CN104677342A - Apple orchard yield measuring method - Google Patents
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- CN104677342A CN104677342A CN201510100595.2A CN201510100595A CN104677342A CN 104677342 A CN104677342 A CN 104677342A CN 201510100595 A CN201510100595 A CN 201510100595A CN 104677342 A CN104677342 A CN 104677342A
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Abstract
The invention relates to an apple orchard yield measuring method. The method comprises steps as follows: 1) an apple orchard yield measuring system is provided and located on a UAV (unmanned aerial vehicle) and comprises UAV driving equipment, an aviation camera, image recognition equipment and an ARM11 processor, wherein the aviation camera is used for shooting an apple orchard to acquire orchard images; the image recognition equipment is connected with the aviation camera to process the orchard images, recognize types of apples in the orchard images and recognize the sum of the apples in the orchard images on the basis of the types of apples; the ARM11 processor is connected with the UAV driving equipment to control the UAV driving equipment to drive the UAV to fly right above the apple orchard; 2) the system is used for measuring.
Description
Technical field
The present invention relates to agriculture and forestry product field of planting, particularly relate to a kind of apple orchard yield monitoring method.
Background technology
Apple is first of the large fruit (apple, grape, citrus and banana) in the world four, owing to having abundant nutritive value and low in calories and be well received by consumers.In order to cater to this demand of consumer to increase production extra earning, add that the area that apple is suitable for planting is extensive, orchard workers have a preference for this crop of plantation apple, but, if just use too many region to carry out apple cultivation without investigating in advance, cause apple production too much, drug on the market in market, the unsalable situation of apple will be formed, bring economic loss to orchard worker on the contrary.
In order to coordinate the relation between supply and demand between apple production and consumer demand, build the market atmosphere of consumer and orchard worker's doulbe-sides' victory, need to investigate to the apple production in apple orchard on the spot and assess, according to investigation and assessment result with like that the number of consumer determines the cultivated area of the apple in lower season.Apple orchard of the prior art yield monitoring system or too dependence are artificial, consume a large amount of human cost and the time cost of survey institute, or the apple orchard yield monitoring of the local area based on image procossing is carried out at scene in apple orchard, this metering system on the one hand cannot according to apple kind adjustment measurement parameter, image processing techniques is too simple simultaneously, measure limited area on the other hand, cannot from the apple production in the whole apple orchard of reflection.
Therefore, need a kind of apple orchard yield monitoring method, different Image Processing parameter can be used based on the difference of apple kind, the apple production in whole apple orchard can be measured flexibly, all sidedly, improve the accuracy of apple orchard yield monitoring.
Summary of the invention
In order to solve the problem, the invention provides a kind of apple orchard yield monitoring method, adopt unmanned plane as measuring table, flexibly, the apple production in each apple orchard is measured all sidedly, adopt the image processing techniques based on apple kind, improve the precision of apple orchard yield monitoring, introduce contrast strengthen, self-adaptation recursive filtering and wireless communication technology targetedly simultaneously, realize the efficient measurement of apple orchard output.
According to an aspect of the present invention, provide a kind of apple orchard yield monitoring method, the method comprises: 1) provide a kind of apple orchard yield monitoring system, described measuring system is positioned on unmanned plane, described measuring system comprises unmanned plane driving arrangement, aerial camera, image recognition apparatus and ARM 11 processor, described aerial camera is used for apple orchard shooting to obtain garden image, described image recognition apparatus is connected to carry out image procossing to described garden image with described aerial camera, identify the apple kind in described garden image, and based on the apple sum in garden image described in described apple category identification, described ARM 11 processor is connected to control described unmanned plane driving arrangement and drives described unmanned plane to arrive in by plane directly over apple orchard with described unmanned plane driving arrangement, 2) described system is used to measure.
More specifically, in the yield monitoring system of described apple orchard, also comprise: portable hard drive, for prestoring the benchmark image template of the apple of various species, the benchmark image template of each kind is for taking obtained pattern in advance to the benchmark individual plant apple of each kind, described portable hard drive has also prestored apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value, described apple tree upper limit gray threshold and described apple tree lower limit gray threshold are used for apple tree in image to be separated with image background, wireless telecommunications system, two-way wireless communication link is set up with the apple production research platform of far-end, for receiving the flight steering order that described apple production research platform sends, described flight steering order comprises object gps data corresponding to position directly over apple orchard and object shooting height, also for described apple kind is wirelessly sent to described apple production research platform, the Apple upper limit gray threshold corresponding with described apple kind returned with apple production research platform described in wireless receiving and Apple lower limit gray threshold, described apple upper limit gray threshold and described Apple lower limit gray threshold are used for the Apple of apple kind corresponding in image to be separated with image background, GPS positioning equipment, connects GPS navigation satellite, for receiving the real-time GPS data of unmanned plane position, pressure-altitude sensor, for according to the air pressure change near unmanned plane, detects the real-time barometer altitude of unmanned plane position, radio altitude sensor, comprise radio transmitter, radio receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described radio transmitter and described radio receiver, described radio transmitter launches radiowave earthward, described radio receiver receives the radiowave of ground return, described single-chip microcomputer calculates the real-time radio electrical height of unmanned plane according to the launch time of described radio transmitter, the time of reception of described radio receiver and velocity of radio wave, and described velocity of radio wave is the light velocity, described aerial camera is linear array digital aviation video camera, comprises undercarriage having shock absorption function, front cover glass, camera lens, filter and image-forming electron unit, for taking apple orchard to obtain garden image, described image recognition apparatus is connected respectively with described aerial camera and described portable hard drive, comprise contrast strengthen unit, self-adaptation recursive filtering unit, gray processing processing unit, apple tree recognition unit and Apple recognition unit, described contrast strengthen unit, described self-adaptation recursive filtering unit, described gray processing processing unit, described apple tree recognition unit and described Apple recognition unit adopt different fpga chips to realize respectively, described contrast strengthen unit is connected to carry out contrast enhancement processing to described garden image with described aerial camera, image is strengthened to obtain, described self-adaptation recursive filtering unit is connected to carry out the process of self-adaptation recursive filtering to described enhancing image with described contrast strengthen unit, to obtain filtering image, described gray processing processing unit is connected with described self-adaptation recursive filtering unit, gray processing process is carried out to described filtering image, to obtain gray level image, described apple tree recognition unit is connected respectively with described gray processing processing unit and described portable hard drive, the pixel identification of gray-scale value in described gray level image between described apple tree upper limit gray threshold and described apple tree lower limit gray threshold is formed multiple apple tree subimage, and select an apple tree subimage, the benchmark image template of the apple tree subimage of selection with the apple of various species in described portable hard drive is mated, kind corresponding to the benchmark image template that output matching degree is the highest exports as the apple kind in described garden image, described Apple recognition unit is connected respectively with described gray processing processing unit and described portable hard drive, the pixel identification of gray-scale value in described gray level image between described Apple upper limit gray threshold and described Apple lower limit gray threshold is formed multiple Apple subimage, and the quantity of multiple Apple subimage is exported as the apple sum in described garden image, described ARM 11 processor and described unmanned plane driving arrangement, described wireless telecommunications system, described GPS positioning equipment, described pressure-altitude sensor, described radio altitude sensor, described portable hard drive, described aerial camera is connected respectively with described image recognition apparatus, based on real-time barometer altitude, real-time radio electrical height, barometer altitude weighted value and radio altitude weighted value calculate the real-time height of aircraft, receive the flight steering order that described wireless telecommunications system forwards, described flight steering order is resolved to obtain object gps data corresponding to position directly over apple orchard and object shooting height, control described unmanned plane driving arrangement to fly to position directly over described apple orchard to drive described unmanned plane, when described aircraft highly mates with described object shooting height in real time and described real-time GPS data is mated with described object gps data, enter apple orchard yield monitoring pattern, when described aircraft does not highly mate with described object shooting height in real time or described real-time GPS data is not mated with described object gps data, enter apple orchard searching modes, wherein, described ARM 11 processor is in the yield monitoring pattern of apple orchard, start described aerial camera and described image recognition apparatus, the apple kind that apple tree recognition unit in described image recognition apparatus exports is transmitted to described wireless telecommunications system, the Apple upper limit gray threshold corresponding with described apple kind and Apple lower limit gray threshold is returned to obtain described wireless telecommunications system, and the Apple upper limit gray threshold corresponding with described apple kind and Apple lower limit gray threshold are stored in described portable hard drive, described ARM 11 processor also receives the apple sum in described garden image subsequently, apple sum in described garden image is transmitted to described apple production research platform by described wireless telecommunications system, wherein, described ARM 11 processor connects described Apple recognition unit, with after Apple upper limit gray threshold corresponding for described apple kind and Apple lower limit gray threshold are stored into described portable hard drive, trigger the operation of described Apple recognition unit.
More specifically, in the yield monitoring system of described apple orchard, also comprise: serial communication interface, for connecting external unit by serial communication mode, to read the benchmark image template of the apple of the various species stored in external unit, apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value.
More specifically, in the yield monitoring system of described apple orchard: described serial communication interface is connected with described portable hard drive, be stored in described portable hard drive with the benchmark image template of the apple by various species, apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value.
More specifically, in the yield monitoring system of described apple orchard: the apple production research platform of described wireless telecommunications system wireless connections belonging to apple production research institution, the server with wireless communication interface.
More specifically, in the yield monitoring system of described apple orchard: described ARM 11 processor, in the searching modes of described apple orchard, cuts out described aerial camera and described image recognition apparatus.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present invention are described, wherein:
Fig. 1 is the block diagram of the apple orchard yield monitoring system illustrated according to an embodiment of the present invention.
Embodiment
Below with reference to accompanying drawings the embodiment of apple orchard of the present invention yield monitoring system is described in detail.
Apple belongs to the rose family, deciduous tree, and elliptic leaf shape, has sawtooth; Fruit is spherical, and taste is sweet, and mouthfeel is sharp and clear, and being common fruit, is also modal fruit, is rich in abundant nutrition.Apple is generally red, but also has yellow and green.
Apple is dicotyledon, and spend light red or lilac red, self-sterility mostly, needs cross-pollination, and fruit is grown by ovary and holder and formed.Pulp is clear and melodious fragrant and sweet, can help digest.Apple is kind of a food low in calories, and every 100 grams only produce 60 kilocalories of heats; Apple Middle nutrition composition solubility is large, is easily absorbed by the body, therefore has the title of " running water ".Be conducive to dissolving element sulphur, make skin lubrication tender.Also have the element such as copper, iodine, manganese, zinc, potassium in apple, human body as lacked these elements, skin will dry, easily split, very itch.It is applied in black-eyed place, can to help elimination livid ring around eye.
Extensively like by consumer just because of apple, orchard workers are ready to plant more apple, if but without the apple production investigation before plantation, often cause imbalance between supply and demand, this does not meet the economic interests of orchard worker and consumer.Therefore, the measurement of apple production is quite important.
Identification to apple production of the prior art is except the manual measurement mode of original backwardness, most employing image recognition technology, one strain or number strain apple are taken pictures, identify the citrusfruit number in the Apple image obtained or Apple area occupied, the output of a strain or number strain apple is determined based on Apple number or Apple area occupied, this mode measures limited area, measure inefficiency, and due to apple huge number, do not adopt different image recognition parameters that the apple production deviation of measurement can be caused larger based on apple kind, in addition, original image processing techniques is too simple, there is no specific aim.
The present invention has built a kind of apple orchard yield monitoring system, the Quick Measurement of whole apple orchard apple production is realized by unmanned aerial vehicle platform flexibly, and take differentiated recognition technology based on dissimilar apple, the introducing of unmanned plane elevation weight account form and various image processing techniques targetedly, accurately reliably completes the estimation of apple production simultaneously.
Fig. 1 is the block diagram of the apple orchard yield monitoring system illustrated according to an embodiment of the present invention, described measuring system comprises unmanned plane driving arrangement 1, wireless telecommunications system 2, GPS positioning equipment 3, pressure-altitude sensor 4, radio altitude sensor 8, portable hard drive 5, aerial camera 6, image recognition apparatus 7 and ARM 11 processor 9, described ARM 11 processor 9 respectively with described unmanned plane driving arrangement 1, described wireless telecommunications system 2, described GPS positioning equipment 3, described pressure-altitude sensor 4, described radio altitude sensor 8, described portable hard drive 5, described aerial camera 6, described image recognition apparatus connects 7 respectively, described image recognition apparatus 7 is connected with described aerial camera 6.
Wherein, described aerial camera 6 is for taking apple orchard to obtain garden image, described image recognition apparatus 7 is for carrying out image procossing to described garden image, identify the apple kind in described garden image, and based on the apple sum in garden image described in described apple category identification, described ARM 11 processor 9 drives described unmanned plane to arrive in by plane directly over apple orchard to trigger apple orchard yield monitoring operation for controlling described unmanned plane driving arrangement 1.
Then, continue to be further detailed the concrete structure of apple orchard of the present invention yield monitoring system.
Described portable hard drive 5 is for prestoring the benchmark image template of the apple of various species, the benchmark image template of each kind is for taking obtained pattern in advance to the benchmark individual plant apple of each kind, described portable hard drive 5 has also prestored apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value, and described apple tree upper limit gray threshold and described apple tree lower limit gray threshold are used for apple tree in image to be separated with image background.
Described wireless telecommunications system 2 sets up two-way wireless communication link with the apple production research platform of far-end, for receiving the flight steering order that described apple production research platform sends, described flight steering order comprises object gps data corresponding to position directly over apple orchard and object shooting height, also for described apple kind is wirelessly sent to described apple production research platform, the Apple upper limit gray threshold corresponding with described apple kind returned with apple production research platform described in wireless receiving and Apple lower limit gray threshold, described apple upper limit gray threshold and described Apple lower limit gray threshold are used for the Apple of apple kind corresponding in image to be separated with image background.
Described GPS positioning equipment 3 connects GPS navigation satellite, for receiving the real-time GPS data of unmanned plane position.
Described pressure-altitude sensor 4, for according to the air pressure change near unmanned plane, detects the real-time barometer altitude of unmanned plane position.
Described radio altitude sensor 8 comprises radio transmitter, radio receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described radio transmitter and described radio receiver, described radio transmitter launches radiowave earthward, described radio receiver receives the radiowave of ground return, described single-chip microcomputer calculates the real-time radio electrical height of unmanned plane according to the launch time of described radio transmitter, the time of reception of described radio receiver and velocity of radio wave, and described velocity of radio wave is the light velocity.
Described aerial camera 6 is linear array digital aviation video camera, comprises undercarriage having shock absorption function, front cover glass, camera lens, filter and image-forming electron unit, for taking apple orchard to obtain garden image.
Described image recognition apparatus 7 is connected respectively with described aerial camera 6 and described portable hard drive 5, described image recognition apparatus 7 comprises contrast strengthen unit, self-adaptation recursive filtering unit, gray processing processing unit, apple tree recognition unit and Apple recognition unit, and described contrast strengthen unit, described self-adaptation recursive filtering unit, described gray processing processing unit, described apple tree recognition unit and described Apple recognition unit adopt different fpga chips to realize respectively.
Described contrast strengthen unit is connected to carry out contrast enhancement processing to described garden image with described aerial camera 6, image is strengthened to obtain, described self-adaptation recursive filtering unit is connected to carry out the process of self-adaptation recursive filtering to described enhancing image with described contrast strengthen unit, to obtain filtering image, described gray processing processing unit is connected with described self-adaptation recursive filtering unit, gray processing process is carried out to described filtering image, to obtain gray level image.
Described apple tree recognition unit is connected respectively with described gray processing processing unit and described portable hard drive 5, the pixel identification of gray-scale value in described gray level image between described apple tree upper limit gray threshold and described apple tree lower limit gray threshold is formed multiple apple tree subimage, and select an apple tree subimage, the benchmark image template of the apple tree subimage of selection with the apple of various species in described portable hard drive mated, kind corresponding to the benchmark image template that output matching degree is the highest exports as the apple kind in described garden image.
Described Apple recognition unit is connected respectively with described gray processing processing unit and described portable hard drive 5, the pixel identification of gray-scale value in described gray level image between described Apple upper limit gray threshold and described Apple lower limit gray threshold is formed multiple Apple subimage, and the quantity of multiple Apple subimage exported as the apple sum in described garden image.
Described ARM 11 processor 9 is based on real-time barometer altitude, real-time radio electrical height, barometer altitude weighted value and radio altitude weighted value calculate the real-time height of aircraft, receive the flight steering order that described wireless telecommunications system 2 forwards, described flight steering order is resolved to obtain object gps data corresponding to position directly over apple orchard and object shooting height, control described unmanned plane driving arrangement 1 to fly to position directly over described apple orchard to drive described unmanned plane, when described aircraft highly mates with described object shooting height in real time and described real-time GPS data is mated with described object gps data, enter apple orchard yield monitoring pattern, when described aircraft does not highly mate with described object shooting height in real time or described real-time GPS data is not mated with described object gps data, enter apple orchard searching modes.
Wherein, described ARM 11 processor 9 is in the yield monitoring pattern of apple orchard, start described aerial camera 6 and described image recognition apparatus 7, the apple kind that apple tree recognition unit in described image recognition apparatus 6 exports is transmitted to described wireless telecommunications system 2, the Apple upper limit gray threshold corresponding with described apple kind and Apple lower limit gray threshold is returned to obtain described wireless telecommunications system 2, and the Apple upper limit gray threshold corresponding with described apple kind and Apple lower limit gray threshold are stored in described portable hard drive 5, described ARM 11 processor 9 also receives the apple sum in described garden image subsequently, apple sum in described garden image is transmitted to described apple production research platform by described wireless telecommunications system 2.
Wherein, described ARM 11 processor 9 connects described Apple recognition unit, with after Apple upper limit gray threshold corresponding for described apple kind and Apple lower limit gray threshold are stored into described portable hard drive 5, trigger the operation of described Apple recognition unit.
Wherein, described measuring system can also comprise: serial communication interface, for connecting external unit by serial communication mode, to read the benchmark image template of the apple of the various species stored in external unit, apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value; Described serial communication interface is connected with described portable hard drive 5, is stored in described portable hard drive 5 with the benchmark image template of the apple by various species, apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value; The apple production research platform of described wireless telecommunications system 2 wireless connections belonging to apple production research institution, the server with wireless communication interface; Described ARM 11 processor 9, in the searching modes of described apple orchard, can cut out described aerial camera 6 and described image recognition apparatus 7.
In addition, FPGA (Field-Programmable Gate Array), i.e. field programmable gate array, he is the product further developed on the basis of the programming devices such as PAL, GAL, CPLD, occur as a kind of semi-custom circuit in special IC (ASIC) field, he solves the deficiency of custom circuit, also overcomes the shortcoming that original programming device gate circuit number is limited.
As far back as 1980 mid-nineties 90s, FPGA takes root in PLD equipment.CPLD and FPGA includes the Programmadle logic unit of some relatively large amount.The density of CPLD logic gate is between several thousand to several ten thousand logical blocks, and FPGA normally arrives millions of several ten thousand.The key distinction of CPLD and FPGA is their system architecture.CPLD is a somewhat restrictive structure.This structure is arranged by the logical groups of one or more editable result sum and forms with the register of the locking of some relatively small amounts.Such result lacks editor's dirigibility, but but have the time delay and logical block that can estimate to the advantage of linkage unit height ratio.And FPGA has a lot of linkage units, although allow him edit more flexibly like this, structure is complicated many.The difference of CPLD and FPGA another one is that most FPGA contains high-level built-in module (such as totalizer and multiplier) and built-in memory body.Therefore relevant important difference be much new FPGA support completely or part system in reconfigure.Allow their design along with system upgrade or dynamically reconfigure and change.Some FPGA can allow a part for equipment update and other parts continue normal operation.
FPGA have employed logical cell array LCA (Logic Cell Array) such concept, and inside comprises configurable logic blocks CLB (Configurable Logic Block), input/output module IOB (Input Output Block) and interconnector (Interconnect) three parts.
Field programmable gate array (FPGA) is programming device, and as compared to conventional logic circuit and gate array (as PAL, GAL and CPLD device), FPGA has different structures.FPGA utilizes small-sized look-up table (16 × 1RAM) to realize combinational logic, each look-up table is connected to the input end of a d type flip flop, trigger drives other logical circuits again or drives I/O, thus constitute the basic logic unit module that not only can realize combination logic function but also can realize sequential logic function, these intermodules utilize metal connecting line to be connected to each other or are connected to I/O module.
Adopt apple orchard of the present invention yield monitoring system, excessive for the existing estimation error brought owing to ignoring species differences based on the apple orchard yield monitoring system of image recognition technology, measured zone is limited, image processing mode is too simple, there is no technical matters targetedly, by adopting unmanned aerial vehicle platform flexibly, the image recognition technology that variety classes apple estimation parameter is different, introduce weight calculation mode and Geng Duo image procossing mode targetedly simultaneously, the accuracy of effective raising apple orchard yield monitoring system and real-time, widen the measurement area of apple orchard output.
Be understandable that, although the present invention with preferred embodiment disclose as above, but above-described embodiment and be not used to limit the present invention.For any those of ordinary skill in the art, do not departing under technical solution of the present invention ambit, the technology contents of above-mentioned announcement all can be utilized to make many possible variations and modification to technical solution of the present invention, or be revised as the Equivalent embodiments of equivalent variations.Therefore, every content not departing from technical solution of the present invention, according to technical spirit of the present invention to any simple modification made for any of the above embodiments, equivalent variations and modification, all still belongs in the scope of technical solution of the present invention protection.
Claims (6)
1. an apple orchard yield monitoring method, the method comprises:
1) a kind of apple orchard yield monitoring system is provided, described measuring system is positioned on unmanned plane, described measuring system comprises unmanned plane driving arrangement, aerial camera, image recognition apparatus and ARM 11 processor, described aerial camera is used for apple orchard shooting to obtain garden image, described image recognition apparatus is connected to carry out image procossing to described garden image with described aerial camera, identify the apple kind in described garden image, and based on the apple sum in garden image described in described apple category identification, described ARM 11 processor is connected to control described unmanned plane driving arrangement and drives described unmanned plane to arrive in by plane directly over apple orchard with described unmanned plane driving arrangement,
2) described system is used to measure.
2. the method for claim 1, is characterized in that, described measuring system also comprises:
Portable hard drive, for prestoring the benchmark image template of the apple of various species, the benchmark image template of each kind is for taking obtained pattern in advance to the benchmark individual plant apple of each kind, described portable hard drive has also prestored apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value, and described apple tree upper limit gray threshold and described apple tree lower limit gray threshold are used for apple tree in image to be separated with image background;
Wireless telecommunications system, two-way wireless communication link is set up with the apple production research platform of far-end, for receiving the flight steering order that described apple production research platform sends, described flight steering order comprises object gps data corresponding to position directly over apple orchard and object shooting height, also for described apple kind is wirelessly sent to described apple production research platform, the Apple upper limit gray threshold corresponding with described apple kind returned with apple production research platform described in wireless receiving and Apple lower limit gray threshold, described apple upper limit gray threshold and described Apple lower limit gray threshold are used for the Apple of apple kind corresponding in image to be separated with image background,
GPS positioning equipment, connects GPS navigation satellite, for receiving the real-time GPS data of unmanned plane position;
Pressure-altitude sensor, for according to the air pressure change near unmanned plane, detects the real-time barometer altitude of unmanned plane position;
Radio altitude sensor, comprise radio transmitter, radio receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described radio transmitter and described radio receiver, described radio transmitter launches radiowave earthward, described radio receiver receives the radiowave of ground return, described single-chip microcomputer calculates the real-time radio electrical height of unmanned plane according to the launch time of described radio transmitter, the time of reception of described radio receiver and velocity of radio wave, and described velocity of radio wave is the light velocity;
Described aerial camera is linear array digital aviation video camera, comprises undercarriage having shock absorption function, front cover glass, camera lens, filter and image-forming electron unit, for taking apple orchard to obtain garden image;
Described image recognition apparatus is connected respectively with described aerial camera and described portable hard drive, comprise contrast strengthen unit, self-adaptation recursive filtering unit, gray processing processing unit, apple tree recognition unit and Apple recognition unit, described contrast strengthen unit, described self-adaptation recursive filtering unit, described gray processing processing unit, described apple tree recognition unit and described Apple recognition unit adopt different fpga chips to realize respectively, described contrast strengthen unit is connected to carry out contrast enhancement processing to described garden image with described aerial camera, image is strengthened to obtain, described self-adaptation recursive filtering unit is connected to carry out the process of self-adaptation recursive filtering to described enhancing image with described contrast strengthen unit, to obtain filtering image, described gray processing processing unit is connected with described self-adaptation recursive filtering unit, gray processing process is carried out to described filtering image, to obtain gray level image, described apple tree recognition unit is connected respectively with described gray processing processing unit and described portable hard drive, the pixel identification of gray-scale value in described gray level image between described apple tree upper limit gray threshold and described apple tree lower limit gray threshold is formed multiple apple tree subimage, and select an apple tree subimage, the benchmark image template of the apple tree subimage of selection with the apple of various species in described portable hard drive is mated, kind corresponding to the benchmark image template that output matching degree is the highest exports as the apple kind in described garden image, described Apple recognition unit is connected respectively with described gray processing processing unit and described portable hard drive, the pixel identification of gray-scale value in described gray level image between described Apple upper limit gray threshold and described Apple lower limit gray threshold is formed multiple Apple subimage, and the quantity of multiple Apple subimage is exported as the apple sum in described garden image,
Described ARM 11 processor and described unmanned plane driving arrangement, described wireless telecommunications system, described GPS positioning equipment, described pressure-altitude sensor, described radio altitude sensor, described portable hard drive, described aerial camera is connected respectively with described image recognition apparatus, based on real-time barometer altitude, real-time radio electrical height, barometer altitude weighted value and radio altitude weighted value calculate the real-time height of aircraft, receive the flight steering order that described wireless telecommunications system forwards, described flight steering order is resolved to obtain object gps data corresponding to position directly over apple orchard and object shooting height, control described unmanned plane driving arrangement to fly to position directly over described apple orchard to drive described unmanned plane, when described aircraft highly mates with described object shooting height in real time and described real-time GPS data is mated with described object gps data, enter apple orchard yield monitoring pattern, when described aircraft does not highly mate with described object shooting height in real time or described real-time GPS data is not mated with described object gps data, enter apple orchard searching modes,
Wherein, described ARM 11 processor is in the yield monitoring pattern of apple orchard, start described aerial camera and described image recognition apparatus, the apple kind that apple tree recognition unit in described image recognition apparatus exports is transmitted to described wireless telecommunications system, the Apple upper limit gray threshold corresponding with described apple kind and Apple lower limit gray threshold is returned to obtain described wireless telecommunications system, and the Apple upper limit gray threshold corresponding with described apple kind and Apple lower limit gray threshold are stored in described portable hard drive, described ARM 11 processor also receives the apple sum in described garden image subsequently, apple sum in described garden image is transmitted to described apple production research platform by described wireless telecommunications system,
Wherein, described ARM 11 processor connects described Apple recognition unit, with after Apple upper limit gray threshold corresponding for described apple kind and Apple lower limit gray threshold are stored into described portable hard drive, trigger the operation of described Apple recognition unit.
3. method as claimed in claim 2, it is characterized in that, described estimating system also comprises:
Serial communication interface, for connecting external unit by serial communication mode, to read the benchmark image template of the apple of the various species stored in external unit, apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value.
4. method as claimed in claim 3, is characterized in that:
Described serial communication interface is connected with described portable hard drive, is stored in described portable hard drive with the benchmark image template of the apple by various species, apple tree upper limit gray threshold, apple tree lower limit gray threshold, barometer altitude weighted value and radio altitude weighted value.
5. method as claimed in claim 2, is characterized in that:
The apple production research platform of described wireless telecommunications system wireless connections belonging to apple production research institution, the server with wireless communication interface.
6. method as claimed in claim 2, is characterized in that:
Described ARM 11 processor, in the searching modes of described apple orchard, cuts out described aerial camera and described image recognition apparatus.
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Cited By (3)
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CN107450595A (en) * | 2017-09-19 | 2017-12-08 | 广东容祺智能科技有限公司 | A kind of system of gathering medicinal herbs based on unmanned plane |
CN108564583A (en) * | 2018-04-23 | 2018-09-21 | 广州林邦信息科技有限公司 | Sample ground monitoring method, apparatus and system |
CN108801350A (en) * | 2018-06-22 | 2018-11-13 | 江苏省农业科学院 | A kind of fruit tree growth monitoring system based on unmanned plane Technology of low altitude remote sensing |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070050116A1 (en) * | 2005-07-22 | 2007-03-01 | Jernigan William B | Yield monitor |
CN103090946A (en) * | 2013-01-15 | 2013-05-08 | 北京农业信息技术研究中心 | Method and system for measuring single fruit tree yield |
CN104200193A (en) * | 2014-08-05 | 2014-12-10 | 北京农业信息技术研究中心 | Fruit tree yield estimation method and device |
CN104296850A (en) * | 2014-10-31 | 2015-01-21 | 中国农业科学院农业信息研究所 | Device and method for automatically recording accurate yield of fruit trees |
CN104330410A (en) * | 2014-11-04 | 2015-02-04 | 无锡北斗星通信息科技有限公司 | Crop pest detection system positioned on unmanned aerial vehicle |
-
2015
- 2015-03-08 CN CN201510100595.2A patent/CN104677342A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070050116A1 (en) * | 2005-07-22 | 2007-03-01 | Jernigan William B | Yield monitor |
CN103090946A (en) * | 2013-01-15 | 2013-05-08 | 北京农业信息技术研究中心 | Method and system for measuring single fruit tree yield |
CN104200193A (en) * | 2014-08-05 | 2014-12-10 | 北京农业信息技术研究中心 | Fruit tree yield estimation method and device |
CN104296850A (en) * | 2014-10-31 | 2015-01-21 | 中国农业科学院农业信息研究所 | Device and method for automatically recording accurate yield of fruit trees |
CN104330410A (en) * | 2014-11-04 | 2015-02-04 | 无锡北斗星通信息科技有限公司 | Crop pest detection system positioned on unmanned aerial vehicle |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107450595A (en) * | 2017-09-19 | 2017-12-08 | 广东容祺智能科技有限公司 | A kind of system of gathering medicinal herbs based on unmanned plane |
CN108564583A (en) * | 2018-04-23 | 2018-09-21 | 广州林邦信息科技有限公司 | Sample ground monitoring method, apparatus and system |
CN108801350A (en) * | 2018-06-22 | 2018-11-13 | 江苏省农业科学院 | A kind of fruit tree growth monitoring system based on unmanned plane Technology of low altitude remote sensing |
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