CN113057529B - Garbage classification control system based on stair cleaning robot - Google Patents
Garbage classification control system based on stair cleaning robot Download PDFInfo
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- CN113057529B CN113057529B CN202110197537.1A CN202110197537A CN113057529B CN 113057529 B CN113057529 B CN 113057529B CN 202110197537 A CN202110197537 A CN 202110197537A CN 113057529 B CN113057529 B CN 113057529B
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/24—Floor-sweeping machines, motor-driven
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4002—Installations of electric equipment
- A47L11/4008—Arrangements of switches, indicators or the like
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G06F18/00—Pattern recognition
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- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
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Abstract
The invention discloses a garbage classification control system based on a stair cleaning robot, which relates to the technical field of garbage classification and comprises an acquisition module, a storage module and a classification module, wherein the acquisition module is used for acquiring specific images of garbage to be classified; the preprocessing module is used for extracting the characteristic part information of the specific image of the garbage to be classified and generating a standard image of the garbage to be classified; the matching module is used for extracting the standard image of the garbage to be classified, matching the standard image with a pre-established garbage model base, and outputting the initial garbage category of the garbage to be classified after matching the standard image with the garbage identification model base; and the identification module is used for determining a final garbage category corresponding to the garbage to be classified according to the initial garbage category. Compared with the mode that all the garbage is absorbed into the garbage storage box arranged in the stair cleaning robot when the garbage is cleaned by the traditional stair cleaning robot, the stair cleaning robot can identify the garbage category when the garbage is cleaned, so that the follow-up garbage treatment is facilitated.
Description
Technical Field
The invention relates to the technical field of garbage classification, in particular to a garbage classification control system based on a stair cleaning robot.
Background
The floor sweeping robot is also called an automatic cleaner, intelligent dust collection, a robot dust collector and the like, is one of intelligent household appliances, and can automatically complete floor cleaning work in a room by means of certain artificial intelligence. Generally, the floor cleaning machine adopts a brushing and vacuum mode, and firstly absorbs the impurities on the floor into the garbage storage box, so that the function of cleaning the floor is achieved. Generally, a robot that performs cleaning, dust collection and floor wiping is also collectively called a floor sweeping robot. The stair cleaning robot is developed specially for cleaning stair garbage, and can clean the garbage in the stair well in time for a householder, so that people can be effectively prevented from slipping when walking on the stairs.
And stair cleaning robot is when clearing up rubbish and is unified to be absorbed all rubbish and build in among them rubbish receiver, and does not pass through waste classification at the in-process that rubbish was accomodate, adopts same treatment mode to different rubbish, and the rubbish of different grade type is piled up together and is unfavorable for subsequent rubbish retreatment.
Disclosure of Invention
The invention aims to provide a garbage classification control system based on a stair cleaning robot, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a waste classification control system based on a stair cleaning robot is characterized by comprising:
the acquisition module is used for acquiring a specific image of the garbage to be classified;
the preprocessing module is used for extracting the characteristic part information of the specific image of the garbage to be classified and generating a standard image of the garbage to be classified;
the matching module is used for extracting the standard image of the garbage to be classified, matching the standard image with a pre-established garbage model base, and outputting the initial garbage category of the garbage to be classified after matching the standard image with the garbage identification model base;
and the identification module is used for determining a final garbage category corresponding to the garbage to be classified according to the initial garbage category.
As a further scheme of the invention: the method for forming the garbage model library comprises the following steps:
collecting specific images of different types of garbage under different states;
preprocessing the collected specific image, and generating a model image corresponding to the image after collecting characteristic part information in the image;
extracting model images of the garbage of the same type in different states and generating a garbage model sub-library;
and after extracting garbage model sub-libraries of different types of garbage, integrating to generate a garbage model library.
As a further scheme of the invention: the step of obtaining the standard image of the garbage to be classified comprises the following steps:
extracting a specific image of the garbage to be classified;
and adjusting the specific image of the garbage to be classified to enable the garbage to be classified to be positioned in the center of the image and to be the same as the size of the model image recorded in the garbage model library in size.
And generating the standard image of the garbage to be classified after adjusting the brightness, the color contrast and the color saturation of the image.
As a further scheme of the invention: the matching module is specifically configured to:
extracting the standard image of the garbage to be classified;
comparing the standard image with a garbage model library, and extracting a model image which is similar to the standard image to a certain proportion from the garbage model library;
judging the initial garbage category of the garbage to be classified according to the category of the garbage model sub-library to which the extracted model image belongs;
as a further scheme of the invention: and when the extracted model images belong to different garbage model sub-libraries, selecting the garbage model sub-library comprising more model images as the initial garbage category of the garbage to be classified.
As a further scheme of the invention: the identification module is specifically configured to:
restoring all model images in the garbage model sub-library into specific images;
extracting the standard image of the garbage to be classified, comparing the standard image with the specific image, and extracting the specific image which has similarity to the standard image of the garbage to be classified to a certain proportion;
extracting specific images which are similar to the standard images of the garbage to be classified to a certain proportion, and calculating the proportion of the number of the specific images to the number of all model images in the garbage model sub-library;
and when the proportion is larger than the set threshold value, outputting the final garbage category of the garbage to be classified.
As a further scheme of the invention: and when the similarity of the standard images of the garbage to be classified is smaller than the ratio of the specific images in a certain proportion to all the model images in the garbage model sub-library, abandoning the identification, re-extracting the specific images of the garbage to be classified, and identifying and classifying the specific images.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of acquiring specific image information of garbage to be classified, preprocessing the image information to generate a standard image which accords with a standard format, matching the standard image with a model image in a garbage model library included in a system, screening out a model image which has similarity with the standard image of the garbage to be classified to a certain proportion, identifying the screened model image and the subordinate garbage model sub-library, and identifying the initial garbage type of the garbage to be classified according to the garbage model sub-library occupying the largest proportion; then further confirm through carrying out the matching once more with the original image of the model image in this rubbish model sublibrary for stair cleaning robot can classify the rubbish classification when clearing up rubbish, thereby adopts different clearance modes, and is more scientific and efficient.
Drawings
Fig. 1 is a schematic diagram of the general structure of a garbage classification control system based on a stair cleaning robot.
Fig. 2 is a schematic flow chart of generating a standard spam image to be classified.
Fig. 3 is a schematic structural diagram of a matching module.
FIG. 4 is a schematic flow chart for generating a garbage model.
FIG. 5 is a schematic structural diagram of an identification module
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that, if there is a directional indication (such as up, down, left, right, front, and back) in the embodiment of the present invention, it is only used to explain the relative position relationship between the components, the motion situation, and the like in a certain posture, and if the certain posture is changed, the directional indication is changed accordingly.
In addition, if the description of "first", "second", etc. is referred to in the present invention, it is used for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
The following detailed description of specific implementations of the present invention is provided in conjunction with specific embodiments:
as shown in fig. 1, the garbage classification control system based on the stair cleaning robot provided by the invention includes an obtaining module 100, configured to obtain a specific image of garbage to be classified; the preprocessing module 200 is configured to extract feature part information of the specific image of the garbage to be classified, and generate a standard image of the garbage to be classified; the matching module 300 is configured to extract the standard image of the garbage to be classified, match the standard image with a pre-established garbage model library, and output an initial garbage category of the garbage to be classified after matching the standard image with the garbage identification model library; and the identifying module 400 is configured to determine a final garbage category corresponding to the garbage to be classified according to the initial garbage category.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of obtaining the standard image of the garbage to be classified includes:
step S201, extracting the specific image of the garbage to be classified;
step S202, the specific image of the garbage to be classified is adjusted, so that the garbage to be classified is positioned in the center of the image and has the same size as the size of the model image recorded in the garbage model library.
Step S203, generating the standard image of the garbage to be classified after adjusting the brightness, the color contrast and the color saturation of the image.
As shown in fig. 3, as a preferred embodiment of the present invention, the matching module 300 is specifically configured to:
s301, extracting the standard image of the garbage to be classified;
s302, comparing the standard image with a garbage model library, and extracting a model image which is similar to the standard image to a certain proportion from the garbage model library;
s303, judging the initial garbage category of the garbage to be classified according to the category of the garbage model sub-library to which the extracted model image belongs.
As shown in fig. 4, as a preferred embodiment of the present invention, the method for forming the garbage model library includes the following steps:
step S3021, collecting specific images of different types of garbage in different states;
step S3022, preprocessing the collected specific image, collecting characteristic part information in the image, and generating a model image corresponding to the image;
step S3023, extracting model images of the same type of garbage in different states and generating a garbage model sub-library;
and S3024, extracting garbage model sub-libraries of different types of garbage, and integrating to generate a garbage model library.
As a preferred embodiment of the present invention, when the extracted model images belong to different garbage model sub-libraries, the garbage model sub-library including more model images is selected as the initial garbage category of the garbage to be classified.
As shown in fig. 5, as a preferred embodiment of the present invention, the identification module 400 is specifically configured to:
s401, extracting all model images in a garbage model sub-library under the initial garbage category of the garbage to be classified;
s402, restoring all model images in the garbage model sub-library into specific images;
s403, extracting the standard image of the garbage to be classified, comparing the standard image with the specific image, and extracting the specific image which has similarity to the standard image of the garbage to be classified to a certain proportion;
s404, extracting specific images which have similarity to the standard images of the garbage to be classified to a certain proportion, and calculating the proportion of the number of the specific images to the number of all model images in the garbage model sub-library;
and S405, outputting the final garbage category of the garbage to be classified when the proportion is larger than the set threshold value.
As shown in fig. 5, as a preferred embodiment of the present invention, when the similarity of the standard images of the garbage to be classified reaches a certain ratio, and the ratio of the number of the specific images in the garbage model sub-library to all the model images in the garbage model sub-library is smaller than a set threshold, the current recognition is abandoned, and the specific images of the garbage to be classified are re-extracted and are recognized and classified.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (5)
1. A waste classification control system based on a stair cleaning robot is characterized by comprising:
the acquisition module is used for acquiring a specific image of the garbage to be classified;
the preprocessing module is used for extracting the characteristic part information of the specific image of the garbage to be classified and generating a standard image of the garbage to be classified;
the matching module is used for extracting the standard image of the garbage to be classified, matching the standard image with a pre-established garbage model base, and outputting the initial garbage category of the garbage to be classified after matching the standard image with the garbage identification model base;
the identification module is used for determining a final garbage category corresponding to the garbage to be classified according to the initial garbage category;
the identification module is specifically configured to:
extracting all model images in a garbage model sub-library under the initial garbage category of the garbage to be classified;
restoring all model images in the garbage model sub-library into specific images;
extracting the standard image of the garbage to be classified, comparing the standard image with the specific image, and extracting the specific image which has similarity to the standard image of the garbage to be classified to a certain proportion;
extracting specific images which are similar to the standard images of the garbage to be classified to a certain proportion, and calculating the proportion of the number of the specific images to the number of all model images in the garbage model sub-library;
when the proportion is larger than a set threshold value, outputting the final garbage category of the garbage to be classified;
and when the similarity of the standard images of the garbage to be classified is smaller than the ratio of the specific images in a certain proportion to all the model images in the garbage model sub-library, abandoning the identification, re-extracting the specific images of the garbage to be classified, and identifying and classifying the specific images.
2. The stair cleaning robot based garbage classification control system according to claim 1, wherein the method for forming the garbage model library comprises the following steps:
collecting specific images of different types of garbage under different states;
preprocessing the collected specific image, and generating a model image corresponding to the image after collecting characteristic part information in the image;
extracting model images of the garbage of the same type in different states and generating a garbage model sub-library;
and after extracting garbage model sub-libraries of different types of garbage, integrating to generate a garbage model library.
3. The stair cleaning robot based garbage classification control system according to claim 1, wherein the step of obtaining the standard garbage image to be classified comprises:
extracting a specific image of the garbage to be classified;
adjusting the specific image of the garbage to be classified to enable the garbage to be classified to be located in the center of the image and to be the same as the size of the model image recorded in the garbage model library in size;
and generating the standard image of the garbage to be classified after adjusting the brightness, the color contrast and the color saturation of the image.
4. The stair cleaning robot-based garbage classification control system according to claim 1, wherein the matching module is specifically configured to:
extracting the standard image of the garbage to be classified;
comparing the standard image with a garbage model library, and extracting a model image which is similar to the standard image to a certain proportion from the garbage model library;
and judging the initial garbage category of the garbage to be classified according to the category of the garbage model sub-library to which the extracted model image belongs.
5. The stair cleaning robot-based garbage classification control system according to claim 4, wherein when the extracted model images belong to different garbage model sub-libraries, the garbage model sub-library comprising more model images is selected as the initial garbage category of the garbage to be classified.
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| RU2382408C2 (en) * | 2007-09-13 | 2010-02-20 | Институт прикладной физики РАН | Method and system for identifying person from facial image |
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| CN104616024B (en) * | 2015-02-13 | 2018-06-15 | 中国科学院空间科学与应用研究中心 | Polarimetric synthetic aperture radar image classification method based on random scatter similitude |
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Effective date of registration: 20230612 Address after: Room 101, Building 19, Zhizaogu, Xinxin Zhizaogu, Yunhe Suqian Port Industrial Park, Sucheng District, Suqian City, Jiangsu Province, 223800 Patentee after: JIANGSU LONGJIE AUTOMATION TECHNOLOGY Co.,Ltd. Address before: 223800 room 306, 3rd floor, science and technology complex, No. 29, Beijing East Road, Siyang County, Suqian City, Jiangsu Province Patentee before: Jiangsu klinbot Intelligent Technology Co.,Ltd. |