CN113850124A - Recoverable garbage supervision method, transportation equipment and storage medium - Google Patents
Recoverable garbage supervision method, transportation equipment and storage medium Download PDFInfo
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- CN113850124A CN113850124A CN202110949535.3A CN202110949535A CN113850124A CN 113850124 A CN113850124 A CN 113850124A CN 202110949535 A CN202110949535 A CN 202110949535A CN 113850124 A CN113850124 A CN 113850124A
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- garbage
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65F—GATHERING OR REMOVAL OF DOMESTIC OR LIKE REFUSE
- B65F3/00—Vehicles particularly adapted for collecting refuse
- B65F3/001—Vehicles particularly adapted for collecting refuse for segregated refuse collecting, e.g. vehicles with several compartments
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Abstract
The invention discloses a supervision method of recoverable garbage, transportation equipment and a storage medium, wherein the supervision method comprises the steps of receiving image information, and segmenting an image to obtain a plurality of target objects; if the exposure area of any target object is judged to be within the preset range, acquiring the characteristic information of the target object, and importing the characteristic information into a preset model to acquire the type of the target object; and recovering the target objects of the specified type according to the requirements and monitoring the recovery and classification processes of the target objects in real time. The garbage classification method can be used for shooting and analyzing images of garbage and identifying the type of a partially shielded target object, so that the garbage type can be accurately identified even if the garbage is in a shielded state, and whether the garbage is classified or not is determined; meanwhile, the supervision method is applied to garbage transportation equipment, and the wrongly classified garbage can be selected in the garbage transportation process, so that the garbage classification efficiency is improved.
Description
Technical Field
The invention relates to the field of garbage recycling treatment, in particular to a supervision method, transportation equipment and a storage medium for recyclable garbage.
Background
At present, in order to recycle useful garbage, reduce landfill of garbage and reduce harm of a large amount of garbage to the environment, garbage classification becomes social consensus. However, in the existing garbage disposal process, people are generally required to manually classify the garbage and then throw the classified garbage into the corresponding garbage can, so that the purpose of garbage classification is achieved. However, even if people classify the garbage manually, a small part of garbage can still be mistakenly thrown, and garbage cleaning personnel directly throw all garbage in the garbage can into the garbage transport vehicle, so that the garbage with the wrong classification cannot be taken out in time, and the garbage still needs to be classified manually in a later period.
And current garbage classification generally shoots the general appearance of rubbish through the camera, just can carry out accurate classification to rubbish, if pile up each other between rubbish and lead to partial rubbish to be sheltered from, then can't accurately discern the rubbish kind, still can't carry out accurate classification to rubbish.
Disclosure of Invention
In order to overcome the defects of the prior art, one of the purposes of the invention is to provide a monitoring method for recyclable garbage, which can automatically realize the garbage classification and recycling effect and improve the garbage classification accuracy.
The invention also aims to provide a transporting device capable of recycling the garbage, and the method for supervising the recyclable garbage is applied to the garbage transporting device, so that the garbage can be directly classified in the transporting process, and the efficiency is improved.
The present invention also provides a computer storage medium for executing the above method for monitoring recyclable garbage.
One of the purposes of the invention is realized by adopting the following technical scheme:
a method of supervising recyclable waste, comprising:
receiving image information, and segmenting the image to obtain a plurality of target objects;
if the exposure area of any target object is judged to be within the preset range, acquiring the characteristic information of the target object, and importing the characteristic information into a preset model to acquire the type of the target object;
and recovering the target objects of the specified type according to the requirements and monitoring the recovery and classification processes of the target objects in real time.
Further, the method for acquiring the image information comprises the following steps:
the designated area is continuously photographed at preset time intervals to obtain a plurality of photographed images, and the plurality of photographed images are partially replaced to obtain image information.
Further, the method for locally replacing a plurality of images comprises the following steps:
identifying all the target objects in all the shot images, and connecting at least three same target objects in all the shot images in pairs;
adjusting angles and/or positions of all shot images to enable areas obtained by connection in all the shot images to coincide;
and comparing the resolution of the target object at the same position in the shot images after the angles are adjusted, and replacing the target object with the target object image at the same position and with the resolution higher than the preset value in other shot images on the basis of any shot image if the resolution of any target object in the shot images is lower than the preset value, so as to obtain a clear shot image.
Further, if the exposure area of any one target object is judged to be smaller than the minimum value in the preset range, tracking and identifying the target object until the exposure area of the acquired target object reaches the preset range again.
Further, if the exposure area of any one target object is judged to be larger than the maximum value in the preset range, the type of the target object is directly obtained through image recognition processing, and corresponding type recovery processing is carried out on the target object.
Further, the characteristic information is one or more combinations of characters, patterns, outer contours, colors and materials of the target object.
Further, the preset model is a neural network model obtained by training characteristic information as a neural network training sample.
Further, when the target object is monitored, if the target object is recovered to the recovery area with the wrong garbage type through monitoring, an alarm prompt is initiated according to the image information, the characteristic information, the type information, the correct recovery position and the current recovery position of the target object.
The second purpose of the invention is realized by adopting the following technical scheme:
a transportation device for recyclable garbage comprises a transportation body and a recycling body for executing the supervision method for recyclable garbage.
The third purpose of the invention is realized by adopting the following technical scheme:
a storage medium having stored thereon a computer program which, when executed, implements the method of administering recyclable waste as described above.
Compared with the prior art, the invention has the beneficial effects that:
the garbage classification method can be used for shooting and analyzing images of garbage and identifying the type of a partially shielded target object, so that the garbage type can be accurately identified even if the garbage is in a shielded state, and whether the garbage is classified or not is determined; meanwhile, the supervision method is applied to garbage transportation equipment, the garbage with wrong classification can be selected in the garbage transportation process, the step of manually classifying the garbage is replaced, the garbage classification effect is accurately achieved, and meanwhile the garbage classification efficiency can be improved.
Drawings
FIG. 1 is a schematic flow chart of a method for supervising recyclable garbage according to the present invention;
fig. 2 is a schematic block diagram of the recyclable waste transport apparatus of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
Example one
The embodiment provides a supervision method for recyclable garbage, which can be used for recycling and classifying garbage, sorting out the garbage with wrong classification and improving the garbage classification accuracy.
The supervision method can classify and recycle the garbage under the condition that the garbage classification is not executed at all, and can detect the garbage classified manually for the second time so as to judge whether the garbage classification is wrong or not.
As shown in fig. 1, the method for supervising recyclable garbage of the present embodiment specifically includes the following steps:
step S1: receiving image information, and segmenting the image to obtain a plurality of target objects;
step S2: if the exposure area of any target object is judged to be within the preset range, acquiring the characteristic information of the target object, and importing the characteristic information into a preset model to acquire the type of the target object;
step S3: and recovering the target objects of the specified type according to the requirements and monitoring the recovery and classification processes of the target objects in real time.
In this embodiment, in the step S1, the image information is obtained by shooting the garbage with the camera, and since the shot image needs to be analyzed, a picture with relatively high definition is needed, so that the embodiment can obtain the image with high definition by combining multiple shooting and collecting and post-image processing, specifically, continuously shooting the designated area where the garbage is located according to a preset time interval to obtain multiple shot images, and partially replacing the multiple shot images to obtain the image information.
After a plurality of shot images are obtained in the embodiment, because the position of the garbage is likely to change in the transportation process, after the same designated area is continuously shot, the target object in each shot image can be identified and marked, a plurality of shot images with the most same target object are subjected to local replacement processing, one or two shot images with the least same target object are abandoned, namely, the shot images with the garbage in a relatively stable state are reserved, and therefore the garbage can be more accurately classified and recycled for the target object.
After a plurality of shot images are obtained, since a part of the target object may be blurred in the shooting process, the method for locally replacing a plurality of images is as follows:
step S11: and identifying all the target objects in all the shot images, and connecting at least three same target objects in all the shot images in pairs.
The method for identifying all the objects in the image can identify the contour line of each object in an image contour line extraction mode, and mark the object in each complete contour line as one object. After all the target objects of the multiple shot images are marked, the target objects with the contour similarity reaching the preset ratio in the multiple shot images are regarded as the same target object, and the same target object in the multiple shot images is named as the same name. And then selecting at least three target objects with the same name from all the shot images, and connecting the connecting points of the three same target objects in each shot image in pairs by taking the central points of the target objects as connecting points, thereby forming a triangular area in each shot image.
Step S12: all the captured images are angularly and/or positionally adjusted so that the areas of the captured images that are connected coincide.
Because the shooting angle of each shot image is deviated or the garbage is not in a static state during shooting, in order to accurately identify the position of each target object in each shot image, angle and/or position adjustment needs to be carried out on the shot images, and triangular areas obtained by connection in all the shot images are kept coincident all the time in the adjustment process, so that each position in a plurality of shot images can be in one-to-one correspondence, the outline and the position of a fuzzy target object can be conveniently determined from other shot images, and the subsequent replacement operation can be conveniently completed.
Step S13: and comparing the resolution of the target object at the same position in the shot images after the angles are adjusted, and replacing the target object with the target object image at the same position and with the resolution higher than the preset value in other shot images on the basis of any shot image if the resolution of any target object in the shot images is lower than the preset value, so as to obtain a clear shot image. In this example, one of the shot images may be used as a basis, and all the objects with low resolution in the shot image are replaced by the same object image with high resolution, so that all the objects in one shot image are in a clear state, and thus one shot image with high resolution is obtained.
For example: if the resolution of the target object a in the shot image A is lower than the preset value and the resolution of the target object a in the shot image B is higher than the preset value, the target object a in the shot image B can be replaced into the shot image A, so that the target object a in the shot image A is in a clear state.
After a clear image is obtained, the exposed area of each target object is calculated, and when the exposed area of any target object is judged to be within a preset range, the type of the target object cannot be directly embodied according to the existing contour of the target object, and the garbage type of the target object cannot be directly identified, the target object is indicated to be in a shielded state, at the moment, the characteristic information of the target object exposed in the outer area is extracted, and the characteristic can be one of characters, images, outer contours, colors, materials and the like, or the combination of the characteristics. The feature extraction method can be performed by the existing methods such as image feature extraction, object material identification, object color analysis, etc., and the various feature extraction methods will not be described in detail here.
After the characteristic information of the target object is obtained, the characteristic information is led into a preset model, the model is a neural network model obtained by inputting a training sample through the characteristic information as a neural network, outputting the training sample through the garbage type as the neural network, and training and learning the neural network. In addition, the weight setting can be carried out on the input training sample before the neural network training, so that the accuracy of the neural network model is improved.
After the characteristic information of the target object is identified and the type of the target object is output from the neural network model according to the characteristic information, the type of the garbage can be obtained; and after the types of all the target objects are analyzed, outputting a type analysis result to a user. And then, the garbage of the appointed type can be screened out according to the user requirement to realize garbage recycling, and the garbage of different types can be classified to realize the garbage classification function.
If the exposure area of any one target object is smaller than the minimum value in the preset range in the step S2, it means that most of the area of the target object is blocked, and the true type of the target object may not be accurately identified, and at this time, the camera is required to track the target object, and the exposure area of the target object is always recalculated under the tracking condition until the exposure area of the target object reaches the preset range again; because the target object may move due to transportation and the like, and the exposed area may be increased due to displacement in the moving process of the target object, the tracking of the target object in the embodiment can improve the probability of accurate analysis of the target object. In addition, a vibration instruction can be actively initiated to the mechanism for transporting the garbage, and the vibration instruction can control the small-amplitude vibration generated by the vibration mechanism so as to drive the target object to perform small-amplitude motion, so that the exposed area of the target object is gradually increased. If the exposed area of the target object still cannot be increased through vibration, the steps of identifying and analyzing the target object are abandoned, and after the steps of image acquisition, analysis and recovery are completed, the garbage is remixed and then the steps of image acquisition and analysis are performed on the garbage again, so that the type of each piece of garbage in the garbage team is identified as much as possible, and the garbage with wrong classification is found from the garbage pile.
If the exposed area of any one of the objects is determined to be larger than the maximum value in the preset range in step S2, it means that most of the area of the object is exposed, and at this time, the feature extraction and subsequent model processing steps are not required to be performed, and the type of the object can be obtained directly through the existing image recognition processing, and the recovery processing can be performed directly according to the type of the object.
According to the embodiment, the target object of the specified type can be grabbed in a mechanical arm mode and placed in the specified area to be recycled; the object may be grasped by other means or mechanisms. In the process of classifying and recovering the target objects of the specified types, the camera is utilized to monitor the target objects in real time, whether the mechanical arm correctly grabs the specified target objects is judged in the monitoring process, images of the recovery areas of the target objects can be acquired through the camera, and whether the specified target objects are placed in the corresponding recovery areas is judged according to the images. If the situation that the mechanical arm grabs the wrong target object is judged, or the situation that the target object is recovered to the recovery area with the wrong garbage type is monitored, an alarm prompt is initiated, the image information of the target object collected by the camera is sent to the appointed terminal, the characteristic information and the type information of the target object are analyzed, the correct recovery area where the target object should be placed and the recovery area where the target object is currently placed are sent to the appointed terminal, and therefore a user is informed of relevant information of the target object, and the user can conveniently execute corresponding correction operation. The correction operation can be to manually put the wrongly placed garbage into the correct recovery area again, or to control the mechanical arm in real time in a manual mode, or even to automatically send the target object information to the controller of the mechanical arm, so that the mechanical arm can grab the target object again and place the target object into the correct recovery area, thereby realizing the accurate classification and recovery of the garbage.
Example two
The embodiment provides a transportation equipment of recoverable rubbish, this transportation equipment includes the transportation body and carries out the recovery body like the supervision method of recoverable rubbish as above, and wherein retrieve the body and can set up on the transportation body for the packing box structure, retrieve the inside operation such as a series of shootings, analysis, classification and recovery of carrying out of body in the transportation body transportation, make full use of transit time accomplishes and retrieves the action, raise the efficiency.
As shown in fig. 2, three large areas may be disposed in the recycling body of this embodiment, the first area is a filtering area, the recycling body is provided with a feeding port and a discharging port, the feeding port is directly communicated with the filtering area, and the discharging port may correspond to the second and third areas; the garbage can be grabbed by the mechanical arm on the transportation equipment, the garbage in the garbage can is poured into the filtering area from the feeding hole to realize solid-liquid separation, and even the purpose of separating out small-volume objects is realized, wherein the small-volume objects can be unformed objects such as broken glass, stone blocks and the like; this filtration zone can be realized through the cylinder device that is equipped with the filtration pore, is equipped with the filtration pore of certain diameter in the cylinder device, utilizes drive arrangement to drive the cylinder device and rotates along the axis direction, lets little volume object or liquid can drop through the filtration pore in the cylinder device to realize the purpose of little volume object screening and solid-liquid separation.
The rubbish after filtering in the filtering area can be directly poured into the second area through the dumping mode of the roller device, the rubbish can be conveyed to the second area through the conveying belt by pouring the conveying belt in advance, the rubbish transferring mode collected between the first area and the second area can be freely set and planned in combination with the inner space structure of the recovery body, and the rubbish transferring mode between the first area and the second area is not specifically limited. The second area in this embodiment is an identification area, which is used for shooting and analyzing the garbage to identify the type of each garbage; a vibration chassis can be arranged in the second area, and after the conveying belt conveys the garbage to the vibration chassis, the vibration chassis can firstly start a small-amplitude vibration function to separate the garbage on the vibration chassis as much as possible, so that the condition that the garbage is shielded from each other is reduced; after the vibration of the preset time, the vibration operation is suspended, the camera right above the vibration chassis is used for shooting the garbage on the vibration chassis, and the monitoring method for the recyclable garbage is executed, so that the type of each garbage on the vibration chassis is identified.
The third area is a recycling area, at least one recycling space is arranged in the classification area, a mechanical arm is arranged between the second area and the third area and used for grabbing and transferring the target objects of the specified types on the vibration chassis into the recycling space, for example, most of the garbage on the vibration chassis is of an unrecoverable type, when the garbage of the recoverable type is identified to be mixed in the unrecoverable garbage, the recoverable garbage is transferred into the recycling space, the time for transporting the garbage by the transportation equipment is fully utilized to continuously identify and classify the garbage on the vibration chassis, only the garbage of the same type is reserved on the vibration chassis, and after the garbage classification and recycling steps are completed, the garbage of the same type is discharged from the discharge port to be uniformly treated, so that manual classification operation is reduced, and efficiency is improved.
EXAMPLE III
The present embodiment provides a storage medium, on which a computer program is stored, and when the computer program is executed, the method for supervising recyclable garbage according to the first embodiment is implemented.
The storage medium in this embodiment and the method in the foregoing embodiment are based on two aspects of the same inventive concept, and the method implementation process has been described in detail in the foregoing, so that those skilled in the art can clearly understand the structure and implementation process of the storage medium in this embodiment according to the foregoing description, and for the sake of brevity of the description, details are not repeated here.
The above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (10)
1. A method for supervising recyclable waste, comprising:
receiving image information, and segmenting the image to obtain a plurality of target objects;
if the exposure area of any target object is judged to be within the preset range, acquiring the characteristic information of the target object, and importing the characteristic information into a preset model to acquire the type of the target object;
and recovering the target objects of the specified type according to the requirements and monitoring the recovery and classification processes of the target objects in real time.
2. The method for supervising recoverable garbage according to claim 1, wherein the image information is obtained by:
the designated area is continuously photographed at preset time intervals to obtain a plurality of photographed images, and the plurality of photographed images are partially replaced to obtain image information.
3. The method for supervising recoverable refuse of claim 2, wherein the method for locally replacing the plurality of images comprises:
identifying all the target objects in all the shot images, and connecting at least three same target objects in all the shot images in pairs;
adjusting angles and/or positions of all shot images to enable areas obtained by connection in all the shot images to coincide;
and comparing the resolution of the target object at the same position in the shot images after the angles are adjusted, and replacing the target object with the target object image at the same position and with the resolution higher than the preset value in other shot images on the basis of any shot image if the resolution of any target object in the shot images is lower than the preset value, so as to obtain a clear shot image.
4. The method of claim 1, wherein if the exposure area of any one object is smaller than the minimum value of the predetermined range, the object is tracked and identified until the exposure area of the acquired object reaches the predetermined range again.
5. The method for supervising recoverable refuse according to claim 1, wherein if it is determined that the exposed area of any one of the objects is larger than the maximum value within the preset range, the type of the object is directly obtained through image recognition processing, and the object is subjected to corresponding type recovery processing.
6. The method for supervising recoverable garbage according to claim 1, wherein the characteristic information is one or more of a text, a pattern, an outline, a color and a material of the target.
7. The method of claim 1, wherein the predetermined model is a neural network model obtained by training the characteristic information as a neural network training sample.
8. The method for supervising recoverable garbage according to claim 1, wherein when monitoring the target object, if the target object is recovered to the recovery area with the wrong garbage type by monitoring, an alarm prompt is initiated according to the image information, the characteristic information, the type information, the correct recovery position and the current recovery position of the target object.
9. A transportation facility for recyclable waste, comprising a transportation entity and a recycling entity for performing the method of supervising recyclable waste as claimed in any one of claims 1 to 8.
10. A storage medium having stored thereon a computer program which, when executed, implements a method of administering recyclable waste as described in any one of claims 1 to 8.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110949535.3A CN113850124A (en) | 2021-08-18 | 2021-08-18 | Recoverable garbage supervision method, transportation equipment and storage medium |
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| CN202110949535.3A CN113850124A (en) | 2021-08-18 | 2021-08-18 | Recoverable garbage supervision method, transportation equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114275416A (en) * | 2022-01-19 | 2022-04-05 | 平安国际智慧城市科技股份有限公司 | Kitchen waste classification method, device, equipment and medium based on image recognition |
| CN116142658A (en) * | 2023-03-31 | 2023-05-23 | 成都鸿翔环卫服务有限公司 | Intelligent garbage classification system |
-
2021
- 2021-08-18 CN CN202110949535.3A patent/CN113850124A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114275416A (en) * | 2022-01-19 | 2022-04-05 | 平安国际智慧城市科技股份有限公司 | Kitchen waste classification method, device, equipment and medium based on image recognition |
| CN116142658A (en) * | 2023-03-31 | 2023-05-23 | 成都鸿翔环卫服务有限公司 | Intelligent garbage classification system |
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