CN108921067A - A kind of method, apparatus, equipment and system counting agricultural pests - Google Patents
A kind of method, apparatus, equipment and system counting agricultural pests Download PDFInfo
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- CN108921067A CN108921067A CN201810650987.XA CN201810650987A CN108921067A CN 108921067 A CN108921067 A CN 108921067A CN 201810650987 A CN201810650987 A CN 201810650987A CN 108921067 A CN108921067 A CN 108921067A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M1/00—Stationary means for catching or killing insects
- A01M1/02—Stationary means for catching or killing insects with devices or substances, e.g. food, pheronones attracting the insects
- A01M1/04—Attracting insects by using illumination or colours
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
Abstract
The embodiment of the invention discloses a kind of statistics agricultural pests quantitative approach, device, equipment and systems, including：Pest image is received, image boundary detection is carried out to carry out identification marking to brightness change visibility point in pest image to pest image.Region segmentation is carried out to obtain segmented image to pest image according to boundary marking.Binary image is obtained according to segmented image, binary image includes at least one first join domain generated according to cut zone.According to the elemental area of each first join domain and preset pest elemental area, the second join domain for corresponding to pest in the first join domain is obtained.Pest label, and the superposition pest number marked according to the second join domain are overlapped to the second join domain, calculate the number of pest that pest image includes.The present invention solves the problems, such as that pest identification, incremental data obtain upper time-consuming, laborious and can specifically recognize that the number of pest of which period is relatively more.
Description
Technical field
The present invention relates to electronic technology field, more particularly to a kind of statistics agricultural pests quantitative approach, device, equipment and
System.
Background technique
China is large agricultural country, and agriculture sound development is concerning national roots.In recent years, mentioning with national life level
Height, consumer are higher and higher for the quality of agricultural product and the requirement of safety.In agricultural production process, control of insect is agriculture
Therefore the important factor in order of crop quality realizes that the accurate acquisition to pest identification and quantity information is insect pest forecast forecast
Primary work.If be impossible to without correct sample investigation data to the Number dynamics of pest, the extent of injury of pest
It is accurately predicted, less can guarantee the correct execution of Economic Threshold of Injurious Insect Control.
Traditional pest identification with count mainly using manual identified method, field investigation method, trap method etc., manual identified with
Agricultural pests are counted since field conditions are complicated, that seriously there is discriminations is low for the factors such as unstable, count accuracy is poor, field
The disadvantages of task large labor intensity, non real-time nature, this method have been unable to meet the monitoring that critical conditions occur for current agricultural pests
It is required that；Field investigation method is time-consuming, laborious, and the investigation of data, the link that records, report are more, and the heavy workload of monitoring personnel is main
Sight factor influences big, the poor in timeliness of data application, influences the Accurate Prediction forecast of pest, is not able to satisfy production actual demand.
Summary of the invention
The purpose of the present invention is to overcome the deficiency in the prior art, provides a kind of statistics agricultural pests quantitative approach, device, sets
Standby and system specifically includes as follows：
In a first aspect, the embodiment of the present invention provides a kind of statistics agricultural pests quantitative approach comprising following steps：
Receive pest image；
Image boundary detection is carried out to carry out identification mark to brightness change visibility point in pest image to pest image
Know, obtains boundary marking；
Region segmentation is carried out to obtain segmented image to pest image according to boundary marking；Segmented image includes at least one
Closed cut zone；
Binary image is obtained according to segmented image；Wherein, binary image includes being generated at least according to cut zone
One the first join domain；
According to the elemental area of each first join domain and preset pest elemental area, the first join domain is obtained
In correspond to pest the second join domain；
Pest label, and the superposition pest marked according to each second join domain are overlapped to the second join domain
Number calculates the number of pest that pest image includes.
Further, after receiving pest image, image boundary detection is carried out to scheme to the pest to pest image
Brightness change visibility point carries out identification marking as in, includes before obtaining boundary marking：
Image reinforcement processing is carried out to pest image using frequency algorithm.
Further, obtaining binary image according to segmented image is specially：
S1 carries out gray processing operation to segmented image, obtains gray level image；
S2 calculates the average gray Y0 of gray level image；
S3, setting Y1 are the average gray of the pixel less than or equal to Y0, and setting Y2 is that the gray scale of the pixel greater than Y0 is flat
Mean value；
S4 calculates iteration threshold Y；Wherein Y=(Y1+Y2)/2；
S5 compares Y and Y0, if equal, exports Y as binarization threshold；Otherwise average gray Y0 is updated to Y,
And return step S3；
S6 carries out binary conversion treatment to the gray level image, obtains binary image according to the binarization threshold of output.
Further, pest label is overlapped to second join domain, and according to each second area label
It is superimposed pest number, the number of pest that pest image includes is calculated and specifically includes：
According to the pixel value gradient transform characteristics of gray level image, the superposition pest number of each second join domain is calculated, and
Superposition pest number is tagged to corresponding second join domain；
According to the superposition pest number that each second area marks, the number of pest that pest image includes is calculated.
Second aspect, the embodiment of the present invention provide a kind of device for counting agricultural pests quantity, and described device includes：
Image receiver module, for receiving pest image；
Boundary recognition module, for carrying out image boundary detection to pest image with obvious to brightness change in pest image
Position carry out identification marking, obtain boundary marking；
Image segmentation module, for carrying out region segmentation to the pest image according to the boundary marking to be divided
Image；Segmented image includes at least one closed cut zone；
First join domain module, for obtaining binary image according to segmented image；Wherein, binary image includes root
At least one first join domain generated according to cut zone；
Second join domain module, for according to each first join domain elemental area and preset pest pixel
Area obtains the second join domain for corresponding to pest in the first join domain；
Number calculating section, for being overlapped pest label to the second join domain, and according to each second bonding pad
The superposition pest number of field mark calculates the number of pest that the pest image includes.
The third aspect, the embodiment of the present invention provide a kind of equipment for counting agricultural pests quantity, including：Controller, switch
Circuit, light trap, camera；Controller is connect with the switching circuit, light trap, camera；
Camera for acquiring the image for the pest trapped and killed, and sends an image to the controller；
Switching circuit is connect with light trap；
Controller includes memory and processor, and memory includes executable code, and executable code can be processed
Device executes, the method to realize statistics agricultural pests quantity as described in relation to the first aspect.
It further, further include at least one environmental detection sensor；Environmental detection sensor is for detecting current environment
Environmental parameter, and environmental parameter is sent to controller；
Count agricultural pests quantity method, further include：
The environmental parameter sent by environmental detection sensor is received, and according to environmental parameter, controls the switch of light trap.
Further, environmental detection sensor includes：Raindrop sensor, Temperature Humidity Sensor, illuminance sensor, wind speed
Detection sensor；The wind speed measurement sensor, the Raindrop sensor, the Temperature Humidity Sensor and illuminance sensing
Device is connect with the controller；
Air velocity transducer includes Hall sensor and vane sensor, and the Hall sensor and the vane sensor connect
It connects, for detecting ambient wind velocity data；
Then according to the environmental parameter, the switch of light trap is controlled, specially：
Judge whether the illuminance numerical value of illuminance sensor detection is greater than 1LX, if so, entering trapping for day time
Lamp closed state；
If it is not, being then, then continue to judge whether the output level of Raindrop sensor detection is low level the time in the evening；
If low level, it is judged as rainy, then closes light trap；
If high level, then continue to judge whether the wind speed numerical value of air velocity transducer detection is greater than 5 grades；
If so, closing light trap；
If it is not, then continue to judge Temperature Humidity Sensor detection temperature whether≤20 DEG C or humidity whether≤50%；
If so, closing light trap；
If it is not, then opening light trap.
Further, further include：NB-IOT module connected to the controller, for leading to number of pest and environmental information
Cross the trapping lamp switch that cloud service center is sent to user terminal or sends for receiving user terminal by cloud service center
Instruction；
Power circuit, solar controller and solar panels；Power circuit is connect with solar controller, solar control
Device is connect with solar panels；
For giving the power supply circuit of each power elements；Power supply circuit is connect with the controller；
For generating the clock circuit of periodically pulsing signal, clock circuit is connect with controller.
For removing the motor and pest collector of pest corpse, motor connects with switching circuit and pest collector respectively
It connects；The image pickup part face pest collector of camera.
Fourth aspect, the embodiment of the present invention provide a kind of statistics agricultural pests quantity system, including cloud service center, user
Terminal and the statistics agricultural pests number of devices as described in third aspect any one；Statistics agricultural pests quantity device passes through
Cloud service center is communicated with user terminal.
Implement the embodiment of the present invention, there are following advantageous effects：
By camera connected to the controller, during light trap is opened, it can take pictures, control for the timing of pest collector
Device processed further carries out image recognition processing calculating by the quantity of insect-killing trapping to taking a picture.Solves pest identification, quantity
Time-consuming on data acquisition, laborious problem and it can specifically recognize that the number of pest of which period is relatively more.
Detailed description of the invention
In order to illustrate more clearly of technical solution of the present invention, attached drawing needed in embodiment will be made below
Simply introduce, it should be apparent that, the accompanying drawings in the following description is only some embodiments of the present invention, general for this field
For logical technical staff, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow diagram of statistics agricultural pests quantitative approach of first embodiment provided by the invention.
Fig. 2 is a kind of acquisition binary image of statistics agricultural pests quantitative approach of first embodiment provided by the invention
Flow diagram.
Fig. 3 is a kind of structural schematic diagram of statistics agricultural pests quantity device of second embodiment provided by the invention.
Fig. 4 is a kind of statistics agricultural pests number of devices structural schematic diagram of 3rd embodiment provided by the invention.
A kind of statistics agricultural pests number of devices of Fig. 5 3rd embodiment provided by the invention be with cloud service center and
The interaction schematic diagram of user terminal.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
First embodiment of the invention：
Referring to Fig. 1 and Fig. 2, Fig. 1 is a kind of stream for statistics agricultural pests quantitative approach that first embodiment of the invention provides
Journey schematic diagram, Fig. 2 are a kind of acquisition binary picture of statistics agricultural pests quantitative approach of first embodiment provided by the invention
The flow diagram of picture.Specifically comprise the following steps：
S10 receives pest image.
The image pickup part face pest collector of camera is timed or periodically takes pictures, and processor is fetched from receipts camera shooting
Head captured by pest picture, wherein camera can be the infrared photosensitive night vision cam of 5,000,000 pixel of IR-CUT, adjustable focus,
With handoff functionality on daytime at night.The camera sensitive chip can be OV 5647, and aperture 1.8, field angle is 75.7 degree, have
Conducive to the picture of shooting clear.
S20 carries out image boundary detection to institute's pest image to carry out to brightness change visibility point in pest image
Identification marking obtains boundary marking；
The purpose of border detection is brightness change visibility point in mark pest image, thus the wheel to determine pest corpse
Exterior feature is conducive to identification and the quantity statistics of pest.
S30 carries out region segmentation to the pest image according to boundary marking to obtain segmented image；Segmented image includes
At least one closed cut zone.
Based on the profile of the pest corpse detected, pest image is divided into certain amount and with the area of certain feature
Domain, each region split have similitude for texture, are connection inside region to certain property such as gray scale of pest
And without excessive aperture, zone boundary be it is specific, adjacent area has apparent difference to property based on segmentation, can be
Interested target pest is further extracted to lay the foundation.
S40 obtains binary image according to segmented image；Wherein, binary image includes being generated according to cut zone
At least one first join domain；
Binarization operation is in order to simplify image, if region of the image without containing connection after binaryzation, just gives up this
A image, if being just further processed there are also the region of connection and being determined as the first join domain.
S50 obtains the first connection according to the elemental area of each first join domain and preset pest elemental area
Correspond to the second join domain of pest in region；
When the elemental area S0 of pest corpse is threshold value, the pest image of S0 is more than or equal to the first join domain area
Join domain is marked, and obtains the second join domain.All the second labeled join domain quantity are counted, pest can be obtained
Quantity.S0 is the elemental area of pest corpse, and S0 is calculated according to the pixel of the pest image of standard.
S60 is overlapped pest label to the second join domain, and according to the superposition evil of each second join domain label
Borer population calculates the number of pest that the pest image includes.
The feature converted using gray processing pest image pixel value gradient, the pest corpse being superimposed is marked
It separates, is conducive to the correct statistics of number of pest.Preferably, what can be generated during pest image binaryzation is some miscellaneous
Point after being overlapped pest label by the pest to the second join domain, further carries out the miscellaneous point removal of binaryzation, this has
Conducive to more accurate statistics number of pest.
On the basis of first embodiment, in a preferred embodiment of the present invention, it is included in after receiving pest image,
Image boundary detection is carried out to carry out identification marking to brightness change visibility point in pest image to pest image, obtains side
Boundary mark is known includes before：Image reinforcement processing is carried out to pest image using frequency algorithm.Since the influence of environment causes pest
Picture quality is lower, needs to carry out reinforcement processing to picture quality using frequency algorithm, wants if image is not met also after reinforcing
It asks, then carries out pest image photographic again.
Referring to fig. 2, on the basis of first embodiment, in a preferred embodiment of the present invention, including according to described point
Cutting image acquisition binary image is specially：
S1 carries out gray processing operation to segmented image, obtains gray level image.
S2 calculates the average gray Y0 of gray level image.
S3, setting Y1 are the average gray of the pixel less than or equal to Y0, and setting Y2 is that the gray scale of the pixel greater than Y0 is flat
Mean value.
S4 calculates iteration threshold Y；Wherein Y=(Y1+Y2)/2.
S5 compares Y and Y0, if equal, exports Y as binarization threshold；Otherwise average gray Y0 is updated to Y,
And return step S3.
S6 carries out binary conversion treatment to the gray level image, obtains binary image according to the binarization threshold of output.
Pest image includes pest corpse, ambient noise etc., and setting a threshold value Y can be pest corpse from image
Extract carry out quantity statistics.
Second embodiment of the invention：
Referring to Fig. 3, Fig. 3 is that a kind of structure of statistics agricultural pests quantity device of second embodiment provided by the invention is shown
It is intended to.Second embodiment of the invention provides a kind of device for counting agricultural pests quantity, specifically includes：
Image receiver module 101, for receiving pest image.
Boundary recognition module 102, for carrying out image boundary detection in the pest image to the pest image
Brightness change visibility point carries out identification marking, obtains boundary marking.
Image segmentation module 103, for carrying out region segmentation to the pest image according to the boundary marking to obtain
Segmented image；The segmented image includes at least one closed cut zone.
First join domain module 104, for obtaining binary image according to the segmented image；Wherein, the two-value
Changing image includes at least one first join domain generated according to the cut zone.
Second join domain module 105, for according to each first join domain elemental area and preset pest
Elemental area obtains the second join domain for corresponding to pest in the first join domain.
Number calculating section 106, for being overlapped pest label to second join domain, and according to each second
The superposition pest number of join domain label, calculates the number of pest that the pest image includes.
Boundary recognition module 102, further include after receiving pest image, to pest image carry out image boundary detection with
Identification marking is carried out to brightness change visibility point in the pest image, includes before obtaining boundary marking：
Image reinforcing module, for carrying out image reinforcement processing to pest image using frequency algorithm.
On the basis of second embodiment, in a preferred embodiment of the present invention, including obtained according to the segmented image
Obtaining binary image is specially：
Image gray processing module obtains gray level image for carrying out gray processing operation to segmented image；
Averaging module is calculated, for calculating the average gray Y0 of gray level image；
Setup module, for the average gray that Y1 is the pixel less than or equal to Y0 to be arranged, setting Y2 is the picture greater than Y0
The average gray of element；
Iteration threshold module is calculated, for calculating iteration threshold Y；Wherein Y=(Y1+Y2)/2；
Comparison module, if equal, exports Y as binarization threshold for comparing Y and Y0；Otherwise by average gray
Y0 is updated to Y, and return step S3；
Binarization block carries out binary conversion treatment to the gray level image, obtains for the binarization threshold according to output
Binary image.
On the basis of second embodiment, in a preferred embodiment of the present invention, number calculating section 106 further includes：
Gradient conversion module calculates each second bonding pad for the pixel value gradient transform characteristics according to gray level image
The superposition pest number in domain, and superposition pest number is tagged to corresponding second join domain, then according to each second area mark
The superposition pest number of note calculates the number of pest that pest image includes.
Third embodiment of the invention：
Referring to fig. 4 and Fig. 5, Fig. 4 be 3rd embodiment provided by the invention a kind of statistics agricultural pests number of devices knot
A kind of statistics agricultural pests number of devices of structure schematic diagram, Fig. 5 3rd embodiment provided by the invention be and cloud service center with
And the interaction schematic diagram of user terminal.Third embodiment of the invention provides a kind of equipment for counting agricultural pests quantity, specific to wrap
It includes：
Controller 100, switching circuit 16, light trap 15, camera 13；Controller 100 and switching circuit 16, light trap
15, camera 13 connects；The camera 13 is sent to institute for acquiring the image for the pest trapped and killed, and by described image
State controller 100；The switching circuit 16 is connect with the light trap 15；The controller 100 includes memory 17 and place
Device 1 is managed, the memory 17 includes executable code, and the executable code can be executed by the processor 1, to realize such as
The method of agricultural pests quantity is counted described in first embodiment of the invention.Memory 17 includes 1GB memory and 16GB SD card,
(SuSE) Linux OS is run and stored for secondary processor 1, while assist process device 1 completes image recognition and operation algorithm
To calculate by the quantity of insect-killing trapping.
It further include that at least one environment measuring passes on the basis of 3rd embodiment, in a preferred embodiment of the present invention
Sensor 200；The environmental detection sensor 200 is used to detect the environmental parameter of current environment, and the environmental parameter is sent
To controller 100.
It is described statistics agricultural pests quantity method, further include：
The environmental parameter sent by environmental detection sensor 200 is received, and according to the environmental parameter, controls light trap 15
Switch.Environmental detection sensor 100 includes：Raindrop sensor 4, Temperature Humidity Sensor 5, illuminance sensor 12, wind speed inspection
Survey sensor；Wind speed measurement sensor, Raindrop sensor 4, Temperature Humidity Sensor 5, illuminance sensor 12 and controller 100 connect
It connects.
Air velocity transducer includes Hall sensor 2 and vane sensor 3, and Hall sensor is connect with vane sensor, is used
In detection ambient wind velocity data.Symmetrically placed two of vane sensor 3 on Hall sensor 2 and face Hall sensor 2
Button magnet is constituted；The 3 magnetic field induction detection sensitivity of vane sensor is high, whenever vane sensor 3 passes through with moving magnet
Primary current variation will be generated an at time, can measure wind speed by calculating.
For Raindrop sensor 4 when not having rainwater on the Raindrop sensor plate 4, the level of output is high level；It is rainy
When drop is on Raindrop sensor 4, output reforms into low level, and processor 1 may know that by the judgement to high and low level
Whether have rainy.
Illuminance sensor 12 has measurement range using there is the silicon blue streak of higher sensitivity to lie prostrate detector element to dim light
Advantage wide, Linearity is good, can be used to the light conditions around detecting devices, and Lighting information can be used to judge weather darkness feelings
Condition, while being also used to detect whether light trap 15 works normally.
Then according to environmental parameter, the switch of light trap is controlled, specially：
After agricultural pests trap and kill detecting devices electrifying startup, which, which first checks whether, " is received in cloud service
The order of the heart " first carries out cloud service center order and carries out opening or closing light trap；If not from the life of cloud service center
It enables, then further checks " illuminance sensor numerical value "；Judge whether the illuminance numerical value of the illuminance sensor detection is big
In 1LX, if so, entering light trap closed state for day time；If it is not, being then, then continue described in judgement the time in the evening
Whether the output level of Raindrop sensor detection is low level；If low level, it is judged as rainy, then closes light trap；If
High level then continues to judge whether the wind speed numerical value of the air velocity transducer detection is greater than 5 grades；If so, closing light trap；If
Be not then continue to judge Temperature Humidity Sensor detection temperature whether≤20 DEG C or humidity whether≤50%；It is lured if so, closing
Kill lamp；If it is not, then opening light trap.
On the basis of 3rd embodiment, further include in a preferred embodiment of the present invention：It is connect with controller 100
NB-IOT module 10, for number of pest and environmental information to be sent to user terminal 20 by cloud service center 19 or used
Pass through 15 switch order of light trap that cloud service center 19 is sent in receiving user terminal 20.
The wireless device that NB-IOT module 10 can provide 50-100 times than existing wireless technology accesses number, can reduce object
The data communication expense of networked devices.Meanwhile NB-IOT module 10 focuses small data quantity, small rate application, therefore NB-IOT is set
Standby power consumption can accomplish very small, can ensure the service life of battery.Agricultural pests trap and kill equipment holder and pass through user's end
20 access cloud service centers 19 of end, can real time inspection insect pest situation and environmental data, and can remotely control agricultural pests trapping equipment
Camera 13 and light trap 15.User terminal in the present embodiment can be mobile terminal 20 or make the mobile communication terminal to be
Refer to the computer equipment that can use on the move, broad sense say including personal computer (Personal Computer, PC),
Personal digital assistant (Personal Digital Assistant, PDA), mobile phone (Mobile Phone, MP), POS machine
The electronic equipment that can be even communicated wirelessly including vehicle-mounted computer etc..The present embodiment processor uses high-performance low-power-consumption chip
Module such as ARM Cortex-A53, it provides a powerful operational capability, cooperates (SuSE) Linux OS, can efficiently realize
Image recognition and the operation for being reinforced threshold value iteration pest statistic algorithm (PSA-IEIT) based on image, are realized by insect-killing trapping quantity
Automatic acquisition.Processor 1 can be realized the solution to NB-IOT communication signaling between NB-IOT module 10 and cloud service center 19
NB-IOT wireless communication is realized in analysis.To help to establish the WAN equipment network for supporting that communication distance is remote, energy consumption is low,
Reach the performance requirement of the agricultural pests trapping and detecting devices.
On the basis of 3rd embodiment, further include in a preferred embodiment of the present invention：Power circuit 8, solar energy
Controller 7, solar panels 6, for the power supply circuit 11 to each power elements, the clock for generating periodically pulsing signal
Circuit 9, motor 10 and pest collector 14 for removing pest corpse.Power circuit 8 is connect with solar controller 7, too
Sun can control device 7 and electricity of 6 connection management of solar panels from solar panels 6.Power supply circuit is connect with controller 100.When
Clock circuit 9 is connect with controller 100.Motor 18 is connect with switching circuit 16 and pest collector 14 respectively.Switching circuit 16 can
To control coupled trapping lamp module 15, according to the order from processor 1, the open and close of light trap 15 are controlled.
The pest trapped and killed is stored in the pest collector 14 being made by white moulding material.Pest described in the image pickup part face of camera 13
Collector 14.Camera 13 can take pictures for 14 timing of pest collector, and processor 1 further carries out image knowledge to taking a picture
Other places reason, and reinforce threshold value iteration pest statistic algorithm (PSA-IEIT) using image to calculate by the quantity of insect-killing trapping.It takes the photograph
As head 13 can be the infrared photosensitive night vision cam of 5,000,000 pixel of IR-CUT, adjustable focus, and have handoff functionality on daytime at night.
The camera sensitive chip can be OV 5647, and aperture 1.8, field angle is 75.7 degree.Take pictures and number of pest count successfully it
Afterwards, using motor circuit 19, pest collector 14 can be overturn, removes pest corpse, taken pictures for next time and image recognition is done
It is good to prepare.
Preferably, it counts and is set on agricultural pests device there are two two dimensional code, the equipment holder uses smart phone
One of two dimensional code downloading smart phone client in the equipment is scanned, scans another two dimensional code for the equipment
It is bound with the smart phone.User is facilitated to download smart phone client by the way that two dimensional code is arranged, APP need to only download installation one
Secondary, for the equipment of subsequent purchase, equipment and smart phone can be bound by directly scanning the two-dimensional code, and facilitate user to equipment
Use and manage.
Fourth embodiment of the invention：
Fourth embodiment of the invention provides a kind of statistics agricultural pests quantity system, including cloud service center, user terminal
And a kind of statistics agricultural pests number of devices as described in the third embodiment of the present invention；Statistics agricultural pests quantity device passes through cloud
Service centre is communicated with user terminal.
Processor alleged by the present invention can be central processing unit (Central Processing Unit, CPU), may be used also
To be other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
It is the control centre of the statistics agricultural pests quantitative approach Deng, the processor, it is entire using various interfaces and connection
The various pieces for realizing statistics agricultural pests quantitative approach.
The memory can be used for storing the computer program and/or module, and the processor is by operation or executes
Computer program in the memory and/or module are stored, and calls the data being stored in memory, realizes statistics
The various functions of agricultural pests quantitative approach.The memory can mainly include storing program area and storage data area, wherein deposit
Storing up program area can application program needed for storage program area, at least one function (such as sound-playing function, text conversion function
Energy is equal) etc.；Storage data area, which can be stored, uses created data (such as audio data, text message data according to mobile phone
Deng) etc..In addition, memory may include high-speed random access memory, it can also include nonvolatile memory, such as firmly
Disk, memory, plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital,
SD) card, flash card (Flash Card), at least one disk memory, flush memory device or other volatile solid-states
Part.
Wherein, if the module for realizing service equipment is realized in the form of SFU software functional unit and as independent production
Product when selling or using, can store in a computer readable storage medium.Based on this understanding, the present invention realizes
All or part of the process in above-described embodiment method can also instruct relevant hardware to complete by computer program,
The computer program can be stored in a computer readable storage medium, which is being executed by processor
When, it can be achieved that the step of above-mentioned each embodiment of the method.Wherein, the computer program includes computer program code, described
Computer program code can be source code form, object identification code form, executable file or certain intermediate forms etc..The meter
Calculation machine readable medium may include：Can carry the computer program code any entity or device, recording medium, USB flash disk,
Mobile hard disk, magnetic disk, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory
Device (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It needs to illustrate
It is that the content that the computer-readable medium includes can be fitted according to the requirement made laws in jurisdiction with patent practice
When increase and decrease, such as in certain jurisdictions, according to legislation and patent practice, computer-readable medium does not include electric carrier wave letter
Number and telecommunication signal.
It should be noted that the apparatus embodiments described above are merely exemplary, wherein described be used as separation unit
The unit of explanation may or may not be physically separated, and component shown as a unit can be or can also be with
It is not physical unit, it can it is in one place, or may be distributed over multiple network units.It can be according to actual
It needs that some or all of the modules therein is selected to achieve the purpose of the solution of this embodiment.In addition, device provided by the invention
In embodiment attached drawing, the connection relationship between module indicate between them have communication connection, specifically can be implemented as one or
A plurality of communication bus or signal wire.Those of ordinary skill in the art are without creative efforts, it can understand
And implement.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by anyone skilled in the art,
It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with scope of protection of the claims
Subject to.
Claims (10)
1. a kind of method for counting agricultural pests quantity, which is characterized in that including：
Receive pest image；
Image boundary detection is carried out to know to brightness change visibility point in the pest image to the pest image
It does not identify, obtains boundary marking；
Region segmentation is carried out to obtain segmented image to the pest image according to the boundary marking；The segmented image includes
At least one closed cut zone；
Binary image is obtained according to the segmented image；Wherein, the binary image includes raw according to the cut zone
At at least one first join domain；
According to the elemental area of each first join domain and preset pest elemental area, it is right in the first join domain to obtain
It should be in the second join domain of pest；
Pest label, and the superposition pest marked according to each second join domain are overlapped to second join domain
Number, calculates the number of pest that the pest image includes.
2. a kind of method for counting agricultural pests quantity according to claim 1, which is characterized in that receiving pest image
Later, image boundary detection is carried out to know to brightness change visibility point in the pest image to the pest image
It does not identify, includes before obtaining boundary marking：
Image reinforcement processing is carried out to the pest image using frequency algorithm.
3. a kind of method for counting agricultural pests quantity according to claim 1, which is characterized in that according to the segmented image
Obtaining binary image is specially：
S1 carries out gray processing operation to the segmented image, obtains gray level image；
S2 calculates the average gray Y0 of the gray level image；
S3, setting Y1 are the average gray of the pixel less than or equal to Y0, and setting Y2 is the average gray of the pixel greater than Y0；
S4 calculates iteration threshold Y；Wherein Y=(Y1+Y2)/2；
S5 compares Y and Y0, if equal, exports Y as binarization threshold；Otherwise average gray Y0 is updated to Y, and returned
Return step S3；
S6 carries out binary conversion treatment to the gray level image, obtains binary image according to the binarization threshold of output.
4. a kind of method for counting agricultural pests quantity according to claim 1, which is characterized in that second bonding pad
Domain is overlapped pest label, and the superposition pest number marked according to each second area, and calculating the pest image includes
Number of pest specifically includes：
According to the pixel value gradient transform characteristics of the gray level image, the superposition pest number of each second join domain is calculated, and
The superposition pest number is tagged to corresponding second join domain；
According to the superposition pest number that each second area marks, the number of pest that the pest image includes is calculated.
5. a kind of device for counting agricultural pests quantity, which is characterized in that described device includes：
Image receiver module, for receiving pest image；
Boundary recognition module, for carrying out image boundary detection to brightness change in the pest image to the pest image
Visibility point carries out identification marking, obtains boundary marking；
Image segmentation module, for carrying out region segmentation to the pest image according to the boundary marking to obtain segmentation figure
Picture；The segmented image includes at least one closed cut zone；
First join domain module, for obtaining binary image according to the segmented image；Wherein, the binary image packet
Include at least one first join domain generated according to the cut zone；
Second join domain module, for according to each first join domain elemental area and preset pest pixel faces
Product obtains the second join domain for corresponding to pest in the first join domain；
Number calculating section, for being overlapped pest label to second join domain, and according to each second bonding pad
The superposition pest number of field mark calculates the number of pest that the pest image includes.
6. a kind of equipment for counting agricultural pests quantity, which is characterized in that including：Controller, switching circuit, light trap, camera shooting
Head；The controller is connect with the switching circuit, the light trap, the camera；
The camera is sent to the controller for acquiring the image for the pest trapped and killed, and by described image；
The switching circuit is connect with the light trap；
The controller includes memory and processor, and the memory includes executable code, the executable code energy
It is enough to be executed by the processor, the method to realize the statistics agricultural pests quantity as described in claim 1-4.
7. a kind of statistics agricultural pests number of devices according to claim 6, which is characterized in that further include at least one ring
Border detection sensor；The environmental detection sensor is used to detect the environmental parameter of current environment, and the environmental parameter is sent out
Give controller；
It is described statistics agricultural pests quantity method, further include：
The environmental parameter sent by environmental detection sensor is received, and according to the environmental parameter, controls the switch of light trap.
8. a kind of statistics agricultural pests number of devices according to claim 6, which is characterized in that the environment measuring sensing
Device includes：Raindrop sensor, Temperature Humidity Sensor, illuminance sensor, wind speed measurement sensor；The wind speed measurement sensing
Device, the Raindrop sensor, the Temperature Humidity Sensor and the illuminance sensor are connect with the controller；
The air velocity transducer includes Hall sensor and vane sensor, and the Hall sensor and the vane sensor connect
It connects, for detecting ambient wind velocity data；
Then according to the environmental parameter, the switch of light trap is controlled, specially：
Judge whether the illuminance numerical value of the illuminance sensor detection is greater than 1LX, if so, entering trapping for day time
Lamp closed state；
If it is not, being then, then continue to judge whether the output level of the Raindrop sensor detection is low level the time in the evening；
If low level, it is judged as rainy, then closes light trap；
If high level, then continue to judge whether the wind speed numerical value of the air velocity transducer detection is greater than 5 grades；
If so, closing light trap；
If it is not, then continue to judge the Temperature Humidity Sensor detection temperature whether≤20 DEG C or humidity whether≤50%；
If so, closing light trap；
If it is not, then opening light trap.
9. a kind of statistics agricultural pests number of devices according to claim 6, which is characterized in that further include：With the control
The NB-IOT module of device processed connection, for by number of pest and environmental information by cloud service center be sent to user terminal or
Person is for receiving the light trap switch order that user terminal is sent by the cloud service center；
Power circuit, solar controller and solar panels；The power circuit is connect with solar controller, the solar energy
Controller is connect with solar panels；
For giving the power supply circuit of each power elements；The power supply circuit is connect with the controller；
For generating the clock circuit of periodically pulsing signal, the clock circuit is connect with the controller.
For removing the motor and pest collector of pest corpse, the motor is received with the switching circuit and the pest respectively
Storage connection；Pest collector described in the image pickup part face of the camera.
10. a kind of statistics agricultural pests quantity system, which is characterized in that including cloud service center, user terminal and such as right
It is required that statistics agricultural pests number of devices described in 6-9 any one；The statistics agricultural pests quantity device passes through cloud service
Center is communicated with the user terminal.
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