CN115026015A - Ground rubbish detection system based on image processing - Google Patents
Ground rubbish detection system based on image processing Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C2501/00—Sorting according to a characteristic or feature of the articles or material to be sorted
- B07C2501/0054—Sorting of waste or refuse
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- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
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Abstract
The invention discloses a ground garbage detection system based on image processing, which comprises an image acquisition module, a main control module and an execution module, and specifically comprises the following steps: (1) obtaining a ground garbage image through an industrial camera and a lens of an image acquisition module; (2) after the main control module receives the image input by the image acquisition module, performing target spam image enhancement, target spam image recognition and target spam image posture detection on the image, and sending an instruction to the execution module according to a detection result; (3) after the execution module receives an instruction sent by the main control module, the garbage is picked up and placed to a corresponding garbage can through the manipulator. The garbage sorting machine has high automation degree, high sorting efficiency and low error rate compared with manual garbage sorting, can save a large amount of manpower, reduce the garbage cleaning cost and improve the quality of life of people and urban environment.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a ground garbage detection system based on image processing.
Background
In recent years, with the increase of population density and the complication of urban functions, the number of large public places such as airports and the like is increasing, and the work pressure of garbage sorting is huge. At present, the automation of ground garbage sorting is not well realized, and the garbage sorting work still needs a large amount of manpower. Although the garbage cleaning robot sold on the market at present has a simple path planning function, the operation process of the garbage cleaning robot is mostly full-coverage garbage sorting, the blindness is high, and the garbage cleaning robot is always in a work execution state no matter whether garbage exists in an operation area or not. In addition, the robot does not have the automatic garbage detection and classification capability, and in short, the operation efficiency and the quality are low. In order to save energy consumption and improve the efficiency and quality of garbage sorting, the garbage sorting equipment needs to be equipped with a ground garbage detection system based on image processing, so that the garbage sorting equipment can distinguish garbage types independently before operation. Therefore, the development of the ground garbage detection system based on image processing has important practical significance.
Patent publications and literature data at the present stage show: 1) the patent (CN201911045869.7) realizes classification of garbage by shooting garbage to be discarded by a user and performing image recognition to determine the type of garbage, but in the process of shooting garbage thrown by the user, the garbage thrown by the user is easily affected by the hand speed of the user, so that the shot photos are blurred, and thus in the subsequent image processing, an erroneous result or a result cannot be obtained, and finally garbage classification fails; 2) in the patent (CN201911188747.3), solid-liquid separation is performed on garbage to be classified entering a garbage treatment plant to obtain solid garbage, and 2D images, 3D models and surface physicochemical attribute information of the solid garbage are respectively detected for garbage classification, but the method is suitable for classifying mixed garbage, and cannot perform sorting in time when garbage is collected, which causes waste of a large amount of manpower and material resources; 3) patent (CN201911047467.0) lets the user classify to rubbish through the rubbish that provides different characteristics at random, provides the characteristic information of different rubbish simultaneously to the user and supplies the user to study, through this operation of going on repeatedly for the user has clear understanding to the classification of rubbish, and this method needs the manual work to interfere and sorts rubbish, and degree of automation is low, consumes the manpower more.
In summary, although the existing research results and methods can realize garbage sorting to a certain extent, there are many problems such as too much manual guidance and high garbage disposal cost, so it is necessary to provide a ground garbage detection system based on image processing.
Disclosure of Invention
The invention aims to solve the problems and provides a ground garbage detection system based on image processing, which obtains a ground garbage image through an industrial camera and a lens of an image acquisition module, performs target garbage image enhancement, target garbage image recognition and target garbage image posture detection on the image after a main control module receives the image input by the image acquisition module, sends an instruction to an execution module according to a detection result, and picks up garbage and places the garbage at a corresponding garbage can through a manipulator after the execution module receives the instruction sent by the main control module. Compared with manual garbage collection and sorting, the garbage sorting machine has the advantages of high automation degree and sorting efficiency, and can save a large amount of manpower, reduce the garbage cleaning cost and improve the quality of life of people and urban environment.
The invention realizes the purpose through the following technical scheme:
the utility model provides a ground rubbish detecting system based on image processing which characterized in that, this ground rubbish detecting system includes image acquisition module, main control module, image enhancement module, image recognition module, image gesture detection module and execution module, specifically includes following step:
the method comprises the following steps that firstly, a rubbish image on the ground is obtained through shooting of an industrial camera and a lens in an image acquisition module of a ground rubbish detection system;
after the main control module receives the image input by the image acquisition module, firstly, the image is enhanced by the image enhancement module, so that the accuracy rate of target rubbish image identification is improved; then the image recognition module extracts image features through a set algorithm based on the image input by the image enhancement module, and then compares the image features with the images in the image library to obtain the type of the target garbage; then, the posture detection module carries out posture detection on the enhanced image to obtain the posture information of the target garbage on the ground, so that a manipulator can conveniently adjust to a proper angle and position to grab the target garbage; finally, the image posture detection module converts the detection result into an instruction and sends the instruction to the execution module;
and step three, after receiving the instruction sent by the image posture detection module, the execution module converts the instruction into an execution action of a manipulator, and picks up the garbage through the manipulator and places the garbage into garbage bins of corresponding types.
As a further improvement of the present invention, in the first step, the image acquisition module acquires an image, and since the range of taking a picture by the camera is limited, the driving trolley on which the camera and the lens are mounted needs to be stopped to a suitable position, and the driving trolley is matched with the auxiliary light source mounted on the driving trolley to acquire an image of the target garbage.
As a further improvement of the present invention, in the second step, the main control module includes, in addition to the image enhancement module, the image recognition module, the image posture detection module, and a software interface module, when debugging the detection system, the functions of the image enhancement module, the image recognition module, and the image posture detection module can be manually and respectively tested through the software interface, and simultaneously, the manipulator and the driver thereof in the execution module can be directly controlled.
As a further improvement of the invention, the execution module comprises a mechanical arm and a pneumatic mechanism, receives the instruction output by the main control module in the second step, utilizes a PLC to control, and communicates through a Modbus TCP protocol to realize the picking of the ground target garbage.
As a further improvement of the present invention, in the second step, the target garbage image is enhanced, the image is decomposed into a detail layer and a base layer, then the detail layer and the base layer are processed in parallel at the same time, a countermeasure network is generated to obtain the detail layer from which raindrops are removed, the base layer after brightness enhancement is obtained by a Retinex algorithm, and finally the processed detail layer and the base layer are synthesized to obtain the target garbage enhanced image.
As a further improvement of the present invention, in the step two, target spam image recognition is performed, since detection of spam requires real-time performance and accuracy requirement is high, so the YOLOV3 algorithm is used.
As a further improvement of the present invention, in the second step, the posture detection of the target garbage image includes extracting a target region from the target garbage image, preprocessing the garbage image, including performing gray processing, noise reduction filtering and threshold segmentation binarization processing on the target region, and finally detecting the posture of the target garbage image, including searching the outer contour of the preprocessed image, then performing ellipse fitting, determining a central axis, and finally outputting an angle, so as to complete the detection of the posture of the target garbage image.
As a further improvement of the invention, the garbage can be sorted by the three steps, and the next garbage can be continuously sorted by the system until all the garbage is sorted.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of obtaining a ground garbage image through an industrial camera and a lens of an image acquisition module, then carrying out target garbage image enhancement, target garbage image recognition and target garbage image posture detection on the image after the main control module receives the image input by the image acquisition module, sending an instruction to an execution module according to a detection result, and finally picking up garbage and placing the garbage to a corresponding garbage can through a manipulator after the execution module receives the instruction sent by the main control module. Compared with manual garbage collection and sorting, the garbage sorting machine has the advantages of high automation degree, high sorting efficiency and low error rate, can save a large amount of manpower, reduces the garbage cleaning cost, and improves the quality of life of people and urban environment.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an implementation of an image processing-based ground garbage detection system according to the present invention;
FIG. 2 is a technical architecture diagram of a ground garbage detection system based on image processing according to the present invention;
FIG. 3 is a lens parameter diagram of a ground garbage detection system based on image processing according to the present invention;
FIG. 4 is a diagram of an image enhancement process of the image processing-based ground garbage detection system according to the present invention;
FIG. 5 is a diagram illustrating the effect of image enhancement processing of a ground garbage detection system based on image processing according to the present invention;
FIG. 6 is a flow chart of image pose detection for a ground spam detection system based on image processing according to the present invention;
fig. 7 is an image posture detection effect diagram of the ground garbage detection system based on image processing according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.
(1) As shown in FIG. 3, the industrial camera in the image capture module is Haekwovis, model MV-CA003-21UCX, the lens is Kowa company, model LM3NCM, focal length is 3.5mm, target surface size is 1/2 inches, back focal length is 9.7mm, optical interface is C-Mount, weight is 75g, aperture range is F2.4-F14, object distance range is 0.1m to infinity, distortion rate is 0.4%, working temperature is-10 ℃ -45 ℃, and mechanical size is phi 45 x 38.2 mm. And after the driving trolley stops in place, the auxiliary light source is turned on, and the camera adjusts parameters such as focal length, aperture and the like to acquire images of the target garbage.
(2) As shown in fig. 2, the image of the target spam is input into the controller of the main control module, firstly, the image enhancement module performs image enhancement processing on the image of the target spam, as shown in fig. 4, the image is decomposed into a detail layer and a base layer, the detail layer is processed by generating a confrontation network to obtain the detail layer without raindrops, meanwhile, the base layer is processed by a Retinex algorithm to obtain a base layer with enhanced brightness, and finally, the base layer and the detail layer are laminated to obtain an enhanced image, as shown in fig. 5.
(3) As shown in fig. 2, based on an image database, using a YOLOV3 algorithm to perform image recognition on an image subjected to image enhancement processing, then performing image posture detection according to a flow shown in fig. 6, firstly extracting a target region of the image, mainly extracting a ROI region of the input image, then preprocessing the image, mainly performing gray processing, noise reduction filtering, threshold segmentation binarization processing, and finally performing posture detection, mainly searching an outer contour, fitting an ellipse, determining a central axis and an output angle, and finally determining the position of the output angle as (126.164), thereby completing detection of a target spam posture, wherein an effect diagram is shown in fig. 7.
(4) As shown in fig. 2, after the execution module receives an instruction sent by the target garbage attitude detection module in the main control module, the execution module processes the instruction by using a PLC, performs communication through a Modbus TCP protocol, and controls the manipulator to adjust the position of the manipulator, so as to sort the ground target garbage.
(5) The garbage can be sorted by the three steps, and the next garbage can be continuously sorted by the system until all the garbage is sorted.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the embodiments of the present invention without departing from the spirit and scope of the present invention, which is set forth in the following claims.
Claims (8)
1. The utility model provides a ground rubbish detecting system based on image processing which characterized in that, this ground rubbish detecting system includes image acquisition module, main control module, image enhancement module, image recognition module, image gesture detection module and execution module, specifically includes following step:
(1) shooting through an industrial camera and a lens in an image acquisition module of the ground garbage detection system to obtain a garbage image on the ground;
(2) after the main control module receives the image input by the image acquisition module, firstly, the image is enhanced by the image enhancement module, so that the accuracy of target junk image identification is improved; then the image recognition module extracts image features through a set algorithm based on the image input by the image enhancement module, and then compares the image features with the images in the image library to obtain the type of the target garbage; then, the posture detection module carries out posture detection on the enhanced image to obtain the posture information of the target garbage on the ground, so that a manipulator can conveniently adjust to a proper angle and position to grab the target garbage; finally, the image posture detection module converts the detection result into an instruction and sends the instruction to the execution module;
(3) after receiving the instruction sent by the image attitude detection module, the execution module converts the instruction into an execution action of the manipulator, and picks up the garbage through the manipulator and places the garbage into the garbage bin of the corresponding type.
2. The image processing-based ground garbage detection system as claimed in claim 1, wherein in the first step, the image acquisition module acquires an image, and since the range of photographing by the camera is limited, the driving trolley with the camera and the lens is required to stop to a proper position, and the driving trolley is matched with an auxiliary light source installed on the driving trolley to acquire an image of the target garbage.
3. The image processing-based ground garbage detection system of claim 1, wherein the main control module in the second step comprises a software interface module in addition to the image enhancement module, the image recognition module and the image posture detection module, and when the detection system is debugged, the functions of the image enhancement module, the image recognition module and the image posture detection module can be manually and respectively tested through the software interface, and meanwhile, the manipulator and the drive thereof in the execution module can be directly controlled.
4. The ground garbage detection system based on image processing as claimed in claim 1, wherein the execution module comprises a manipulator and a pneumatic mechanism, and the manipulator and the pneumatic mechanism are controlled by a PLC through receiving the instructions output by the two main control modules in the step two, and the picking of the target garbage on the ground is realized through communication by a Modbus TCP protocol.
5. The image processing-based ground refuse detection system according to claim 1, wherein in the second step, the target refuse image is enhanced, the image is decomposed into a detail layer and a base layer, then the detail layer and the base layer are processed simultaneously in parallel, the detail layer after the raindrop is removed is obtained by generating a countermeasure network, the base layer after the brightness enhancement is obtained by a Retinex algorithm, and finally the processed detail layer and the base layer are synthesized to obtain the target refuse enhanced image.
6. The image processing-based ground spam detection system according to claim 1, wherein the target spam image identification in the second step uses the YOLOV3 algorithm because the spam detection requires real-time performance and high accuracy.
7. The image processing-based ground garbage detection system according to claim 1, wherein in the second step, the target garbage image posture detection is performed by firstly extracting a target region from the target garbage image, then preprocessing the garbage image, including performing gray processing, noise reduction filtering, threshold segmentation binarization processing on the target region, and finally detecting the target garbage posture, and includes firstly searching an outer contour of the preprocessed image, then performing ellipse fitting, determining a central axis, and finally outputting an angle, so that the target garbage posture detection is completed.
8. The image processing-based ground garbage detection system according to claim 1, wherein the garbage can be sorted by the three steps, and the sorting of the next garbage can be continued by the system until all the garbage is sorted.
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Application publication date: 20220909 |