CN104813993A - Automatic monitoring device and method of micro agricultural insects based on machine vision - Google Patents
Automatic monitoring device and method of micro agricultural insects based on machine vision Download PDFInfo
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Abstract
The invention discloses an automatic monitoring device and an automatic monitoring method of micro agricultural insects based on a machine vision. The automatic monitoring device substantially consists of parts such as an automatic micro agricultural insect trap device, a camera and a computer. The automatic monitoring method substantially comprises the following steps: installing the automatic monitoring device; replacing a sticky insect-capturing plate; collecting a frame of image about the sticky insect-capturing plate; waiting for a while, collecting another frame of image about the sticky insect-capturing plate; applying a differential detection two the recently collected two frames of images about the sticky insect-capturing plate; and automatically counting and classifying the result of the differential detection; outputting the result, judging whether to stop monitoring, and judging whether to replace the sticky insect-capturing plate. The automatic monitoring device and the automatic monitoring method of the micro agricultural insects based on the machine vision can automatically trap the micro agricultural insects without the existence of the insect sex attractant and the high-voltage grid. The trapped insects can be automatically counted and classified by using the machine vision technology, so as to record the information that the number and the category of the trapped insects change with time.
Description
Technical field
The present invention relates to pest automatic monitoring technical field, specifically a kind of small pest automated watch-keeping facility based on machine vision and method.
Background technology
In China's agricultural production, larger small pest mainly Homoptera and dipterous insect is affected on output and economic benefit, includes but not limited to: aphid, plant hopper, Bemisia tabaci, liriomyza bryoniae, fruit bat etc.At present artificial visually examine's investigation method is still taked for the field investigation of these small pest, the method wastes time and energy, investigation result person under investigation person subjective impact is large, in addition basic unit plant protection personnel lack now, field investigation task weight, artificial visually examine's investigation method of this inefficiency can not meet the requirement of agricultural modernization.
In recent years, some new insect automatic monitoring technicals are constantly suggested, monitoring technology main at present has infrared counting technology, picture count technology etc., and the development of these technology improves insect and automatically identifies and the efficiency counted, and greatly facilitates the development of worm monitoring automation.As patent 201410128410.4 discloses a kind of pest trap counting device and number system, this invention first carrys out trapping pests by insects attractant, then infrared counting technology and picture count technology is comprehensively used to count insect, but owing to lacking corresponding insects attractant, this invention can't trap the small pest such as aphid, plant hopper, Bemisia tabaci, liriomyza bryoniae, fruit bat, this invention simultaneously is also provided with high-voltage fence in trapper, also can be burnt by electricity in trapper even if there are small pest to fly to by mistake, thus can not by accurate counting.
Summary of the invention
In order to solve the defect existed in above-mentioned prior art, the invention provides a kind of small pest automated watch-keeping facility based on machine vision and method, can not have automatically to trap small pest in insects attractant and high-voltage fence situation, and utilize machine vision technique to carry out Auto-counting and classification to the insect of traping, the time dependent information of record pest trap value volume and range of product.
The technical solution used in the present invention: a kind of small pest automated watch-keeping facility based on machine vision, comprises support, described support is fixed with initiatively roller bearing, a driven roller bearing and around the insect-sticking plate on active roller bearing and driven roller bearing; Be provided with mythimna separata agent painting brush above described insect-sticking plate, below is provided with mythimna separata agent and removes brush; Described insect-sticking plate surface is removed to brush with mythimna separata agent painting brush and mythimna separata agent and is contacted; Described mythimna separata agent painting brush is connected with a mythimna separata agent storage bin; Described monitoring device is also provided with camera for monitoring insect-sticking plate and calculator.
According to a further aspect in the invention, a kind of small pest automatic monitoring method based on machine vision is provided, comprises the steps:
S1: install small pest automated watch-keeping facility, monitoring device according to claim 1 is arranged on crops field, makes the bottom of insect-sticking plate higher than crops top 10-20 centimetre; By mythimna separata agent filler, mythimna separata agent is added mythimna separata agent storage bin; Regulate the focal length of camera, make monitoring range cover insect-sticking plate;
S2: upgrade insect-sticking plate, rotate instruction is sent to active roller bearing by calculator, initiatively roller bearing rotates, under the assistance of driven roller bearing, insect-sticking plate moves down towards the side of camera, and displacement exceedes the height of insect-sticking plate, in the moving process of insect-sticking plate, mythimna separata agent painting brush is by mythimna separata agent uniform application on insect-sticking plate, and simultaneously mythimna separata agent removes brush by the mythimna separata agent on insect-sticking plate and adhere to superincumbent insect and dispose together with foreign material;
S3: after insect-sticking plate has upgraded, camera gathers the image of a frame insect-sticking plate immediately;
S4: wait for a period of time;
S5: the image of camera collection one frame insect-sticking plate;
S6: contrast stretching and gray processing process are carried out to the two frame insect-sticking plate images gathered recently, then Differential Detection and binary conversion treatment is carried out to two frame gray level images;
S7: carry out mathematical morphology open operator to the binary image that Differential Detection obtains, then marks UNICOM region, and carries out dual threshold screening to UNICOM region, finally carries out Auto-counting and compressive classification to screening the figure spot obtained;
S8: Output rusults, the number of pest increased in the output unit time and kind;
S9: judge whether to stop monitoring, if stop monitoring, then exit, if do not stop monitoring, continues to perform next step;
S10: judge whether to upgrade insect-sticking plate, if the gross area of catching insect current exceedes 60% of insect-sticking plate area, then perform step S2, otherwise performs step S4.
Beneficial effect of the present invention: the small pest automated watch-keeping facility based on machine vision that the present invention announces and method, the investigation for small pest provides a kind of new automatic monitoring method.Do not utilize conventional insects attractant technology in this method, but utilize small pest to the taxis of particular color, designing a kind of automatic trap, achieving the function yet traping small pest when not having sex attractant.Be provided with insect-sticking plate automatic renewing device in automatic trap, this device can according to monitoring needs, timely replacement insect-sticking plate, solve the problem that artificial replacing insect-sticking plate time interval assurance is inaccurate, labour intensity is large.The present invention, by relative with the position of insect-sticking plate for the position of camera fixing, makes the monitoring range of camera just cover whole insect-sticking plate, reduces the difficulty of Differential Detection when insect Auto-counting and classification, improves efficiency and the stability of Differential Detection.The present invention has used mathematical morphology open operator in based on the small pest automatic testing method of machine vision, and connection that can be tiny between fragmentary spot, makes Auto-counting more accurate; Adopt artificial intelligence neural networks model to classify to insect image, nicety of grading is high, good stability.
Accompanying drawing explanation
Fig. 1 is the structural representation of the small pest automated watch-keeping facility of the present invention;
Fig. 2 is the flow chart of the small pest automatic monitoring method of the present invention.
Embodiment
In order to state details and the advantage thereof of technical solution of the present invention better, be now described further by reference to the accompanying drawings.
As shown in Figure 1, a kind of small pest automated watch-keeping facility based on machine vision, comprises support, described support is fixed with initiatively roller bearing 7, a driven roller bearing 4 and around the insect-sticking plate 5 on active roller bearing 7 and driven roller bearing 4; Be provided with mythimna separata agent painting brush 2 above described insect-sticking plate 5, below is provided with mythimna separata agent and removes brush 8; Described insect-sticking plate 5 surface is removed brush 8 with mythimna separata agent painting brush 2 and mythimna separata agent and is contacted; Described mythimna separata agent painting brush 2 is connected with a mythimna separata agent storage bin 3; Described monitoring device is also provided with camera 9 for monitoring insect-sticking plate 5 and calculator 15.
Wherein, described mythimna separata agent storage bin 3 is provided with mythimna separata agent filler 1, and for mythimna separata agent of annotating, meanwhile, the mythimna separata agent in mythimna separata agent storage bin 3 directly contacts with mythimna separata agent painting brush 2, by mythimna separata agent painting brush by mythimna separata agent uniform application on insect-sticking plate 5.
Electromotor is provided with in described active roller bearing 7; Described electromotor is connected with calculator 15 by roller bearing control line 6, the rotation that execution calculator 15 is assigned or halt instruction, and provides power supply by calculation machine 15; Described camera 9 is connected with calculator 15 by camera data wire 14, performs the collection image command that calculator 15 is assigned, and provides power supply by calculation machine 15.The data wire used in embodiment, is USB interface data wire, can provide power supply while transmission information.Insect-sticking plate 5 image that camera 9 gathers, all preserves in the computer 15, and comprises acquisition time and number information, when needed, can have access at any time, thus further ensure the accuracy of monitoring result.
Described support comprises the A-frame 12 being positioned at bottom and the expansion link 11 be arranged on A-frame 12, and described expansion link 11 is provided with set bolt 10; Described camera 9 is fixed on expansion link 11 top by camera fixing support 13; Described insect-sticking plate 5, its color can select yellow, blueness or white as required, and in the present embodiment, insect-sticking plate 5 selects yellow; Described active roller bearing 7, its girth, slightly larger than 1/3 of insect-sticking plate 5 height, therefore, when upgrading insect-sticking plate 5, only need control initiatively roller bearing 73 circles that roll and can complete 1 renewal.
As shown in Figure 2, a kind of small pest automatic monitoring method based on machine vision, concrete steps are as follows:
S1: install automated watch-keeping facility, with A-frame 12, monitoring device is fixed on crops field, adjustable telescopic rod 11, makes insect-sticking plate 5 bottom higher than crops top 10-20 centimetre, then fix expansion link 11 with set bolt 10; Connect initiatively roller bearing 7 and calculator 15 with roller bearing control line 6, connect monitoring camera 9 and calculator 15 with data wire 14; By filler 1, mythimna separata agent is filled into mythimna separata agent storage bin 3; Regulate the focal length of monitoring camera 9, make the monitoring range of monitoring camera 9 just cover insect-sticking plate 5;
S2: upgrade insect-sticking plate 5, send rotate instruction by calculator 15 to active roller bearing 7, initiatively roller bearing 7 average rate rotates 3 weeks, under the assistance of driven roller bearing 4, initiatively roller bearing 7 drives insect-sticking plate 5 to move down towards the side of camera, and displacement exceedes the height of insect-sticking plate 5; Insect-sticking plate 5 top when painting brush 2, painting brush 2 by the mythimna separata agent uniform application in mythimna separata agent storage bin 3 on insect-sticking plate 5; Insect-sticking plate 5 bottom, in time removing brush 8, is removed brush 8 and the mythimna separata agent on insect-sticking plate 5 and the insect be attached in mythimna separata agent is removed;
S3: after insect-sticking plate 5 has upgraded, monitoring camera 9 gathers the image of an insect-sticking plate 5 immediately, and time numbering is designated as t
i(i=1), picture number is designated as m
i(i=1), gather image storage format be JPG form, color mode is rgb format;
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, time numbering is designated as t
i, picture number is designated as m
i;
S6: contrast stretching and gray processing process are carried out to the image of the two frame insect-sticking plates 5 gathered recently, then Differential Detection and binaryzation is carried out to two frame gray level images;
Contrast stretching, first to the RGB image m of the two frame insect-sticking plates 5 gathered recently before Differential Detection
iand m
i-1carry out IHS conversion, obtain brightness (Intensity, I), colourity (Hue, H), degree of saturation (Saturation, S) three components, then get the luminance component I of two two field pictures after IHS conversion
iand I
i-1, ask its associating grey level histogram, according to joint histogram respectively to I
iand I
i-1carry out contrast stretching, finally with the luminance component I ' after stretching
iwith I '
i-1carry out IHS inverse transformation with respective colourity, degree of saturation component, obtain the RGB image m ' after contrast stretching
iwith m '
i-1;
Image gray processing process, by RGB image m '
iwith m '
i-1be converted to gray level image f
iand f
i-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 f
iand f
i-1carry out Differential Detection as follows:
f
Δt(x,y)＝f
i(x,y)-f
i-1(x,y)
Wherein, Δ t=t
i-t
i-1, f
Δ t(x, y) is the gray scale differences of two frame gray level images at xth row, y row;
Binary conversion treatment, uses maximum variance between clusters to set a rational threshold value T
f, to Differential Detection result f
Δ tcarry out binaryzation, obtain the binary image B of Differential Detection result
i, binaryzation is undertaken by following formula:
At the binary image B of Differential Detection result
iintermediate value be 1 pixel be considered as the insect that newly catches within the Δ t time, value be 0 pixel be considered as background or t
i-1the insect caught before moment;
S7: carry out mathematical morphology open operator to the binary image that Differential Detection obtains, then marks UNICOM region, and carries out dual threshold screening to UNICOM region, finally carries out Auto-counting and compressive classification to screening the figure spot obtained;
Mathematical morphology open operator, with radius be 1 disc structure element mathematical morphology open operator is carried out to the binary picture spot that Differential Detection obtains, namely the computing of advanced line number morphological erosion is with connection tiny between fragmentary spot, and then carries out mathematical morphology dilation operation;
Mark UNICOM region, finds all UNICOMs region according to eight neighborhood, and marks respectively, and each mark UNICOM region is by as an alternative figure spot;
Dual threshold screens, and sets 2 threshold value T
bminand T
bmax, represent lower limit and the upper limit of small pest area respectively, all alternative figure spots screened, remove area and be greater than the upper limit or be less than the figure spot of lower limit;
Auto-counting, screens to dual threshold the figure spot obtained and carries out Auto-counting, and the quantity of figure spot is exactly trap the number of pest arrived in the Δ t time;
Compressive classification, screens the figure spot that obtains as masking-out using dual threshold, obtain coloured image m '
iin the colouring information of each figure spot, calculate 3 eigen values such as the color average of each figure spot, area and aspect ratio, and be entered into the artificial intelligence neural networks model trained and classify, the insect that insect-sticking plate 5 is traped is divided into 4 classes by model, wherein, type I represents alatae worm, and type II represents Bemisia tabaci, type III represents fruit bat, and Type IV represents other;
S8: Output rusults, exports the number of pest and kind that in the current Δ t time, insect-sticking plate 5 increase;
S9: judge whether to stop monitoring, if stop monitoring, then exit, if do not stop monitoring, continues to perform next step;
S10: judge whether to upgrade insect-sticking plate 5, if the insect gross area of catching current exceedes 60% of insect-sticking plate 5 area, then perform step S2, otherwise performs step S4.
Claims (10)
1. the small pest automated watch-keeping facility based on machine vision, it is characterized in that: comprise support, described support is fixed with initiatively roller bearing (7), a driven roller bearing (4) and around the insect-sticking plate (5) on active roller bearing (7) and driven roller bearing (4); Described insect-sticking plate (5) top is provided with mythimna separata agent painting brush (2), and below is provided with mythimna separata agent and removes brush (8); Described insect-sticking plate (5) surface and mythimna separata agent painting brush (2) and mythimna separata agent are removed and are brushed (8) and contact; Described mythimna separata agent painting brush (2) is connected with a mythimna separata agent storage bin (3); Described monitoring device is also provided with camera (9) for monitoring insect-sticking plate (5) and calculator (15).
2. the small pest automated watch-keeping facility based on machine vision according to claim 1, is characterized in that: described mythimna separata agent storage bin (3) is provided with mythimna separata agent filler (1).
3. the small pest automated watch-keeping facility based on machine vision according to claim 1, is characterized in that: be provided with electromotor in described active roller bearing (7); Described electromotor is connected with calculator (15) by roller bearing control line (6), the rotation that execution calculator (15) is assigned or halt instruction, and provides power supply by calculation machine (15); Described camera (9) is connected with calculator (15) by camera data wire (14), performs the collection image command that calculator (15) is assigned, and provides power supply by calculator (15).
4. the small pest automated watch-keeping facility based on machine vision according to claim 1, it is characterized in that: described support comprises the A-frame (12) being positioned at bottom and the expansion link (11) be arranged on A-frame (12), and described expansion link (11) is provided with set bolt (10).
5. the small pest automated watch-keeping facility based on machine vision according to claim 1, is characterized in that: described camera (9) is fixed on the top of expansion link (11) by camera fixing support (13).
6. the small pest automated watch-keeping facility based on machine vision according to claim 1, is characterized in that: described insect-sticking plate (5), and its color is yellow, blue or white.
7., based on a small pest automatic monitoring method for machine vision, it is characterized in that, comprise the following steps:
S1: install small pest automated watch-keeping facility, monitoring device according to claim 1 is arranged on crops field, makes the bottom of insect-sticking plate (5) higher than crops top 10-20 centimetre; By mythimna separata agent filler (1), mythimna separata agent is added mythimna separata agent storage bin (3); Regulate the focal length of camera (9), make monitoring range cover insect-sticking plate (5);
S2: upgrade insect-sticking plate (5), rotate instruction is sent to active roller bearing (7) by calculator (15), initiatively roller bearing (7) rotates, under the assistance of driven roller bearing (4), insect-sticking plate (5) moves down towards the side of camera (9), and displacement exceedes the height of insect-sticking plate (5), in the moving process of insect-sticking plate (5), mythimna separata agent painting brush (2) by mythimna separata agent uniform application on insect-sticking plate (5), simultaneously mythimna separata agent removes brush (8) by the mythimna separata agent on insect-sticking plate (5) and adhere to superincumbent insect and dispose together with foreign material,
S3: after insect-sticking plate (5) has upgraded, 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 and gray processing process are carried out to the image of the two frame insect-sticking plates (5) gathered recently, then Differential Detection and binary conversion treatment is carried out to two frame gray level images;
S7: carry out mathematical morphology open operator to the binary image that Differential Detection obtains, then marks UNICOM region, and carries out dual threshold screening to UNICOM region, finally carries out Auto-counting and compressive classification to screening the figure spot obtained;
S8: Output rusults, the number of pest increased in the output unit time and kind;
S9: judge whether to stop monitoring, if stop monitoring, then exit, if do not stop monitoring, continues to perform next step;
S10: judge whether to upgrade insect-sticking plate (5), if the gross area of catching insect current exceedes 60% of insect-sticking plate (5) area, then perform step S2, otherwise performs step S4.
8. the small pest automatic monitoring method based on machine vision according to claim 7, it is characterized in that: the image storage format gathered in step S3 and step S5 is JPG form, color mode is rgb format.
9. the small pest automatic monitoring method based on machine vision according to claim 7, is characterized in that: in step S6, the computing formula of Differential Detection is:
f
Dt(x,y)＝f
i(x,y)-f
i-1(x,y)
Wherein, f
iand f
i-1for gray level image numbering, f
dt(x, y) is the gray scale difference of two frame gray level images; The binaryzation of Differential Detection result is undertaken by following formula:
Wherein, B
ifor the binary image of Differential Detection result, T
ffor binary-state threshold, f
dtfor Differential Detection result.
10. the small pest automatic monitoring method based on machine vision according to claim 7, it is characterized in that: the compressive classification in step S7, concrete steps are dual threshold is screened the figure spot that obtains as masking-out, obtain the colouring information of the nearest color image frame after contrast stretching, calculate 3 eigen values such as the color average of each figure spot, area and aspect ratio, and be entered into the artificial intelligence neural networks model trained and classify.
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| CN114689800A (en) * | 2022-03-29 | 2022-07-01 | 双工方程(武汉)科技发展有限公司 | Layer-leaning separation method of automatic monitoring and counting system for tobacco leaf pests in storage |
| 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 |
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