to claim 1, it is characterised in that：Institute
The insect-sticking plate (5) that states, its color are yellow, blue or white.
5. a kind of small agricultural pests automatic monitoring method based on machine vision, it is characterised in that comprise the following steps：
S1：Small agricultural pests automated watch-keeping facility is installed, the monitoring device described in claim 1 is arranged on crops field
Between, the bottom of insect-sticking plate (5) is made higher than 10-20 centimetre at the top of crops；Mythimna separata agent is added by mythimna separata agent filler (1) viscous
Worm agent storage bin (3)；The focal length of camera (9) is adjusted, makes monitoring range cover insect-sticking plate (5)；
S2：Insect-sticking plate (5) being updated, rotation instruction being sent from computer (15) to active roller bearing (7), active roller bearing (7) rotates,
Under the assistance of driven roller bearing (4), insect-sticking plate (5) is moved down towards the side of camera (9), and displacement exceedes insect-sticking plate
(5) height, in the moving process of insect-sticking plate (5), mythimna separata agent painting brush (2) is by mythimna separata agent uniform application in insect-sticking plate (5)
On, while brush (8) is removed in mythimna separata agent the mythimna separata agent on insect-sticking plate (5) and the superincumbent insect of attachment and debris are removed together
Fall；
S3：After the completion of insect-sticking plate (5) updates, camera (9) gathers the image of a frame insect-sticking plate (5) immediately；
S4：Wait for a period of time；
S5：Camera (9) gathers the image of a frame insect-sticking plate (5)；
S6：Contrast stretching is carried out to the image of the two frame insect-sticking plates (5) for gathering recently and gray processing is processed, then to two frames ash
Degreeization image carries out Differential Detection and binary conversion treatment；
S7：The binary image obtained by Differential Detection carries out mathematical morphology open operator, then mark UNICOM region, and distich
Logical region carries out dual threshold screening, and finally the figure spot that screening is obtained is counted and compressive classification automatically；
S8：The number of pest increased in output result, output unit time and species；
S9：Judge whether to terminate monitoring, if terminating monitoring, exit, if not terminating monitoring, continue executing with next step；
S10：Judge whether to update insect-sticking plate (5), if currently the gross area of capture insect exceedes insect-sticking plate (5) area
60%, then execution step S2, otherwise execution step S4.
6. the small agricultural pests automatic monitoring method based on machine vision according to claim 5, it is characterised in that：Step
The image storage format gathered in rapid S3 and step S5 is JPG forms, and color mode is rgb format.
7. the small agricultural pests automatic monitoring method based on machine vision according to claim 5, it is characterised in that：Step
In rapid S6, the computing formula of Differential Detection is：
fΔt(x, y)=fi(x,y)-fi-1(x,y)
Wherein, fiAnd fi-1Number for gray level image, fΔt(x, y) is the gray scale difference of two frame gray level images；The two of Differential Detection result
Value is carried out by following equation：
Wherein, BiFor the binary image of Differential Detection result, TfFor binary-state threshold, fΔtFor Differential Detection result.
8. the small agricultural pests automatic monitoring method based on machine vision according to claim 5, it is characterised in that：Step
Compressive classification in rapid S7, concretely comprises the following steps the figure spot for obtaining dual threshold screening as masking-out, after obtaining contrast stretching
The colouring information of a nearest color image frame, calculates 3 characteristic values such as color average, area and length-width ratio of each figure spot, and
It is entered into the artificial intelligence neural networks model for training to be classified.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510195638.XA CN104813993B (en) | 2015-04-22 | 2015-04-22 | Small agricultural pests automated watch-keeping facility and method based on machine vision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510195638.XA CN104813993B (en) | 2015-04-22 | 2015-04-22 | Small agricultural pests automated watch-keeping facility and method based on machine vision |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104813993A CN104813993A (en) | 2015-08-05 |
| CN104813993B true CN104813993B (en) | 2017-03-15 |
Family
ID=53724704
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510195638.XA Active CN104813993B (en) | 2015-04-22 | 2015-04-22 | Small agricultural pests automated watch-keeping facility and method based on machine vision |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104813993B (en) |
Families Citing this family (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR3054662B1 (en) | 2016-07-26 | 2018-08-17 | Demand Side Instruments | METHOD AND DEVICE FOR MEASURING INSECT DENSITY |
| CN107786786A (en) * | 2016-08-24 | 2018-03-09 | 宁波高新区鹏博科技有限公司 | A kind of insect image automatic sweep apparatus |
| CN107279094B (en) * | 2017-07-31 | 2023-05-12 | 新疆农业大学 | Yellow board device easy to fix and clean and application of yellow board device in jujube fruit fly prevention and control |
| CN108040997B (en) * | 2017-12-25 | 2020-09-11 | 仲恺农业工程学院 | Insect pest monitoring method based on machine vision |
| CN109387516A (en) * | 2018-11-19 | 2019-02-26 | 宁夏农林科学院农业经济与信息技术研究所（宁夏农业科技图书馆） | Fructus lycii plants the automatic monitoring and warning station of field insect pest |
| CN109919796B (en) * | 2019-02-27 | 2021-08-03 | 北京农业智能装备技术研究中心 | Insect pest situation detecting and reporting system |
| CN110688989B (en) * | 2019-10-31 | 2022-05-17 | 无锡蜂巢生态农业有限公司 | Intelligent agriculture monitoring management system and method based on ecological environment protection |
| CN110796114B (en) * | 2019-11-07 | 2022-08-26 | 贵州大学 | Intelligent video monitoring and early warning system based on biological vision |
| CN111165455A (en) * | 2020-02-20 | 2020-05-19 | 桂林电子科技大学 | Crop disease and pest supervision device based on machine vision |
| CN111541874A (en) * | 2020-05-09 | 2020-08-14 | 河北天下瞳明科技有限公司 | Tiny insect monitoring device and method |
| CN112056284A (en) * | 2020-09-17 | 2020-12-11 | 河南中烟工业有限责任公司 | Tobacco beetle measuring and reporting device |
| CN112493218B (en) * | 2020-11-27 | 2022-09-02 | 英华达（上海）科技有限公司 | Intelligent mosquito catching device and method thereof |
| CN112868617A (en) * | 2021-02-20 | 2021-06-01 | 浙江农林大学 | Tea garden lesser leafhopper monitoring equipment and monitoring method based on color plate induced counting |
| CN113678804B (en) * | 2021-08-20 | 2022-07-22 | 浙江大学 | Intelligent tea garden insect attracting plate replacing device and method based on image channel calculation |
| CN114689800B (en) * | 2022-03-29 | 2023-10-20 | 双工方程(武汉)科技发展有限公司 | Layer-leaning and separating method of automatic monitoring and counting system for stored tobacco pests |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3956848A (en) * | 1975-04-03 | 1976-05-18 | Gte Laboratories Incorporated | Insect population serializer |
| CN201001349Y (en) * | 2006-10-31 | 2008-01-09 | 周飞鹏 | Recoverable insect-binding adhesive tape device and insect-killing lamp |
| CN202588123U (en) * | 2012-04-17 | 2012-12-12 | 吉林省新天地生物防治技术有限公司 | Roll continuous-type insect sticking paper device |
| CN103749416A (en) * | 2014-02-15 | 2014-04-30 | 福建农林大学 | Oriented monitoring, preventing and controlling system for pests |
| CN204157515U (en) * | 2014-09-24 | 2015-02-18 | 上海星让实业有限公司 | A kind of intelligent imaging system and be provided with the pest-catching device of this intelligent imaging system |
-
2015
- 2015-04-22 CN CN201510195638.XA patent/CN104813993B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3956848A (en) * | 1975-04-03 | 1976-05-18 | Gte Laboratories Incorporated | Insect population serializer |
| CN201001349Y (en) * | 2006-10-31 | 2008-01-09 | 周飞鹏 | Recoverable insect-binding adhesive tape device and insect-killing lamp |
| CN202588123U (en) * | 2012-04-17 | 2012-12-12 | 吉林省新天地生物防治技术有限公司 | Roll continuous-type insect sticking paper device |
| CN103749416A (en) * | 2014-02-15 | 2014-04-30 | 福建农林大学 | Oriented monitoring, preventing and controlling system for pests |
| CN204157515U (en) * | 2014-09-24 | 2015-02-18 | 上海星让实业有限公司 | A kind of intelligent imaging system and be provided with the pest-catching device of this intelligent imaging system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104813993A (en) | 2015-08-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104813993B (en) | Small agricultural pests automated watch-keeping facility and method based on machine vision | |
| Miranda et al. | Pest detection and extraction using image processing techniques | |
| DE102019214038A1 (en) | GRAIN QUALITY CONTROL SYSTEM AND METHOD | |
| CN103246872B (en) | A kind of wide spectrum insect pest situation automatic telemetry method based on computer vision technique | |
| CN203290099U (en) | Insect monitoring management system | |
| CN101701906A (en) | Method and device for detecting stored-grain insects based on near infrared super-spectral imaging technology | |
| CN105005813B (en) | Method of counting and system are analyzed in insect pest | |
| CN106332855A (en) | Automatic early warning system for pests and diseases | |
| CN104137821A (en) | Insect pest situation forecasting management system and forecasting management method | |
| CN111359907B (en) | Real-time online detection system and method for wheat scab infection particle rate based on embedded deep learning | |
| CN112102211A (en) | Crop stress early warning system and method based on temperature and image | |
| CN104918007A (en) | Computer vision-based large field pest situation monitoring sampling device and sampling method | |
| CN105868784A (en) | Disease and insect pest detection system based on SAE-SVM | |
| CN112106747A (en) | Intelligent agricultural insect pest remote automatic monitoring system | |
| CN112067616B (en) | Real-time detection device and method for grain quality | |
| WO2018120634A1 (en) | Method and apparatus for identifying disease and insect damage | |
| CN107403180A (en) | A kind of numeric type equipment detection recognition method and system | |
| KR20180043082A (en) | Plant disease detection system and method | |
| CN115238237A (en) | Insect pest situation monitoring method, device and system | |
| CN114511801A (en) | Insect pest recognition model training method, insect pest monitoring method and electronic equipment | |
| CN104902228A (en) | Insect real-time monitoring device and method based on computer vision | |
| CN212009389U (en) | Farmland disease and insect pest remote diagnosis system based on Internet of things | |
| CN212279561U (en) | Solar insect killing device for insect pest situation measurement and control | |
| CN113569675A (en) | Mouse open field experimental behavior analysis method based on ConvLSTM network | |
| CN216533394U (en) | Insect pest situation observation and report lamp |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| EXSB | Decision made by sipo to initiate substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |