CN112918956A - Garbage classification system based on image recognition technology - Google Patents
Garbage classification system based on image recognition technology Download PDFInfo
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- CN112918956A CN112918956A CN202110193321.8A CN202110193321A CN112918956A CN 112918956 A CN112918956 A CN 112918956A CN 202110193321 A CN202110193321 A CN 202110193321A CN 112918956 A CN112918956 A CN 112918956A
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- 239000010813 municipal solid waste Substances 0.000 title claims abstract description 85
- 238000005516 engineering process Methods 0.000 title claims abstract description 13
- 238000001514 detection method Methods 0.000 claims abstract description 19
- 238000000605 extraction Methods 0.000 claims description 11
- 238000005286 illumination Methods 0.000 claims description 6
- 230000004913 activation Effects 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 3
- 238000000034 method Methods 0.000 abstract description 3
- 239000002699 waste material Substances 0.000 description 7
- 238000003708 edge detection Methods 0.000 description 4
- 230000002708 enhancing effect Effects 0.000 description 3
- 230000004075 alteration Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 239000002920 hazardous waste Substances 0.000 description 1
- 238000010169 landfilling Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 239000010819 recyclable waste Substances 0.000 description 1
- 238000004064 recycling Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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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
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/14—Other constructional features; Accessories
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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
- B65F1/00—Refuse receptacles; Accessories therefor
- B65F1/14—Other constructional features; Accessories
- B65F1/16—Lids or covers
- B65F1/1623—Lids or covers with means for assisting the opening or closing thereof, e.g. springs
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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
- B65F2210/00—Equipment of refuse receptacles
- B65F2210/138—Identification means
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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
- B65F2210/00—Equipment of refuse receptacles
- B65F2210/176—Sorting means
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Abstract
The invention provides a garbage classification system based on an image recognition technology, which comprises a garbage can, a detection module, a recognition module and a control module, wherein the detection module and the recognition module are arranged in front of the garbage can; the garbage can comprises a can body and a can cover, the can cover is arranged above the can body, and the can body is used for storing household garbage; the detection module is used for detecting whether a person stays in front of the garbage can or not and starting the identification module when the person stays in front of the garbage can; the identification module is used for acquiring an image of the garbage to be classified and judging the classification type of the garbage to be classified according to the image; the control module is used for opening the garbage can cover of the garbage can corresponding to the classification type. Through the image recognition mode, people can conveniently classify the garbage, so that people can unnecessarily remember all garbage types. The garbage classification method has a good auxiliary effect on the crowds such as the old and the children who are inconvenient to remember too many garbage classification types.
Description
Technical Field
The invention relates to the field of garbage classification, in particular to a garbage classification system based on an image recognition technology.
Background
Human production activities generate daily large quantities of waste, which is typically either directly landfilled or used as a fuel for thermal power generation. However, the waste contains a large amount of recyclable materials, such as metal, plastic, etc. Direct incineration or land-filling undoubtedly wastes these resources, and therefore, the state has recently vigorously advanced the classification of garbage. However, due to the plethora of types of waste, it is not easy for people to remember the specific recycling types for all waste.
Disclosure of Invention
In view of the above problems, the present invention provides a garbage classification system based on image recognition technology, which comprises a garbage can, a detection module arranged in front of the garbage can, a recognition module and a control module arranged on the garbage can;
the garbage can comprises a can body and a can cover, the can cover is arranged above the can body, and the can body is used for storing household garbage;
the detection module is used for monitoring whether a person stays in front of the garbage can or not and awakening the identification module when the person stays;
the identification module is used for acquiring an image of the garbage to be classified, judging the type of the garbage to be classified according to the image and sending the type to the control module;
the control module is used for controlling the opening of the barrel cover of the garbage barrel corresponding to the type.
Compared with the prior art, the invention has the advantages that:
through the image recognition mode, people can conveniently classify the garbage, so that people can unnecessarily remember all garbage types. The garbage classification method has a good auxiliary effect on the crowds such as the old and the children who are inconvenient to remember too many garbage classification types.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of a garbage classification system based on an image recognition technology according to the present invention.
Fig. 2 is a front view of an exemplary embodiment of a trash can of a trash classification system based on image recognition technology.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in the embodiment of fig. 1, the present invention provides a garbage classification system based on image recognition technology, which includes a garbage can, a detection module, a recognition module and a control module, wherein the detection module, the recognition module and the control module are arranged in front of the garbage can;
as shown in fig. 2, the garbage can comprises a can body 2 and a can cover 1, the can cover 1 is arranged above the can body 2, and the can body 2 is used for storing domestic garbage;
the detection module is used for detecting whether a person stays in front of the garbage can or not and starting the identification module when the person stays in front of the garbage can;
the recognition module is used for acquiring an image of the garbage to be classified, judging the classification type of the garbage to be classified according to the image and sending the classification type to the control module;
the control module is used for opening the garbage can cover 1 of the garbage can corresponding to the classification type.
Preferably, the barrel 2 and the barrel lid 1 are rotatably connected.
Preferably, the detection module comprises a detection unit and a starting unit;
the detection unit is used for detecting whether a person stays within a preset distance in front of the garbage can or not through the human body proximity sensor;
the starting unit is used for starting the identification module when the detection unit detects that someone stays in a preset distance in front of the garbage can.
Preferably, the identification module comprises an image acquisition unit, a feature extraction unit and an image identification unit;
the image acquisition unit is used for acquiring an image of the garbage to be classified and transmitting the image to the feature extraction unit;
the characteristic extraction unit is used for carrying out image recognition on the image of the garbage to be classified, acquiring characteristic information of the image of the garbage to be classified and sending the characteristic information to the image recognition unit;
the image identification unit is used for judging the classification type of the garbage to be classified based on the characteristic information.
Preferably, the image acquisition unit comprises a shooting subunit, a lighting subunit and a control subunit;
the shooting subunit comprises a camera, and the camera is used for acquiring the image of the garbage to be classified;
the control subunit is used for judging the current illumination intensity and controlling the light subunit to be started when the illumination intensity is smaller than a preset illumination intensity threshold;
the light photon unit is used for providing light for assisting shooting for the shooting subunit.
Preferably, the classification type includes recyclable waste, in-waste, hazardous waste, other waste.
Preferably, the performing image recognition on the image to obtain feature information of the image includes:
carrying out graying processing on the image of the garbage to be classified to obtain a first processed image;
carrying out noise reduction processing on the first processed image to obtain a second processed image;
performing enhancement processing on the second processed image to obtain a third processed image;
and performing feature extraction on the third processed image to acquire feature information contained in the third processed image.
Preferably, the graying the image of the garbage to be classified to obtain a first processed image includes:
carrying out graying processing on the image of the garbage to be classified by using the following formula to obtain a first processed image:
firp(a)＝b1R(a)+b2G(a)+b3B(a)
wherein, the first image represents the gray value of the pixel point a, R (a), G (a), B (a) represent the red component, green component and blue component of the pixel point a in the RGB color model, respectively, and b represents the gray value of the pixel point a in the first image1、b2、b3Representing a weight parameter;
and performing the graying processing on all pixel points in the image of the garbage to be classified to obtain a first processed image.
Preferably, b1、b2、b3The values of (A) are respectively 0.298, 0.577 and 0.115.
Preferably, the performing noise reduction processing on the first processed image to obtain a second processed image includes:
decomposing the first image by using a non-downsampling contourlet algorithm to obtain a high-pass image and a low-pass image;
and processing the high-pass image to obtain a processed high-pass image as follows:
in the formula, (x, y) represents the coordinates of pixel points in the high-pass image before processing, U (x, y) represents the set of coordinates of pixel points in the neighborhood with the size of k × k of the pixel points with the coordinates (x, y), bc represents the variance of the distance between all pixel points corresponding to the element in U (x, y) and the pixel points with the coordinates (x, y), dt (x, y) represents the gradient amplitude of the pixel points with the coordinates (x, y), dt (i, j) represents the gradient amplitude of the pixel points with the coordinates (i, j), bd represents the standard deviation of the gradient amplitudes of all pixel points corresponding to the element in U (x, y), and gs (i, j) represents the pixel value of the pixel points with the coordinates (i, j) in the high-pass image before processing; ags (x, y) represents the pixel value of the pixel point with coordinates (x, y) after processing;
and reconstructing the low-pass image and the processed high-pass image to obtain a second image.
When the noise reduction processing is carried out, non-downsampling contourlet decomposition is carried out firstly, then the obtained high-pass image is processed to obtain a processing result, then reconstruction is carried out to obtain a second processing image, and compared with a traditional noise reduction mode, such as Gaussian noise reduction, the method and the device can better keep more detailed information.
Preferably, the enhancing processing is performed on the second processed image to obtain a third processed image, and the enhancing processing includes:
performing edge detection on the second image to obtain edge pixel points;
for the edge pixel point, the following formula is used for enhancing the edge pixel point:
asep(c)＝d×sep(c)+(1-d)sepc(c)
in the formula, asep (c) represents the pixel value of the pixel point c in the third processed image after the enhancement processing, sep (c) represents the pixel value of the pixel point c after the gray level adjustment is performed on the second processed image, sepc (c) represents the pixel value of the pixel point c in the image obtained after the edge detection is performed on the second processed image, d represents the weight parameter,
wherein dp (c) represents the pixel value of the pixel c in the second image, ave (c) represents the average value of the pixel values of the pixels in the neighborhood of t × t of the pixel c in the second image; mid (c) represents the median of the pixel values of all the pixels in the neighborhood.
After edge detection, most of edge pixel points can be detected, the obtained image sepc after gray level adjustment can enable the pixel value distribution of the pixel points to be more uniform, subsequent feature recognition is facilitated, the situation that the detail information of a low-brightness area cannot be correctly recognized is avoided, therefore, the result of edge detection is used on the sepc for enhancement processing, a third processed image is obtained in an image fusion mode, the edge details in the third processed image can be obviously improved compared with the second processed image, and more detail information can be provided for subsequent feature extraction.
Preferably, the feature extraction of the third processed image to obtain feature information included in the third processed image includes:
and performing feature extraction on the third processed image by using an LBP feature extraction algorithm to acquire feature information contained in the third processed image.
Preferably, the determining the classification type of the garbage to be classified based on the feature information includes:
matching the characteristic information with characteristic information of various types of garbage prestored in a database so as to determine the types of the garbage to be classified;
and judging the classification type of the garbage to be classified according to the category.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (5)
1. A garbage classification system based on an image recognition technology is characterized by comprising a garbage can, a detection module, a recognition module and a control module, wherein the detection module and the recognition module are arranged in front of the garbage can;
the garbage can comprises a can body and a can cover, the can cover is arranged above the can body, and the can body is used for storing household garbage;
the detection module is used for detecting whether a person stays in front of the garbage can or not and starting the identification module when the person stays in front of the garbage can;
the recognition module is used for acquiring an image of the garbage to be classified, judging the classification type of the garbage to be classified according to the image and sending the classification type to the control module;
the control module is used for opening the garbage can cover of the garbage can corresponding to the classification type.
2. The image recognition technology-based trash classification system of claim 1, wherein the bin body and the bin cover are rotatably connected.
3. The image recognition technology-based trash classification system of claim 1, wherein the detection module comprises a detection unit and an activation unit;
the detection unit is used for detecting whether a person stays within a preset distance in front of the garbage can or not through the human body proximity sensor;
the starting unit is used for starting the identification module when the detection unit detects that someone stays in a preset distance in front of the garbage can.
4. The image recognition technology-based garbage classification system according to claim 1, wherein the recognition module comprises an image acquisition unit, a feature extraction unit and an image recognition unit;
the image acquisition unit is used for acquiring an image of the garbage to be classified and transmitting the image to the feature extraction unit;
the characteristic extraction unit is used for carrying out image recognition on the image of the garbage to be classified, acquiring characteristic information of the image of the garbage to be classified and sending the characteristic information to the image recognition unit;
the image identification unit is used for judging the classification type of the garbage to be classified based on the characteristic information.
5. The image recognition technology-based trash classification system of claim 1, wherein the image acquisition unit comprises a shooting subunit, a lighting subunit and a control subunit;
the shooting subunit comprises a camera, and the camera is used for acquiring the image of the garbage to be classified;
the control subunit is used for judging the current illumination intensity and controlling the light subunit to be started when the illumination intensity is smaller than a preset illumination intensity threshold;
the light photon unit is used for providing light for assisting shooting for the shooting subunit.
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Cited By (1)
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Application publication date: 20210608 |