CN110348302A - A kind of image identification system and pattern recognition device - Google Patents
A kind of image identification system and pattern recognition device Download PDFInfo
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- CN110348302A CN110348302A CN201910488368.XA CN201910488368A CN110348302A CN 110348302 A CN110348302 A CN 110348302A CN 201910488368 A CN201910488368 A CN 201910488368A CN 110348302 A CN110348302 A CN 110348302A
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- G06V10/00—Arrangements for image or video recognition or understanding
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Abstract
The embodiment of the invention provides a kind of image identification system and pattern recognition devices, including acquisition module is for acquiring image；Identification module object features in described image for identification；Analysis module is used to generate analysis data using the object features in described image；Memory module records the object features that the identification module obtains and the analysis data that the analysis module obtains for storing described image.Image identification system proposed by the present invention, structure is simple, easy to operate, recognition capability is strong, it can acquire and object is quickly identified according to image after image, improve the accuracy of image recognition, while object features can be obtained according to object, analysis data are generated using object features, increase the practicability of image recognition, and whole image identifying system is low in cost, can monitor identification in real time, the cost of image recognition is also reduced, planting cost is reduced.
Description
Technical field
The present invention relates to technical field of image detection, fill more particularly to a kind of image identification system and image recognition
It sets.
Background technique
Planting industry is one of the important component of China's agricultural, and planting industry includes various crops, forest, fruit tree, medicine
Cultivations of plants are waited with ornamental.
Wherein in field of fruit tree cultivation, since planting fruit trees range is big, planting fruit trees quantity is more, in order to improve plantation
Yield needs farmer's moment to observe the growing state of fruit tree and the situation of periphery growing environment.
Currently used method for managing and monitoring is using labor management and picture control management, and wherein labor management is by drawing
The personnel that are engaged in agriculture of certain number are engaged in subregion, each region, are responsible for the plantation of the region fruit tree by the personnel of being engaged in agriculture, and grow, and receive
At etc..And engage and be engaged in agriculture that personal management is at high cost, and worker workload is big, farmer is managed collectively difficult.Another image prison
Keyholed back plate reason, can only carry out security context monitoring management, can not monitor fruit tree growth, can not also be managed collectively to farmer, and
And the ability of picture control management identification fruit tree is poor, the efficiency of management is low, increases the management cost of farmer.
Summary of the invention
In view of the above problems, it proposes the embodiment of the present invention and overcomes the above problem or at least partly in order to provide one kind
A kind of image identification system to solve the above problems.
To solve the above-mentioned problems, may include with lower module the embodiment of the invention discloses a kind of image identification system:
Acquisition module, for acquiring image；
Identification module, for identification object features in described image；
Analysis module, for generating analysis data using the object features in described image；
Memory module records object features and the analysis mould that the identification module obtains for storing described image
The analysis data that block obtains.
Optionally, further includes:
Rotating module, for carrying the acquisition module, and it is mobile to control the acquisition module 0-360 degree；
The rotating module includes: rotating base, is fixed on the runner assembly of the rotating base, and with the rotation
The connected rotation axis of component, the rotation axis are equipped with fixing piece, and the rotation axis passes through the fixing piece and the acquisition module
It is connected.
Optionally, the object features include species characteristic, qualitative characteristics, and the identification module includes:
Category identification module, for identification species characteristic in described image；
Quality identification module, for identifying qualitative characteristics using the species characteristic.
Optionally, the category identification module includes:
Fruit types identification module, for identification the Fruit types feature in described image；
Floristics identification module, for identification the floristics feature in described image；
Caste identification module, for identification the caste feature in described image.
Optionally, the quality identification module includes:
Fruit quality identification module, for identifying the fruit image in described image using the Fruit types feature, and
Generate fruit quality feature；
Plant quality identification module, for using the plant image in floristics feature identification described image, life
At plant quality feature；
Insect quality identification module, for using the insect image identification in caste feature identification described image, life
At insect qualitative characteristics.
Optionally, the object features further include quantative attribute, the identification module further include:
Fruit number identification module for using the fruit image statistics fruit number, and generates fruit number feature；
Number of plant identification module for counting number of plant using the plant image, and generates number of plant feature；
Insect numbers identification module for counting insect numbers using the insect image identification, and generates insect numbers feature.
Optionally, the analysis module includes:
Growth analysis module, for generating the growth analysis data of object using the object features, and by the growth
Analysis data are sent to the memory module；
Forecast analysis module for generating forecast analysis data using the growth analysis data, and the prediction is divided
Analysis data are sent to the memory module.
It optionally, further include cruise module；
The cruise module, for carrying the acquisition module, the identification module, the analysis module, the storage
Module and the mobile module.
Optionally, the cruise module includes moving assembly, is fixed on the mobile base of the moving assembly, the movement
Pedestal is equipped with control assembly and communication part, and the control assembly is connected with the communication part；
The acquisition module, the identification module, the analysis module, the memory module and the mobile module are fixed
In the mobile base, the control assembly respectively with the identification module, the analysis module, the memory module and described
Mobile module is connected.
The invention also provides a kind of pattern recognition devices, including above-mentioned image identification system, and and described image
The connected background apparatus of identifying system；
Described image identifying system identifies the object in image for acquiring image, and to the object in described image into
Row analysis；
The background apparatus, for managing control described image identifying system.
The embodiment of the present invention includes following advantages: image is acquired by acquisition module, sends an image to identification module, by
Identification module identifies the object features in image, and object features are sent to analysis module again by identification module, analysis module according to
Object features analyze object using object features, and generate analysis data, and analysis data are sent to by analysis module again
Memory module.The image identification system that the present embodiment proposes, structure is simple, and easy to operate, recognition capability is strong, can acquire
Object is quickly identified according to image after image, improves the accuracy of image recognition, while object features can be obtained according to object,
Analysis data are generated using object features, increase the practicability of image recognition, and whole image identifying system is low in cost, it can
To monitor identification in real time, the cost of image recognition is also reduced, planting cost is reduced.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of image identification system one of which embodiment of the invention；
Fig. 2 is the structural schematic diagram of image identification system one of which embodiment of the invention；
Fig. 3 is the structural schematic diagram of pattern recognition device one of which embodiment of the invention.
Specific embodiment
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
Referring to Fig.1, the structural schematic diagram of image identification system one of which embodiment of the invention of the invention is shown,
In the present embodiment, using fruit tree image recognition as example, it can also apply and be identified in plant image, agricultural product image recognition etc.
In the cultivation of other planting industry, for example, corn planting, soybean planting, banana planting etc., in the present embodiment, the image recognition
System can specifically include following module:
Acquisition module 101, for acquiring image；
In the present embodiment, acquisition module 101 can be terminal, can be monitoring camera, can be monitoring camera,
It can be scanning means, tablet computer, smartwatch etc., fruit tree image, such as the fruit tree of fruit tree, the tree of fruit tree can be acquired
Leaf, fruit tree or epiphyllous insect etc. can acquire fruit tree ambient enviroment image, and the soil image of fruit tree root works as previous existence
Long ambient image etc..Analysis management can be carried out to fruit tree according to each feature of image, such as farmer can be according to figure
As knowing the current growing state of fruit, to know the growing state of current fruit tree.
In the present embodiment, one or more can be set in acquisition module 101, can be adjusted according to actual needs
It is whole.
In the present embodiment, fruit tree can be monitored in real time using 101 one side of acquisition module, improves management effect
On the other hand rate can reduce artificial monitoring cost using acquisition module 101, and the cost of acquisition module 101 more manually at
This is low, can also reduce the cost of plantation.
Identification module 102, for identification object features in described image；
In the present embodiment, object features may include the color characteristic of object, shape feature, volume size characteristic, number
Measure feature, species characteristic, identification module 102 can identify the type of fruit on fruit tree, the color of fruit, the size of fruit,
It can identify that the color of plant on fruit tree, the type of plant can also identify that the type of insect on fruit tree, the size of insect are led to
It crosses identification object features and identifies the object.Object features can be specifically pre-stored on identification module 102 by user, be known
Other module 102 according to the object features in the object features identification image prestored, judge object features in image whether in advance
The object features deposited are identical, identical, and the object in image is to prestore the corresponding object of object features, the object features prestored
It may include the fruit image of each growth phase, after 101 collecting fruit image of acquisition module, fruit image can be sent to
Identification module 102, then identification module 102 compares received fruit image with the fruit image prestored, when received fruit
Fruit is identical as the fruit of the fruit image prestored in real image, i.e., the fruit in received fruit image is the fruit figure prestored
Fruit as in.The feature of fruit itself can also be pre-stored in identification module 102, by the fruit in received fruit image
Whether the feature of satisfaction prediction, meeting the fruit then in received fruit image is the fruit of pre-stored characteristics, such as prestores orange
Feature, color characteristic be it is orange, it is round, it is rough, when identification module 102 identifies received fruit image, the fruit
Object color in image be it is orange, round and rough, then identification module 102 identifies that the object is orange.It prestores
Features of fruits can be adjusted according to actual needs, such as identification banana, and the object features that can be prestored include color
Feature is yellow, and shape feature is half arc, and arrayed feature is that multiple bananas are stored side by side, when the object of received fruit image
Meet above-mentioned several features, then identification module 102 identifies that the object of the fruit image is banana.
In this embodiment, identification module 102 can also prestore the quantative attribute or volume size characteristic or fruit table of fruit
Face color distribution characteristics etc. can count the quantity of fruit, the volume size of fruit, fruit after identifying Fruit types
The distribution of color on surface.
In the same manner, in the present embodiment, leaf image can also be prestored in identification module 102, the judgement of identification module 102 is worked as
Leaf in preceding received leaf image, it is whether identical as the leaf in the leaf image that prestores, it then identifies if they are the same received
Leaf in leaf image is identical as the leaf in the leaf image prestored.Leaf spy can also be prestored in identification module 102
Sign, such as the shape of blade, the color of blade, lines of blade etc. leaf feature, the reception acquisition module 101 of identification module 102
The image of acquisition identifies the leaf in received image according to the leaf feature prestored, judges whether to meet the leaf spy prestored
Sign is judged as YES the leaf type prestored if meeting, if being unsatisfactory for being judged as type leaf to be judged, can wait sentencing with label
Disconnected type leaf, waits user to judge to identify again.In the present embodiment, it is special that multiple leaves can be stored in identification module 102
Sign or a variety of leaf features increase leaf feature, the recognition capability of identification module 102 can be improved.
Similarly, in the present embodiment, insect image identification or insect feature, identification module can also be prestored in identification module 102
The method of 102 identification insects, it is roughly the same with identification leaf and identification fruit, it can refer to above content analogy, herein not one by one
It is described in detail.
In the present embodiment, identification module 102 can quickly identify the objects such as type, quantity, shape, the color of object spy
Sign, increases the ability of image recognition, while can make a series of analysis operation according to object object features, also improves pipe
The efficiency of reason.
In the present embodiment, identification module 102 can also prestore the volume size characteristic of fruit, then use the body of fruit
Product size characteristic, identifies the growing state of current fruit, for example, the fruit on fruit tree is 3-4 lis long after apple tree planting 60 days
Rice, it is 2-3 centimetres wide, then prestore apple 60 days growth after volume size characteristic be it is 3-4 centimetres long, it is 2-3 centimetres wide, if identification mould
The volume size characteristic that block 102 identifies be it is 2-3 centimetres long, it is 1-2 centimetres wide, then can compare the volume size characteristic that prestores and know
Other volume size characteristic can identify current apple if the volume size characteristic of identification is unsatisfactory for the volume size characteristic prestored
Fruit is unsatisfactory for and the apple normal growth situation.In the present embodiment, identification module 102 can also identify quantative attribute, can be with
According to the quantative attribute of identification, identify that the ability of current fruit tree result is strong or weak, for example, the apple tree that identification module 102 identifies
On apple quantity, the average result quantity of apple tree can be stored in identification module 102 by user, and identification module 102 identifies
Apple quantity, identification module 102 compares the apple quantity of identification and the average result quantity of apple tree, if the apple number of identification
Amount is greater than the average result quantity of apple tree, then identifies that current fruit tree bearing capacity is strong, generation quantity feature, if the apple of identification
Quantity is less than the average result quantity of apple tree, then identifies that current fruit tree bearing capacity is weak, generation quantity feature.
In the present embodiment, identification module 102 can also identify the shape feature of leaf, according to the shape feature of leaf,
The growing state of current fruit tree is judged, for example, identification module 102 identifies after the leaf for identifying the fruit tree is apple leaf
It is all in image to identify that the leaf quantity for the shape feature for meeting leaf in image accounts for using the shape feature of leaf for module 102
The percentage of the quantity of leaf, if the leaf quantity for meeting the shape feature of leaf is more than the percentage of all leaf quantity in image
50, identification module 102 can identify current fruit tree normal growth, generation quantity feature, if meeting the shape feature of leaf
Leaf quantity be more than 20 percent of all leaf quantity in image, identification module 102 can identify that current fruit tree is abnormal
Growth, generation quantity feature.
In the present embodiment, the insect feature that identification module 102 can also identify, for example, identification module 102 identifies currently
The species characteristic of insect, user can store insect type in identification module 102, and insect is divided into pest and beneficial insect, identification
Module 102 also can connect network, voluntarily download insect type, the caste feature that identification module 102 identifies and acquisition
Pest feature compares, if the insect is pest, identification module 102 can identify that the fruit tree weathers, if the insect is beneficial insect,
Identification module 102 can identify the fruit tree normal growth.In the present embodiment, identification module 102 can also identify insect numbers
Feature judges the quantity of insect, if insect numbers are greater than preset value, can identify that current fruit tree weathers, if insect number
Amount is less than preset value, can identify that current fruit tree normal growth, preset value can be according to practical adjustment.In the present embodiment, know
The number of pest that can also do not identify accounts for the percentage of the quantity of the insect of the identification of identification module 102, for example, if identification module
The number of pest of 102 identifications accounts for 75 or more the percent of the quantity of the insect of the identification of identification module 102, identification module
102 can identify that the fruit tree weathers, if the number of pest that identification module 102 identifies accounts for the insect of the identification of identification module 102
Quantity 25 percent or hereinafter, identification can identify the fruit tree normal growth etc..
In the present embodiment, identification module 102 can identify that the quantity of object, type, the object features such as growth speed are used
Family can carry out next planting scheme according to object features or make the analysis that management operates in next step, improve the management of user
Ability can also effectively improve plantation yield.
Analysis module 103, for generating analysis data using the object features in described image；
In the present embodiment, the object features that analysis module 103 is obtained using identification module 102, according to object features point
The growing state of fruit tree is analysed, for example, leaf quantity accounting is more than default if the growth size of fruit meets the size of normal growth
It is worth, number of pest is less than preset value in insect, then analysis module 103 may determine that current fruit tree growth is normal.User can root
According to the judging result of analysis module 103, it is contemplated that the yield of fruit tree is prepared for the sales promotion of next step.If the growth of fruit
Size is unsatisfactory for the size of normal growth, and leaf quantity accounting is less than preset value, and number of pest is greater than preset value in insect, then divides
Analysis module 103 may determine that current fruit tree misgrowth, and user can be improved and treat in time to the fruit, avoid fruit tree
Abnormal conditions, which are spread, gives other fruit trees.
In the present embodiment, analysis module 103 can generate analysis data according to the object features in image, will analyze number
It according to memory module 104 is sent to, is stored by memory module 104, user or farmer can organize fruit tree according to analysis data
It carries out the planting scheme of next step or obtains the growing state of current fruit tree according to analysis data, facilitate user management.
Memory module 104 records object features that the identification module 102 obtains and described for storing described image
The analysis data that analysis module 103 obtains
In the present embodiment, memory module 104 can respectively with acquisition module 101, identification module 102, analysis module 103
It is connected, receives point of object features and analysis module 103 that image, the identification module 102 that acquisition module 101 acquires identify respectively
Data are analysed, in the present embodiment, acquisition module 101 can also be connected with identification module 102, and identification module 102 can be with analysis
Module 103 is connected, and acquisition module 101 can acquire image, and the image of acquisition can be sent to identification module 102, identifies mould
Block 102 can generate object features using acquisition image, object features and acquisition image can be sent to analysis module 103,
Analysis module 103 can generate analysis data using object features, by analysis data, object features and acquisition image and be sent to
Memory module 104.
In the present embodiment, the data user that memory module 104 stores can arbitrarily call, and user can be according to storage number
According to, do the planting scheme or governing plan of next step, while the more convenient management of user can be allowed using memory module 104, with
When can call data.
A kind of image identification system is proposed in the present embodiment, and image is acquired by acquisition module 101, will acquire image
It is sent to identification module 102, the object features in image are identified by identification module 102, identification module 102 again sends out object features
Analysis module 103 is given, analysis module 103 analyzes object using object features according to object features, and generates analysis
Analysis data are sent to memory module 104 again by data, analysis module 103.The image identification system that the present embodiment proposes, structure
Simply, easy to operate, recognition capability is strong, can acquire and quickly identify object according to image after image, improve image recognition
Accuracy, while can according to object obtain object features, using object features generate analysis data, increase image recognition
Practicability, and whole image identifying system is low in cost, can monitor identification in real time, also reduces the cost of image recognition,
Reduce planting cost.
It should be noted that for simple description, therefore, it is stated as a series of module groups for system embodiment
It closes, but those skilled in the art should understand that, the embodiment of the present invention is not limited by the described module order of connection, because
For according to an embodiment of the present invention, certain module can be connected with other modules.Secondly, those skilled in the art should also know that,
The embodiments described in the specification are all preferred embodiments, and the related movement not necessarily embodiment of the present invention must
Must.
Referring to Fig. 2, the structural schematic diagram of image identification system one of which embodiment of the invention is shown, in this implementation
Example in, using fruit tree image recognition as example, can also apply in the agricultural plantings industry such as agricultural planting field, can specifically include as
Lower module:
Acquisition module 201, for acquiring image；
In the present embodiment, acquisition module 201 can be tablet computer, mobile terminal, camera, video camera, monitoring camera,
The mobile terminal devices such as smartwatch.Terminal shooting, collecting image can be used, it, can also be by image transmitting to identification module
Modules are installed in terminal, modules are concentrated on into terminal, are integrally formed, simplify the structure of whole image identifying system；
A video camera can also be installed for example, in the planting range of 3 to 5 fruit trees by the multiple video cameras of installation in fruit, one
Video camera acquires the image of 3 to 5 fruit trees, can also specifically may be used in 5 to 10 planting ranges, installing a video camera
To be adjusted according to actual needs.
Use acquisition module 201 that can improve the efficiency of Image Acquisition with Quick Acquisition image, it can also be in acquisition module
Image storage module 204 is set in 201, and for storing the image of the acquisition of acquisition module 201, user can adjust in fruit in real time
The image acquired with acquisition module 201.
Identification module 202, for identification object features in described image；
In the present embodiment, object features may include species characteristic, qualitative characteristics, quantative attribute, shape feature, color
Feature, volume size characteristic, patterned feature etc., in the present embodiment, identification module 202 may include:
Category identification module 2021, for identification species characteristic in described image；
In the present embodiment, category identification module 2021 can identify that species characteristic, qualitative characteristics, quantity in image are special
Sign, shape feature, color characteristic, volume size characteristic, patterned feature etc..It identifies the species characteristic in image, can identify
The type of objects in images out can carry out Classification Management to object, can also identify the quantity of type in image, calculate the figure
The quantity of the object of a certain type, can also identify shape feature, judge whether the object belongs to a certain object according to shape as in
Body, such as identification object are half-circle-arc shape, can identify that the object is fruit, and it is round or oval for dragging identification body form
Shape can identify that the object is fruit, if identification body form is circular cone or taper, can identify that the object is leaf etc..
Category identification module 2021 can also identify color characteristic, judge what type the object in image is according to color, for example, kind
Class identification module 2021 identifies the red in image, if objects in images is red, can identify that the object is apple, if image
Middle object is green, can identify that the object is leaf etc..
In the present embodiment, the object of identification can be generated species characteristic, the type of generation by category identification module 2021
Feature can be converted to data and be transferred to the use of other modules.Category identification module 2021 can quickly identify objects in images
Objects in images can according to type be classified according to species characteristic, the efficiency of identification can be improved by species characteristic.
In the present embodiment, category identification module 2021 may include:
Fruit types identification module 20211, for identification the Fruit types feature in described image；
In the present embodiment, Fruit types identification module 20211 can pass through Fruit types feature in identification image, identification
The Fruit types out, Fruit types feature can be color, shape.For example, the object color in identification image is red or shallow
Red, Fruit types identification module 20211 identify that the object is fruit, identify that the object color in image is yellow, fruit kind
Class identification module 20211 identifies that the object is fruit etc., can with quicklook identify the Fruit types by color, due to
The color of fruit is different from most of leaf or the color of trunk in fruit tree, while identification effect can be improved in color identification
Rate.In the present embodiment, the color category of Fruit types identification module 20211 can be adjusted according to actual needs.
In the present embodiment, Fruit types identification module 20211 can also identify the body form in image, such as identify
Body form in image is round or oval, Fruit types identification module 20211 identify the object be fruit, such as apple,
It can also identify that the body form in image is circular arc or half-circle-arc shape, Fruit types identification module 20211 identifies the object
For fruit, such as banana.Since the shape of fruit also differs farther out with the shape of leaf or trunk in fruit tree, pass through shape
It can quickly identify fruit, improve recognition efficiency.In the present embodiment, the fruit kind that Fruit types identification module 20211 identifies
Category feature can be prestored by user, and Fruit types identification module 20211 is allowed to identify image according to Fruit types feature
In object.In the present embodiment, the shape type of Fruit types identification module 20211 can carry out according to actual needs
Adjustment.
Floristics identification module 20212, for identification the floristics feature in described image；
In the present embodiment, floristics identification module 20212 can be known by the floristics feature in identification image
Not Chu plant in image, floristics feature also may include color, shape.Such as floristics identification module 20212 is known
Object color in other image is green or bottle green, and floristics identification module 20212 identifies that the object is plant.Due to planting
Object and the colouring discrimination technical characteristic of fruit or insect are larger, and plant can also be quickly recognized by color, improve identification effect
Rate.
In the present embodiment, floristics identification module 20212 can also identify the body form in image, such as identify
Body form in image is round or oval, and floristics identification module 20212 identifies that the object is plant, or identification
Body form in image is fan-shaped or bajiao banana shape, and floristics identification module 20212 can also identify that the object is plant.It plants
Whether the shape of object is more, according to according to actual needs, adjust shape, be plant in the object for judging image according to shape.
In the present embodiment, the floristics feature such as plant shape or color of floristics identification module 20212 can pass through user
It prestores, is that floristics identification module 20212 quickly identifies the body form.
Caste identification module 20213, for identification the caste feature in described image；
In the present embodiment, caste identification module 20213 can be known by the caste feature in identification image
Not Chu insect in image, caste feature may include that color, shape, such as caste identification module 20213 identify
There are many colors to adulterate for object color in image, and caste identification module 20213 identifies that the object in the image is insect,
Since the color of insect is varied, fruit is opposite with the color of plant single, if the object in image includes multiple color, elder brother
Worm category identification module 20213 can identify that the object in the image is insect.
In the present embodiment, caste identification module 20213 can also identify the shape of objects in images, for example, knowing
Body form in other image be it is irregular, object in the image of caste identification module 20213 is insect, due to insect
It is a kind of biology, there is no fixed shapes, can if caste identification module 20213 identifies the in irregular shape of the object
To identify the object as insect, while when acquiring image, insect is possible to stationary, it is also possible to and it is dynamic motion, when
Insect motion becomes the shape of insect irregularly when acquiring image, can when identifying that the body form in image is irregular
Change object in image as insect to identify.
Quality identification module 2022, for identifying qualitative characteristics using the species characteristic.
In the present embodiment, quality identification module 2022 can identify the qualitative characteristics of object, quality identification module 2022
Can whether complete using species characteristic identification fruit shapes, for example, quality identification module 2022 uses category identification module
2021 identification fruits, identify whether the shape of the fruit is complete, if the shape of the fruit is jagged or shape collapses scarce, quality knowledge
Other module 2022, which can be, identifies that the fruit quality is failed, and quality identification module 2022 generates qualitative characteristics of failing, if shape
Shape is complete, no notch or collapses scarce, and quality identification module 2022 can identify that the fruit quality is passed, and it is special to generate qualifying quality
Sign.Quality identification module 2022 is also possible to identify whether the shape lines of the fruit are complete using shape species characteristic, if should
Fruit shapes lines are tortuous, and quality identification module 2022 can identify that the fruit product gesture is failed, and quality identification module 2022 can
To generate qualitative characteristics of failing, if shape lines are complete, without complications, qualifying quality is can be generated in quality identification module 2022
Feature.
Identify whether the object quality in image passes by quality identification module 2022, so that whether judgment object is complete
It is whole, it can effectively improve the accuracy of quality identification.
In the present embodiment, quality identification module 2022 may include:
Fruit quality identification module 20221, for using the fruit figure in Fruit types feature identification described image
Picture, and generate fruit quality feature；
In the present embodiment, fruit quality identification module 20221 can also use Fruit types feature, then identify in fruit
Color, and color area accounting is calculated, for example, if apple contains red and black, fruit quality identification module in image
20221 sizes that identification is red and black is in fruit image, calculate black and red percentage, if black area account for it is red
Color area is more than 30 percent, and fruit quality identification module 20221 identifies that the apple is failed, and generates fruit quality of failing
Feature, if black area accounts for red area less than 30 percent, fruit quality identification module 20221 identifies that the apple is passed,
Generate qualifying fruit quality feature.For example, fruit quality identification module 20221 is known if banana includes yellow and black in image
The size of other yellow and black in banana image calculates the percentage of yellow and black, if black area accounts for yellow face
For product more than 30 percent, fruit quality identification module 20221 identifies that the banana is failed, and generates the fruit quality spy that fails
Sign, if black area accounts for yellow area lower than 30 percent, fruit quality identification module 20221 identifies that the banana is passed, raw
At qualifying fruit quality feature.
Fruit quality identification module 20221 can also use the size species characteristic in species characteristic in the present embodiment,
Identify qualitative characteristics, for example, fruit quality identification module 20221 identifies the size of apple in image, the apple in image is kind
The apple for having planted 60 to 80 days calculates the apple actual size in the image using scaling, if the calculated result apple is
2-3 centimetres long, 1-2 centimetres wide, the apple for actually having planted 60 to 80 days apples is 3-4 centimetres long, 2-3 centimetres wide, fruit product
Matter identification module 20221 identifies that the apple quality is failed, and generates fruit quality feature of failing, if calculated result is the apple
3-4 centimetres long, 2-3 centimetres wide, satisfaction has planted the size of 60 to 80 days apples, and fruit quality identification module 20221 identifies
The apple quality is passed, and qualifying fruit quality feature is generated.
Fruit quality feature can be generated by fruit quality identification module 20221, to sentence according to fruit quality feature
Whether disconnected fruit meets the requirements.Facilitate user to be managed fruit tree, improves the efficiency of management.
Plant quality identification module 20222, for using the plant figure in floristics feature identification described image
Picture generates plant quality feature；
In the present embodiment, plant quality identification module 20222 can use floristics feature, then identify in plant
Color, and color area accounting is calculated, for example, if plant contains green and black, plant quality identification module 20222 in image
The size of identification green and black in plant image, calculates black and green percentage, if black area accounts for green area
More than 30 percent, plant quality identification module 20222 identifies the plant irregular growth, and it is special to generate abnormal plant quality
Sign, if black area accounts for green areas less than 30 percent, plant quality identification module 20222 identifies that the plant is normal, raw
At normal plants qualitative characteristics.For example, plant quality identification module 20222 identifies if plant includes yellow and green in image
The size of yellow and green in banana image, calculates the percentage of yellow and green, if green areas accounts for yellow area
More than 50 percent, plant quality identification module 20222 identifies that the plant is normal, normal plants qualitative characteristics is generated, if green
Color area accounts for yellow area lower than 50 percent, and plant quality identification module 20222 identifies that the plant is withered, generates withered plant
Object qualitative characteristics.
In the present embodiment, the life of plant in image can be identified with quicklook by plant quality identification module 20222
Long situation, for example, the plant of fruit tree is withered and yellow in the growth busy season of fruit tree, user can be according to plant quality identification module 20222
Recognition result, it is abnormal to judge that current fruit tree occurs, the fruit tree is checked and treated immediately, to reduce user's kind
The loss of plant.
Insect quality identification module 20223, for using the insect figure in caste feature identification described image
Picture generates insect qualitative characteristics.
In the present embodiment, insect quality identification module 20223 can use caste feature, according to the insect of identification
Type identifies the type of pest in insect, for example, prestoring in insect quality identification module 20223 containing user is pest species,
If it is pest species that caste, which contains user to prestore, in image, insect quality identification module 20223 identifies the insect infestations fruit
Tree growth, the fruit tree irregular growth, pest qualitative characteristics, if it is species of insect pests that caste is prestored without containing user in image
Class, insect quality identification module 20223 identify that the fruit tree growth is normal, beneficial insect qualitative characteristics.
The pest in image can be quickly recognized by insect quality identification module 20223, user can be according to identification
As a result judge the growing state of current fruit tree, for example, the pest for endangering apple tree occurs in apple tree, user needs to remove immediately,
It can be bred to avoid pest, avoid pest from continuing to encroach on other apple trees, reduce the loss of user.
Fruit number identification module 2023 for using the fruit image statistics fruit number, and generates fruit number
Feature；
In the present embodiment, fruit number identification module 2023 can use object features, such as color characteristic, shape spy
Sign, patterned feature, species characteristic etc., to the fruit number in the fruit image statistics of the use fruit image.Fruit number is known
Other module 2023 can calculate the fruit for meeting color characteristic in the fruit image by the color characteristic in identification fruit image
Quantity, and generate fruit number feature.For example, fruit number identification module 2023 can identify the apple in apple tree Image
Fruit, color characteristic are red, and for acquisition module 201 after acquiring fruit image, fruit number identification module 2023 identifies the fruit
In real image, color is red object, and statistical color is the quantity of red object, and the quantity of the object of the red is apple
The quantity is generated fruit number feature by the quantity of Tree Fruit, fruit number identification module 2023.
In the present embodiment, fruit number identification module 2023 can also be connected with category identification module 2021, and type is known
After other module 2021 identifies the object in acquisition image, fruit number identification module 2023 counts category identification module respectively
The physical quantities of 2021 identifications, then by color characteristic, the object features such as shape feature or species characteristic count category identification mould
The fruit number in object that block 2021 identifies.
By the fruit number in 2023 statistical picture of fruit number identification module, user can be allowed quickly to know the fruit tree
Bearing capacity and production capacity, facilitate user sell or plantation processing.
Number of plant identification module 2024 for counting number of plant using the plant image, and generates number of plant
Feature；
In the present embodiment, number of plant identification module 2024 can use object features, such as color characteristic, shape spy
Sign, patterned feature, species characteristic etc. count the number of plant in the plant image to the plant image of use.Number of plant is known
Other module 2024 can calculate the plant for meeting color characteristic in the plant image by the color characteristic in identification plant image
Quantity, and generate number of plant feature.For example, number of plant identification module 2024 can identify the tree in apple tree Image
Leaf, color characteristic are green, and after acquiring image, number of plant identification module 2024 identifies in the image acquisition module 201
Color is the object of green, and statistical color is the quantity of the object of green, and the quantity of the object of the green is apple tree leaf
Quantity, number of plant identification module 2024 by the quantity generate number of plant feature.
In the present embodiment, number of plant identification module 2024 can also be connected with category identification module 2021, and type is known
After other module 2021 identifies the object in acquisition image, number of plant identification module 2024 counts category identification module respectively
The physical quantities of 2021 identifications, then by color characteristic, the object features such as shape feature or species characteristic count category identification mould
The fruit number in object that block 2021 identifies.
Insect numbers identification module 2025 for counting insect numbers using the insect image identification, and generates insect numbers
Feature.
In the present embodiment, insect numbers identification module 2025 can use object features, such as color characteristic, shape spy
Sign, patterned feature, species characteristic etc. count the insect numbers in the insect image identification to the insect image identification of use.Insect numbers are known
Other module 2025 can calculate the insect for meeting color characteristic in the insect image identification by the color characteristic in identification insect image identification
Quantity, and generate insect numbers feature.For example, insect numbers identification module 2025 can identify the elder brother in apple tree Image
Worm, color characteristic are colour, that is, include the object of at least two or more colors, acquisition module 201 is after acquiring image, insect
Quantity identification module 2025 identifies that color is colored object in the image, and statistical color is the quantity of colored object, should
The quantity of colored object is the quantity of apple tree insect, which is generated insect numbers spy by insect numbers identification module 2025
Sign.For example, insect numbers identification module 2025 can identify that the body form in insect image identification, shape feature are irregular shape
Shape, insect numbers identification module 2025 identifies that shape is irregular object in the image, and Statistical Shape is irregular object
The quantity of the quantity of body, the irregular object is the quantity of apple tree insect, and generates insect numbers feature.
In the present embodiment, insect numbers identification module 2025 can also be connected with category identification module 2021, and type is known
After other module 2021 identifies the object in acquisition image, insect numbers identification module 2025 counts category identification module respectively
The physical quantities of 2021 identifications, then by color characteristic, the object features such as shape feature or species characteristic count category identification mould
The fruit number in object that block 2021 identifies.
In the present embodiment, pass through fruit number identification module 2023, number of plant identification module 2024 and insect numbers
Identification module 2025 can improve the recognition capability of image identification system with fruit in statistical picture, the quantity of plant and insect,
Increase the accuracy of identification.
Analysis module 203, for generating analysis data using the object features in described image；
In the present embodiment, analysis module 203 can using identification module 202 identify object features, carry out analysis or
Judgement generates analysis data, and user can also do the operation of next step, facilitate management of the user to orchard according to analysis data,
Reduce the difficulty of management.
In the present embodiment, analysis module 203 may include:
Growth analysis module 2031, for generating the growth analysis data of object using the object features, and will be described
Growth analysis data are sent to the memory module 204；
In the present embodiment, growth analysis module 2031 can respectively with Fruit types identification module 20211, floristics
Identification module 20212, caste identification module 20213, fruit quality identification module 20221, plant quality identification module
20222, insect quality identification module 20223, fruit number identification module 2023, number of plant identification module 2024, insect number
It measures identification module 2025 to be connected, growth analysis module 2031 can receive the object features that above-mentioned modules generate respectively, raw
At analysis data, for example, growth analysis module 2031 can be connected with caste identification module 20213, caste is received
Identification module 20213 generates caste feature, and it includes pest, such as apple in caste feature that growth analysis module 2031, which is analyzed,
The pest of fruit tree natural enemy analyzes data prompts user by pest and removes in time, if not having if so, then generating pest analysis data
Have, then generates normal growth analysis data, it is for reference.For example, growth analysis module 2031 can be identified with fruit number
Module 2023 is connected, the fruit number feature generated using the identification of fruit number identification module 2023, more current fruit number
It makes comparisons with Average fruit data, if current fruit number is greater than Average fruit quantity, growth analysis module 2031 be can be generated
High throughput analysis data, if current fruit number is less than Average fruit quantity, low yield is can be generated in growth analysis module 2031
Analyze data.For example, growth analysis module 2031 can be connected with plant quality identification module 20222, growth analysis module
The 2031 plant variety features identified using plant quality identification module 20222, if plant variety feature is withered plant quality
Feature, growth analysis module 2031 generate withered growth analysis data, remind user to handle the fruit tree in time, if plant variety is special
Sign is normal plant quality feature, and growth analysis module 2031 generates normal growth and analyzes data, processing for reference.
Analysis data are generated by growth analysis module 2031, on the one hand refer to working as fruit tree to user by analysis data
Preceding upgrowth situation, the management that user on the other hand can also be allowed to be planted by analyzing data, can carry out pin according to yield
Management is sold, Cultivate administration etc. can be carried out according to the speed of growth, improve the plantation efficiency of user.
Forecast analysis module 2032, for generating forecast analysis data using the growth analysis data, and will be described pre-
It surveys analysis data and is sent to the memory module 204；
In the present embodiment, forecast analysis module 2032 can be connected with by growth analysis module 2031, forecast analysis
Module 2032 is predicted using the growth analysis data that growth analysis module 2031 generates, for example, if forecast analysis module
2032, which obtain the normal growth that growth analysis module 2031 generates, analyzes data, and forecast analysis module 2032 is according to normal growth point
It analyses data and generates normal forecast analysis data, predict the fruit tree by normal growth, if forecast analysis module 2032 obtains growth point
The withered growth analysis data that module 2031 generates are analysed, forecast analysis module 2032 generates withered according to withered growth analysis data
Forecast analysis data predict that the fruit tree will wither.The prediction point that user can also generate according to forecast analysis module 2032
Analysis data are prejudged, and can be allowed user that can formulate planting scheme to fruit tree, be improved the efficiency of management of user.
In the present embodiment, forecast analysis module 2032 can also respectively with Fruit types identification module 20211, plant species
Class identification module 20212, caste identification module 20213, fruit quality identification module 20221, plant quality identification module
20222, insect quality identification module 20223, fruit number identification module 2023, number of plant identification module 2024, insect number
Identification module 2025 is measured to be connected.Forecast analysis module 2032 can obtain the object features that above-mentioned modules generate respectively, raw
At prediction growth data.
Memory module 204 records object features that the identification module 202 obtains and described for storing described image
The analysis data that analysis module 203 obtains；
In the present embodiment, data can be saved using memory module 204, avoids loss of data, memory module
204 can be used hard-disc storage, and terminal storage also can be used, and cloud storage also can be used, can also be in modules
Storage unit is set, stores the data of modules etc. mode respectively, specific storage mode can be according to actual needs
It is adjusted.
Rotating module 205 for carrying the acquisition module 201, and controls the acquisition module 201 and carries out 0-360 degree
It is mobile；
In this embodiment, acquisition module 201 can be allowed to carry out multi-angle image acquisition, as acquisition module 201 acquires centainly
Fruit tree image in range areas, can allow acquisition module 201 to be monitored image management to the region.
In the present embodiment, rotating module 205 may include rotating base, be fixed on the runner assembly of rotating base, with
And the rotation axis being connected with runner assembly, rotation axis are equipped with fixing piece, rotation axis passes through the fixing piece and 201 phase of acquisition module
Even.Rotating base can be metal plate or fixed station or fixing seat etc., and runner assembly can be motor or motor, and rotation axis can
To be metal shaft or plastic shaft, rotation axis can be arranged with multistage, so that rotation axis can move up and down extension, rotation axis is equipped with
Fixing piece, fixing piece can be fixing clamp or socket etc., can also be equipped in fixing piece and paste liquid, allow fixation using liquid is pasted
Part is connected with acquisition module 201.
In the present embodiment, rotation axis is driven by control runner assembly, drives 201 turns of acquisition module by rotation axis
It is dynamic, to realize 360 degree rotation, acquisition module 201 can be shot with 360 degree rotation, improves the acquisition energy of acquisition module 201
Power.
In the present embodiment, acquisition module 201, identification module 202, analysis module 203 and memory module 204 can also be consolidated
Surely it links together, the fixing piece in rotation axis can also fix acquisition module 201, identification module 202, analysis module simultaneously
203 and memory module 204.
Cruise module 206, for carry the acquisition module 201, the identification module 202, the analysis module 203,
The memory module 204 and the mobile module
In the present embodiment, acquisition module 201, identification module 202, analysis module can be carried using cruise module 206
203, memory module 204 and mobile module cruise are walked about, to increase the identification range and practicability of image identification system.At this
It is fooled in embodiment, cruise module 206 can be unmanned plane or transport vehicle etc., allow whole image identifying system can be on different ground
Fang Jinhang Image Acquisition, for example, orchard can, can use the cruise locomotive function of cruise module 206, allow image identification system
It is moved in entire orchard, can also be used as monitoring system use, mobile monitoring is carried out to orchard.
In the present embodiment, cruise module 206 includes moving assembly, is fixed on the mobile base of moving assembly, mobile bottom
Seat is equipped with control assembly and communication part, and control assembly is connected with communication part；In the present embodiment.Moving assembly can be fortune
Defeated vehicle or unmanned vehicle, are equipped with mobile base on moving assembly, and mobile base can be metal plate or plastic plate or socket or bottom
Plate etc., control assembly and communication part are respectively provided in mobile base, and control assembly is used to user's control cruise mould
Block 206, if moving assembly uses transport vehicle, user can directly control control assembly on transport vehicle, to control transport vehicle
Operation, communication part can be used for communicating use.
In the present embodiment, acquisition module 201, identification module 202, analysis module 203, memory module 204 and mobile mould
Block is fixed on mobile base, control assembly can respectively with identification module 202, analysis module 203, memory module 204 and mobile
Module is connected.Identification module 202, analysis module 203, memory module 204 and mobile mould can be controlled respectively by control assembly
Block work, communication module can also be connected with identification module 202, analysis module 203, memory module 204 and mobile module respectively,
The data of identification module 202, analysis module 203, memory module 204 are transferred to background apparatus etc. by communication module.
The present embodiment proposes a kind of image identification system, acquires image by acquisition module 201, identification module 202 is known
The image not acquired, analysis module 203 analyze the object features that identification module 202 identifies and generate analysis data, will analyze number
According to being stored in memory module 204, the image identification system structure that the present embodiment proposes is simple, and Image Acquisition ability is strong, identification
Ability is strong, and identification accuracy is high, while can carry out analysis according to the object features of identification and generate analysis data are for reference to make
With user can be planned using analysis data, effectively improve yield and the efficiency of management, and whole image identifying system is real
It is strong with property, image monitoring can also be carried out, the planting cost of user is reduced.
Referring to Fig. 3, the structural schematic diagram of pattern recognition device one of which embodiment of the invention is shown, in this implementation
In example, the image identification system 301 including all technical characteristics of above-described embodiment, and be connected with the image identification system 301
Background apparatus 302.
Image identification system 301 identifies the object in image for acquiring image, and to the object in described image into
Row analysis.
Image Acquisition is carried out by image identification system 301 and identifies the object in image, and object is subjected to analysis generation
Data are analyzed, image identification system 301 can transfer data to background apparatus 302, is managed collectively by background apparatus, Yong Huwu
Image identification system 301 need to be operated on the spot, simplify the operation sequence of user, also facilitate user management, improve user
The efficiency of management.
Background apparatus 302, for managing control image identification system.
In the present embodiment, background apparatus 302 can also can be wireless with 301 wired connection of image identification system,
If background apparatus 302 and image identification system 301 are wirelessly connected, background apparatus 302 can be with the communication of image identification system 301
Component is connected, and carries out wireless data transmission.
The present embodiment proposes a kind of pattern recognition device, which can pass through image identification system 301
The image data of the image of acquisition, the image of identification and analysis, can be sent to backstage and filled by acquisition, identification and analysis image
302 are set, is managed collectively by background apparatus 302, it is user-friendly, improve user management efficiency.
All the embodiments in this specification are described in a progressive manner, the highlights of each of the examples are with
The difference of other embodiments, the same or similar parts between the embodiments can be referred to each other.
It should be understood by those skilled in the art that, the embodiment of the embodiment of the present invention can provide as method, apparatus or calculate
Machine program product.Therefore, the embodiment of the present invention can be used complete hardware embodiment, complete software embodiment or combine software and
The form of the embodiment of hardware aspect.Moreover, the embodiment of the present invention can be used one or more wherein include computer can
With in the computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) of program code
The form of the computer program product of implementation.
The embodiment of the present invention be referring to according to the method for the embodiment of the present invention, terminal device (system) and computer program
The flowchart and/or the block diagram of product describes.It should be understood that flowchart and/or the block diagram can be realized by computer program instructions
In each flow and/or block and flowchart and/or the block diagram in process and/or box combination.It can provide these
Computer program instructions are set to general purpose computer, special purpose computer, Embedded Processor or other programmable data processing terminals
Standby processor is to generate a machine, so that being held by the processor of computer or other programmable data processing terminal devices
Capable instruction generates for realizing in one or more flows of the flowchart and/or one or more blocks of the block diagram
The device of specified function.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing terminal devices
In computer-readable memory operate in a specific manner, so that instruction stored in the computer readable memory generates packet
The manufacture of command device is included, which realizes in one side of one or more flows of the flowchart and/or block diagram
The function of being specified in frame or multiple boxes.
These computer program instructions can also be loaded into computer or other programmable data processing terminal devices, so that
Series of operation steps are executed on computer or other programmable terminal equipments to generate computer implemented processing, thus
The instruction executed on computer or other programmable terminal equipments is provided for realizing in one or more flows of the flowchart
And/or in one or more blocks of the block diagram specify function the step of.
Although the preferred embodiment of the embodiment of the present invention has been described, once a person skilled in the art knows bases
This creative concept, then additional changes and modifications can be made to these embodiments.So the following claims are intended to be interpreted as
Including preferred embodiment and fall into all change and modification of range of embodiment of the invention.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or terminal device including a series of elements not only wrap
Those elements are included, but also including other elements that are not explicitly listed, or further includes for this process, method, article
Or the element that terminal device is intrinsic.In the absence of more restrictions, being wanted by what sentence "including a ..." limited
Element, it is not excluded that there is also other identical elements in process, method, article or the terminal device for including the element.
Above to a kind of image identification system provided by the present invention and a kind of pattern recognition device, detailed Jie has been carried out
It continues, used herein a specific example illustrates the principle and implementation of the invention, and the explanation of above embodiments is only
It is to be used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, according to this hair
Bright thought, there will be changes in the specific implementation manner and application range, in conclusion the content of the present specification should not manage
Solution is limitation of the present invention.
Claims (10)
1. a kind of image identification system characterized by comprising
Acquisition module, for acquiring image；
Identification module, for identification object features in described image；
Analysis module, for generating analysis data using the object features in described image；
Memory module, for storing described image, the object features and the analysis module for recording the identification module acquisition are obtained
The analysis data taken.
2. image identification system according to claim 1, which is characterized in that further include:
Rotating module, for carrying the acquisition module, and it is mobile to control the acquisition module 0-360 degree；
The rotating module includes: rotating base, is fixed on the runner assembly of the rotating base, and with the runner assembly
Connected rotation axis, the rotation axis are equipped with fixing piece, and the rotation axis is connected by the fixing piece with the acquisition module.
3. image identification system according to claim 1, which is characterized in that the object features include species characteristic, product
Matter feature, the identification module include:
Category identification module, for identification species characteristic in described image；
Quality identification module, for identifying qualitative characteristics using the species characteristic.
4. image identification system according to claim 3, which is characterized in that the category identification module includes:
Fruit types identification module, for identification the Fruit types feature in described image；
Floristics identification module, for identification the floristics feature in described image；
Caste identification module, for identification the caste feature in described image.
5. image identification system according to claim 4, which is characterized in that the quality identification module includes:
Fruit quality identification module for being identified the fruit image in described image using the Fruit types feature, and is generated
Fruit quality feature；
Plant quality identification module, for generating and planting using the plant image in floristics feature identification described image
Object qualitative characteristics；
Insect quality identification module, for generating elder brother using the insect image identification in caste feature identification described image
Worm qualitative characteristics.
6. image identification system according to claim 5, which is characterized in that the object features further include quantative attribute,
The identification module further include:
Fruit number identification module for using the fruit image statistics fruit number, and generates fruit number feature；
Number of plant identification module for counting number of plant using the plant image, and generates number of plant feature；
Insect numbers identification module for counting insect numbers using the insect image identification, and generates insect numbers feature.
7. image identification system according to claim 1, which is characterized in that the analysis module includes:
Growth analysis module, for generating the growth analysis data of object using the object features, and by the growth analysis
Data are sent to the memory module；
Forecast analysis module, for generating forecast analysis data using the growth analysis data, and by the forecast analysis number
According to being sent to the memory module.
8. image identification system according to claim 2, which is characterized in that further include cruise module；
The cruise module, for carrying the acquisition module, the identification module, the analysis module, the memory module
With the mobile module.
9. image identification system according to claim 8, which is characterized in that the cruise module includes moving assembly, Gu
Be scheduled on the mobile base of the moving assembly, the mobile base is equipped with control assembly and communication part, the control assembly with
The communication part is connected；
The acquisition module, the identification module, the analysis module, the memory module and the mobile module are fixed on institute
State mobile base, the control assembly respectively with the identification module, the analysis module, the memory module and the movement
Module is connected.
10. a kind of pattern recognition device, which is characterized in that including such as described in any item image identification systems of claim 1-9,
And the background apparatus being connected with described image identifying system；
Described image identifying system identifies the object in image, and divide the object in described image for acquiring image
Analysis；
The background apparatus, for managing control described image identifying system.
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