Method for segmenting particles, electronic device, storage medium, and computer program product

Abstract

A method for segmenting particles, relating to the field of solid waste recovery. The method comprises: randomly collecting (101) a group of particles on a vibration platform; performing vibration (102) at a preset first vibration intensity by means of the vibration platform, so as to reduce the overlap between the group of particles; performing at least one instance of vibration (103) at a preset second vibration intensity by means of the vibration platform, so as to limit the movement of the group of particles within a specified range; triggering (104) a camera to capture an image corresponding to the particles after vibrations, so as to obtain a first image; and segmenting (105) all the particles in the first image. Further disclosed are an electronic device, a storage medium, and a computer program product.

Description

Method for segmenting particles, electronic device, storage medium and computer program product Technical Field

[0001] The embodiments of the present application mainly relate to the field of solid waste recycling, and in particular to a method for segmenting particles, an electronic device, a storage medium, and a computer program product. Background Art

[0002] The solid waste recycling industry currently lags behind in automation and digitization, resulting in low efficiency. Products on the market are often designed and manufactured with diverse material mixes. While this meets the diverse functional needs of the products, it also presents challenges for recycling. Because the products contain a variety of valuable materials, the recycling process inevitably requires two key steps: crushing and sorting to ensure the effective separation of the different material components.

[0003] However, these steps currently rely heavily on the naked eye and experience of industry experts. This method is not only inefficient but also difficult to guarantee accuracy, often resulting in the waste of valuable materials. Therefore, improving the automation and digitalization level of the solid waste recycling industry to achieve more accurate and efficient material sorting has become an urgent issue that needs to be addressed.

[0004] Summary of the Invention

[0005] The embodiments of the present application provide a method for segmenting particles, an electronic device, a storage medium, and a program product. Through the embodiments of the present application, different particles can be segmented quickly and accurately.

[0006] In a first aspect, a method for segmenting particles is provided, comprising: randomly collecting a group of particles onto a vibration platform; vibrating the vibration platform at a preset first vibration intensity to reduce overlap between the group of particles; vibrating the vibration platform at least once at a preset second vibration intensity to limit the movement of the group of particles to a specified range; triggering a camera to acquire an image corresponding to the vibrated particles to obtain a first image; and segmenting all particles in the first image.

[0007] In a second aspect, an electronic device is provided, comprising: at least one memory configured to store computer-readable code; and at least one processor configured to call the computer-readable code and execute each step of the method provided in the first aspect.

[0008] According to a third aspect, a computer-readable medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor, the processor executes the steps of the method provided in the first aspect.

[0009] In a fourth aspect, a computer program product is provided, which is tangibly stored on a computer-readable medium and includes computer-executable instructions, which, when executed, cause at least one processor to perform the steps of the method provided in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The following figures are intended only to illustrate and explain the embodiments of the present application and are not intended to limit the scope of the embodiments of the present application.

[0011] FIG1 is a schematic diagram of a method for segmenting particles according to an embodiment of the present application;

[0012] FIG2 is a schematic diagram of an electronic device according to an embodiment of the present application.

[0013] DESCRIPTION OF REFERENCE NUMERALS 100 : Method for segmenting particles 101 - 105 : Method steps 200 : Electronic device 201 : Processor 202 : Communication interface 203 : Memory 204 : Communication bus 205 : Program DETAILED DESCRIPTION

[0014] The subject matter described herein will now be discussed with reference to example embodiments. It should be understood that discussing these embodiments is merely to enable those skilled in the art to better understand and implement the subject matter described herein, and is not intended to limit the scope of protection, applicability, or examples set forth in the claims. The functions and arrangements of the elements discussed may be changed without departing from the scope of protection of the embodiments of the present application. Various examples may omit, replace, or add various processes or components as needed. For example, the described method may be performed in an order different from the described order, and various steps may be added, omitted, or combined. In addition, the features described relative to some examples may also be combined in other examples.

[0015] As used herein, the term "including" and its variations are open terms meaning "including but not limited to". The term "based on" means "based at least in part on". The terms "one embodiment" and "an embodiment" mean "at least one embodiment". The term "another embodiment" means "at least one other embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other definitions may be included below, whether explicit or implicit. Unless the context clearly indicates otherwise, the definition of a term is consistent throughout the specification.

[0016] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0017] FIG1 is a schematic diagram of a method for segmenting particles according to an embodiment of the present application. As shown in FIG1 , the method 100 for segmenting particles includes:

[0018] Step 101, randomly collecting a group of particles onto a vibration platform;

[0019] Specifically, random collection is performed through a sampling mechanism, and random particle samples are transported to a vibration platform, and the vibration platform can select a flexible vibration plate to ensure that the particles do not fly out of the vibration plate.

[0020] Step 102: Vibrate the vibration platform at a preset first vibration intensity to reduce overlap between the group of particles.

[0021] Preferably, the first vibration intensity should be selected according to the particle size or mass, and ensure that the particles are evenly dispersed on a plane after vibration, thereby providing a better observation view.

[0022] Step 103 : Vibrate the vibration platform at least once at a preset second vibration intensity to limit the movement of the group of particles within a specified range.

[0023] Alternatively, the specified range refers to a small range. For example, in a sample of particles of approximately 1 mm, the movement distance of most particles is limited to 1 mm. However, such low-energy vibrations may occasionally cause new particle overlap. To address this problem, the low-energy vibrations can be repeated multiple times for redistribution.

[0024] Step 104: triggering a camera to acquire an image corresponding to the vibrated particles to obtain a first image;

[0025] Preferably, a high-resolution microscope camera is used to obtain detailed images of all particle samples in the vibrating platform to ensure imaging clarity.

[0026] Optionally, the vibration platform is vibrated at least once at a preset third vibration intensity, and a camera is triggered to capture an image corresponding to the vibrated particles to obtain a second image. All particles in the first image and / or the second image are identified and segmented. Preferably, the third vibration intensity is selected based on the particle size or mass and is slightly higher than the second vibration intensity, so that all particles on the vibration platform can vibrate and move, and the movement is limited to a specified range. This specified range is larger than the specified range corresponding to the second vibration. For example, in a particle sample of approximately 1 mm, the movement distance of all particles is limited to within 2 mm.

[0027] Step 105: Segment all particles in the first image.

[0028] In one embodiment, each of all particles is segmented from the first image, and then all the segmented images are merged into a structured format file.

[0029] Specifically, the segmentation method may include preprocessing the first image to distinguish particles from the background in the first image, generating a third image that retains only the particles. A deep learning-based detection and segmentation algorithm is then used to segment the particles from the third image, and output attributes corresponding to the particles. These attributes include ID, color, pixel area, outline information, and masks, which can be used for further analysis, such as the distribution of various characteristics of the particle sample batch (e.g., size, type distribution, etc.).

[0030] In one embodiment, after outputting the properties corresponding to the particles, the present application embodiment calculates and outputs at least one of the following data information:

[0031] The total particle size distribution curve, where the particle diameter is inferred from the corresponding pixel area;

[0032] The distribution curve of each color is based on the color corresponding to each particle;

[0033] The distribution curve for each material, where the material type is determined based on the color information corresponding to different particles, such as graphite particles are black, copper particles are brown, aluminum particles are silver, etc.

[0034] The proportion of each material in the total particles, based on pixel area.

[0035] In addition, the specific preprocessing methods include: first, using a blur detection algorithm to discard or correct unfocused images; second, using a binary threshold algorithm to distinguish particles from the background; third, applying shadow removal to reduce image noise; finally, extracting the main color and background color, and using the background difference method to remove the background color, thereby obtaining a third image that only retains the particles.

[0036] In one embodiment, after the particles in the third image are segmented out from the third image by a deep learning-based detection and segmentation algorithm, instance segmentation may be performed on the particles in the third image by a contour detection method to further ensure that more particles are segmented.

[0037] The embodiments of the present application provide an automated, online method for analyzing particle size, enabling accurate detection of different particles, even irregular small particles and overlapping particles. This improves the purity of the sorted material and the overall efficiency of the recycling process. From a macroscopic perspective, this can promote the reduction of material waste and the sustainable development of the industry. The embodiments of the present application can provide online particle analysis with scalability, allowing for multiple adjustments and optimizations of the crushing and segmentation processes.

[0038] FIG2 is a schematic diagram of an electronic device according to an embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the electronic device. As shown in FIG2 , the electronic device 200 may include: a processor 201, a communications interface 202, a memory 203, and a communication bus 204. Among them:

[0039] The processor 201 , the communication interface 202 , and the memory 203 communicate with each other via the communication bus 204 .

[0040] The communication interface 202 is used to communicate with other electronic devices or servers.

[0041] The processor 201 is configured to execute the program 202 , and specifically may execute the relevant steps in any one of the aforementioned method embodiments.

[0042] Specifically, the program 205 may include program codes, which include computer operation instructions.

[0043] The processor 201 may be a CPU, an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs, or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0044] The memory 203 is used to store the program 203. The memory 203 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0045] The program 205 can be specifically used to enable the processor 201 to execute any one of the multiple method embodiments in the aforementioned embodiments.

[0046] The specific implementation of each step in procedure 205 can be found in the corresponding descriptions of the corresponding steps and units in the aforementioned embodiment of the method for particle segmentation, and will not be repeated here. Those skilled in the art will clearly understand that for ease and brevity of description, the specific operating processes of the above-described devices and modules can be referenced to the corresponding process descriptions in the aforementioned method embodiment, and will not be repeated here.

[0047] The present application also provides a computer-readable storage medium storing instructions for causing a machine to perform any of the multiple method embodiments described herein. Specifically, a system or device equipped with a storage medium can be provided, wherein the storage medium stores software program code that implements the functions of any of the above-described embodiments, and a computer (or CPU or MPU) of the system or device can read and execute the program code stored in the storage medium.

[0048] In this case, the program code read from the storage medium itself can realize the function of any one of the above embodiments, so the program code and the storage medium storing the program code constitute part of this application.

[0049] Examples of storage media for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, the program code can be downloaded from a server computer via a communication network.

[0050] An embodiment of the present application also provides a computer program product, including computer instructions, which instruct a computing device to perform any corresponding operation in the above-mentioned multiple method embodiments.

[0051] It should be pointed out that, according to the needs of implementation, the various components / steps described in the embodiments of the present application can be split into more components / steps, or two or more components / steps or partial operations of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of the present application.

[0052] The above-mentioned method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as software or computer code that can be stored in a recording medium (such as CD ROM, RAM, floppy disk, hard disk or magneto-optical disk), or can be implemented as computer code that is originally stored in a remote recording medium or a non-temporary machine-readable medium downloaded via a network and will be stored in a local recording medium, so that the method described herein can be stored in such software processing on a recording medium using a general-purpose computer, a special-purpose processor or programmable or special-purpose hardware (such as ASIC or FPGA). It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code, and when the software or computer code is accessed and executed by a computer, a processor or hardware, the method described herein is implemented. In addition, when a general-purpose computer accesses the code for implementing the method shown here, the execution of the code converts the general-purpose computer into a special-purpose computer for executing the method shown here.

[0053] It should be noted that not all steps and modules in the above processes and system structure diagrams are required. Certain steps or modules may be omitted based on actual needs. The execution order of the steps is not fixed and may be adjusted as needed. The system structure described in the above embodiments may be a physical structure or a logical structure. That is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or may be implemented by certain components in multiple independent devices.

[0054] In the above embodiments, the hardware module can be implemented mechanically or electrically. For example, a hardware module can include a permanent dedicated circuit or logic (such as a dedicated processor, FPGA or ASIC) to complete the corresponding operation. The hardware module can also include programmable logic or circuits (such as a general-purpose processor or other programmable processors), which can be temporarily set by software to complete the corresponding operation. The specific implementation method (mechanical method, or dedicated permanent circuit, or temporarily set circuit) can be determined based on cost and time considerations.

[0055] The present invention has been shown and described in detail above through the accompanying drawings and preferred embodiments. However, the present invention is not limited to these disclosed embodiments. Based on the above multiple embodiments, those skilled in the art can know that the code review methods in the above different embodiments can be combined to obtain more embodiments of the present invention, and these embodiments are also within the scope of protection of the present invention.

[0056] Nouns and pronouns referring to persons in this patent application are not limited to a specific gender.

Claims

1. A method for segmenting particles, comprising: - Randomly collect (101) a group of particles onto a vibration platform; - vibrating (102) the vibration platform at a predetermined first vibration intensity to reduce overlap between the groups of particles; - performing at least one vibration (103) at a preset second vibration intensity by the vibration platform to limit the movement of the group of particles to a specified range; - triggering (104) a camera to acquire an image corresponding to the vibrated particles to obtain a first image; - Segmenting (105) all particles in said first image.

2. The method according to claim 1, wherein After triggering (104) the camera to acquire an image of the particles after vibration and obtaining a first image, the method further comprises: - vibrating the vibration platform at least once at a preset third vibration intensity, and triggering the camera to capture an image corresponding to the vibrated particles to obtain a second image; - Identify and segment all particles in the first image and / or the second image.

3. The method according to claim 1, wherein - said segmenting (105) of all particles in said first image comprising: - segmenting each of the particles from the first image; - After said segmenting (105) of all particles in said first image, said method further comprises: -Merge all segmented images into a structured format file.

4. The method according to claim 1 or 3, wherein Segmenting each particle from the first image includes: - preprocessing the first image to distinguish particles from background in the first image, thereby obtaining a third image retaining only particles; -Segmenting the particles in the third image from the third image using a detection and segmentation algorithm based on deep learning, and outputting attributes corresponding to the particles.

5. The method according to claim 4, wherein After the particles in the third image are segmented from the third image using the deep learning-based detection and segmentation algorithm, the method includes: - Perform instance segmentation on the particles in the third image by using a contour detection method to further ensure that more particles are segmented.

6. An electronic device (200), comprising: A processor (201), a communication interface (202), a memory (203) and a communication bus (204), wherein the processor (201), the memory (203) and the communication interface (202) communicate with each other via the communication bus (204); The memory (203) is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the particle segmentation method according to any one of claims 1 to 5.

7. A computer storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for segmenting particles according to any one of claims 1 to 5 is implemented.

8. A computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions which, when executed, cause at least one processor to perform the method for segmenting particles according to any one of claims 1 to 5.

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