Processing apparatus

Abstract

To solve the problem that proper waste classification may be difficult.SOLUTION: A processing apparatus comprises: a base for placing waste to be classified; a visible light camera for capturing an image of the waste placed on the base; and a far-infrared camera for capturing an image of the waste placed on the base. A first pattern discernible with visible light and a second pattern discernible with far infrared light are formed on the surface of the base.SELECTED DRAWING: Figure 11

Description

Technical Field

[0001] The present disclosure relates to a processing device, a classification device, a classification method, and a program.

Background Art

[0002] Techniques used for classifying waste and the like are known.

[0003] For example, Patent Document 1 describes a method for determining the type of material of waste, which includes an image acquisition step of photographing waste with a camera to obtain an image, and a passive determination step of determining the type of material of the waste from the obtained image. Further, Patent Document 1 discloses, as an example of the passive determination step, determination by color, texture, transmittance, reflectance, pressure, or cutting.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] As disclosed in Patent Document 1, whether it appears transparent when using visible light, ultraviolet light, or the like is one of the clues for classifying waste and the like. At this time, depending on the relationship between the waste and the location, such as when the color of the waste itself is similar to the color of the location where the waste is placed, it may be difficult to determine whether it is transparent using the image data. As a result, there has been a problem that it may be difficult to perform appropriate classification using the image data.

[0006] Therefore, one object of the present disclosure is to provide a processing device, a classification device, a classification method, and a program capable of solving the above-described problems.

Means for Solving the Problems

[0007] To achieve such an object, the processing device in the present disclosure has a pedestal part for placing waste to be classified, a visible light camera for imaging the waste placed on the pedestal part, and an infrared camera for imaging the waste placed on the pedestal part, and a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared light are formed on the surface of the pedestal part. It has such a configuration.

[0008] In addition, the classification device in the present disclosure has an image data acquisition unit that acquires image data obtained by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal part on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared light are formed on the surface, and a classification unit that performs classification according to whether visible light or far-infrared light passes through using the image data acquired by the image data acquisition unit. It has such a configuration.

[0009] In addition, the classification method in the present disclosure acquires image data obtained by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal part on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared light are formed on the surface, and performs classification according to whether visible light or far-infrared light passes through using the acquired image data. It has such a configuration.

[0010] In addition, the program in the present disclosure acquires image data obtained by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal part on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared light are formed on the surface, Perform classification according to whether visible light or far-infrared light is transmitted, using the acquired image data. It has such a configuration.

Advantages of the Invention

[0011] According to each configuration as described above, classification can be performed more appropriately using the image data.

Brief Description of the Drawings

[0012]

Figure 1

Figure 2

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Figure 11

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Figure 14

Modes for Carrying Out the Invention

[0013] [First Embodiment] A configuration example of the classification system 100 according to the present disclosure will be described with reference to FIGS. 1 to 10. FIG. 1 is a diagram showing a configuration example of the classification system 100. FIG. 2 is a diagram for explaining an example of the pedestal portion 210. FIG. 3 is a diagram showing an example of image data acquired by the visible light camera 230. FIG. 4 is a diagram showing an example of image data acquired by the far-infrared camera 240. FIG. 5 is a block diagram showing a configuration example of the classification device 300. FIG. 6 is a diagram showing an example of the classification information 341. FIG. 7 is a diagram for explaining a comparison example by the comparison unit 356. FIG. 8 is a flowchart showing an operation example of the classification device 300. FIG. 9 is a diagram for explaining another comparison example by the comparison unit 356. FIG. 10 is a diagram showing another configuration example of the classification system. Note that in the present disclosure, the drawings may be associated with one or more embodiments.

[0014] In the first embodiment of the present disclosure, a classification system 100 for classifying waste such as metal and plastic will be described. As will be described later, the classification system 100 classifies waste according to whether it transmits visible light or far-infrared light. At this time, the classification system 100 places the waste on the pedestal portion 210 on which the first pattern distinguishable by visible light is formed on the surface and the second pattern distinguishable by far-infrared light is formed on the surface, and checks whether it transmits visible light or far-infrared light. For example, in the case of waste that transmits visible light, by using a visible light camera 230 or the like, which is an imaging device using visible light, it is possible to acquire image data capable of confirming the first pattern transmitted through the waste. Further, in the case of waste that transmits far-infrared light, by using a far-infrared camera 240 or the like, which is an imaging device using far-infrared light, it is possible to acquire image data capable of confirming the second pattern transmitted through the waste. Therefore, the classification system 100 can accurately classify the waste according to whether it transmits visible light or far-infrared light by checking the image data acquired using the visible light camera 230, the far-infrared camera 240, or the like.

[0015] Further, the classification system 100 heats the waste placed on the pedestal portion 210 using a heating unit 220 such as a heater, and then acquires image data with the heated waste as the subject using an infrared camera 240 or the like. Then, the classification system 100 classifies the waste according to the thermal conductivity by comparing the acquired image data with a comparison target such as comparison image data stored in advance. By performing classification by such comparison, the classification system 100 can classify the waste according to the thermal conductivity without actually calculating the thermal conductivity.

[0016] Further, after the classification system 100 performs classification according to whether or not it transmits visible light or far-infrared rays as described above, etc., it can be configured to perform classification by comparison only for waste that is difficult to classify, such as waste that cannot be classified by classification according to whether or not it transmits. In other words, the classification system 100 can perform classification by comparison on the waste after exclusion, excluding the waste that can be easily classified without comparison among the waste to be classified.

[0017] FIG. 1 shows a configuration example of the entire classification system 100. Referring to FIG. 1, the classification system 100 includes a processing device 200 and a classification device 300. As shown in FIG. 1, the processing device 200 and the classification device 300 can be connected so as to be communicable with each other. For example, the classification device 300 can be connected to a visible light camera 230, an infrared camera 240, etc. in the processing device 200. The classification device 300 may also be connected so as to be communicable with a heating unit 220, etc. in the processing device 200.

[0018] The processing device 200 is a device that performs various processes required at the time of classification, such as imaging processing and heating processing on waste. Referring to FIG. 1, the processing device 200 includes, for example, a pedestal portion 210, a heating unit 220, a visible light camera 230, and an infrared camera 240. Note that the processing device 200 may have a configuration other than the above-exemplified one.

[0019] The pedestal portion 210 is a pedestal for placing waste to be classified and the like. For example, the pedestal portion 210 is a flat plate-shaped member having a rectangular shape in plan view on which waste can be placed on the surface. The pedestal portion 210 may be configured to be able to convey waste placed on the pedestal portion 210, such as a belt conveyor.

[0020] FIG. 2 shows an example of the state of the surface of the pedestal portion 210 on which waste is placed. Referring to FIG. 2, on the surface of the pedestal portion 210, a first pattern that is difficult to discriminate by far-infrared rays and can be discriminated by visible light, and a second pattern that is difficult to discriminate by visible light and can be discriminated by far-infrared rays, are formed. For example, in the case illustrated in FIG. 2, the first pattern and the second pattern are formed in a shifted state so as not to overlap. Here, the first pattern is a pattern formed by any material that reflects or absorbs visible light. For example, in the case illustrated in FIG. 2, a lattice pattern is formed as the first pattern. However, the first pattern may be any pattern other than the lattice pattern as long as it can be discriminated using visible light. Further, the second pattern is a pattern formed by any material that reflects or absorbs far-infrared rays. As an example, the second pattern is formed by a metal that reflects far-infrared rays, such as aluminum. For example, in the case illustrated in FIG. 2, a lattice pattern is formed as the second pattern. Note that the second pattern may be any pattern other than the lattice pattern as long as it can be discriminated using far-infrared rays, similar to the first pattern.

[0021] The heating unit 220 is a heater or the like that heats the waste placed on the pedestal portion 210 for a predetermined time. For example, the heating unit 220 is installed in the vicinity of the pedestal portion 210 and heats the waste for a predetermined time determined in advance in response to an instruction from the classification device 300 or other external devices. Note that the heating time and heating temperature by the heating unit 220 may be arbitrarily set. Further, the installation position of the heating unit 220 is not limited to the case illustrated in FIG. 1. The heating unit 220 may be installed at any position where it can heat the waste placed on the pedestal portion 210.

[0022] The visible light camera 230 is an imaging device capable of receiving light in the visible light region. The visible light camera 230 can acquire image data with the waste placed on the pedestal portion 210 as the subject. The visible light camera 230 may also acquire information indicating the time when the image data was acquired, together with the image data. For example, the visible light camera 230 acquires image data before heating by the heating unit 220. In addition to before heating by the heating unit 220, the visible light camera 230 may also acquire image data after heating.

[0023] FIG. 3 shows an example of image data when imaging the waste placed on the pedestal portion 210 using the visible light camera 230. Referring to FIG. 3, on the image data obtained using the visible light camera 230, the first pattern can be confirmed. Also, on the image data obtained using the visible light camera 230, in the case of waste that transmits visible light, the first pattern that transmits through the waste can be confirmed. For example, in the case illustrated in FIG. 3, for the waste O1, the first pattern that transmits through the waste can be confirmed. On the other hand, in the case of waste that does not transmit visible light, the first pattern that transmits through the waste cannot be confirmed. For example, in the case shown in FIG. 3, for the waste O2, the first pattern that transmits through the waste cannot be confirmed.

[0024] The far-infrared camera 240 is an imaging device capable of receiving light in the far-infrared region. The far-infrared camera 240 can acquire image data with the waste placed on the pedestal portion 210 as the subject. The far-infrared camera 240 may also acquire information indicating the time when the image data was acquired, together with the image data. For example, the far-infrared camera 240 acquires image data before and after heating the waste by the heating unit 220. The far-infrared camera 240 may acquire image data at the same time as the visible light camera 230, such as before heating by the heating unit 220.

[0025] FIG. 4 shows an example of image data when imaging waste placed on the pedestal portion 210 using the far-infrared camera 240. Referring to FIG. 4, on the image data obtained using the far-infrared camera 240, the second pattern can be confirmed. Also, on the image data obtained using the far-infrared camera 240, in the case of waste that transmits far-infrared rays, the second pattern that transmits through the waste can be confirmed. For example, in the case illustrated in FIG. 4, for the waste O2, the second pattern that transmits through the waste can be confirmed. On the other hand, in the case of waste that does not transmit far-infrared rays, the second pattern that transmits through the waste cannot be confirmed. For example, in the case shown in FIG. 4, for the waste O1, the second pattern that transmits through the waste cannot be confirmed.

[0026] For example, the processing device 200 has the configuration as described above. Note that the configuration of the processing device 200 may be other than the illustrated one. For example, when using a metal heating wire or the like as the heating unit 220, it may be configured to form the second pattern using the heating unit 220. In other words, the second pattern may be formed by the heating unit 220 installed on the surface of the pedestal portion 210. Also, the processing device 200 may be composed of a part of the configuration illustrated in FIG. 1, such as not having the heating unit 220.

[0027] The classification device 300 is an information processing device that classifies waste according to the image data acquired by the processing device 200. For example, the classification device 300 can classify waste according to the presence or absence of metallic luster that can be determined from the image data, whether it transmits visible light or far-infrared rays, the thermal conductivity, and the like. FIG. 5 shows a configuration example of the classification device 300. Referring to FIG. 5, the classification device 300 mainly includes, for example, an operation input unit 310, a screen display unit 320, a communication I / F unit 330, a storage unit 340, and an arithmetic processing unit 350.

[0028] Note that FIG. 5 illustrates a case where the functions of the classification device 300 are realized using a single information processing device. However, the classification device 300 may be realized using multiple information processing devices, for example, being realized on the cloud. Further, the classification device 300 may not include some of the above-exemplified configurations, such as not having the operation input unit 310 or the screen display unit 320, or may have a configuration other than the above-exemplified one.

[0029] The operation input unit 310 consists of operation input devices such as a keyboard and a mouse. The operation input unit 310 detects operations by an operator or the like who operates the classification device 300 and outputs them to the arithmetic processing unit 350.

[0030] The screen display unit 320 consists of a screen display device such as a liquid crystal display or an organic EL (electro-luminescence). The screen display unit 320 can display various information stored in the storage unit 340 and the like on the screen according to an instruction from the arithmetic processing unit 350.

[0031] The communication I / F unit 330 consists of a data communication circuit or the like. The communication I / F unit 330 performs data communication with the visible light camera 230, the far-infrared camera 240, and other external devices connected via a communication line.

[0032] The storage unit 340 is a storage device such as a hard disk or a memory. The storage unit 340 stores processing information and programs 345 necessary for various processes in the arithmetic processing unit 350. The program 345 is read into and executed by the arithmetic processing unit 350 to realize various processing units. The program 345 is pre-read from an external device or a recording medium via a data input / output function such as the communication I / F unit 330 and stored in the storage unit 340. The main information stored in the storage unit 340 includes, for example, classification information 341, comparison image information 342, visible light image information 343, far-infrared image information 344, and the like.

[0033] The classification information 341 is information that the classification device 300 refers to when performing classification according to the image data. The classification information 341 is acquired in advance using methods such as receiving an input using the operation input unit 310 and receiving an input from an external device or the like via the communication I / F unit 330, and is stored in the storage unit 340.

[0034] FIG. 6 shows an example of the classification information 341. Referring to FIG. 6, in the classification information 341, classification condition information that is a classification condition such as the presence or absence of gloss, the relationship of thermal conductivity, and whether it is transparent when viewed with visible light or far-infrared light, and classification information indicating materials to be classified such as metal, glass, and polyethylene are associated. For example, referring to FIG. 6, when the classification device 300 determines that there is gloss and the thermal conductivity is high from the image data, the waste can be classified as metal. Also, when the classification device 300 has no gloss and transmits far-infrared light (is transparent), the waste can be classified as polyethylene.

[0035] The comparison image information 342 is image data that the classification device 300 uses when performing classification according to thermal conductivity in the second classification. The comparison image information 342 includes comparison image data obtained using a far-infrared camera 240 or the like after heating a material that may be a classification target such as various plastics for a predetermined time. The comparison image information 342 may include comparison image data obtained after heating a reference substance such as water. The comparison image information 342 is acquired in advance using methods such as receiving an input from an external device or the like via the communication I / F unit 330, and is stored in the storage unit 340.

[0036] The visible light image information 343 includes the image data acquired by the visible light camera 230. In the visible light image information 343, the image data and information indicating the time when the visible light camera 230 acquired the image data may be associated. The visible light image information 343 is updated in response to, for example, the image data acquisition unit 351 acquiring image data from the visible light camera 230.

[0037] The far-infrared image information 344 includes the image data acquired by the far-infrared camera 240. In the far-infrared image information 344, the image data and the information indicating the time when the far-infrared camera 240 acquired the image data may be associated with each other. For example, the far-infrared image information 344 includes the image data acquired before heating by the heating unit 220 and the image data acquired after heating. The far-infrared image information 344 is updated in response to, for example, the image data acquisition unit 351 acquiring the image data from the far-infrared camera 240.

[0038] The arithmetic processing unit 350 includes an arithmetic device such as a CPU (Central Processing Unit) and its peripheral circuits. The arithmetic processing unit 350 reads and executes the program 345 from the storage unit 340, thereby causing the above-described hardware and the program 345 to cooperate to realize various processing units. The main processing units realized by the arithmetic processing unit 350 include, for example, an image data acquisition unit 351, a heating instruction unit 352, a first classification unit 353, a removal unit 354, a comparison target acquisition unit 355 and a comparison unit 356 forming a second classification unit, an output unit 357, and the like.

[0039] Note that the arithmetic processing unit 350 may have, instead of the above-described CPU, a GPU (Graphic Processing Unit), a DSP (Digital Signal Processor), an MPU (Micro Processing Unit), an FPU (Floating point number Processing Unit), a PPU (Physics Processing Unit), a TPU (Tensor Processing Unit), a quantum processor, a microcontroller, or a combination thereof.

[0040] The image data acquisition unit 351 acquires image data from the visible light camera 230, the far-infrared camera 240, etc. The image data acquisition unit 351 may also acquire information indicating the time when the image data was acquired, together with the image data, from the visible light camera 230, the far-infrared camera 240, etc. For example, the image data acquisition unit 351 can acquire the image data acquired by the visible light camera 230 or the far-infrared camera 240 in the state before heating by the heating unit 220, and the image data acquired by the visible light camera 230 or the far-infrared camera 240 after heating. Also, the image data acquisition unit 351 stores the image data acquired from the visible light camera 230 in the storage unit 340 as visible light image information 343. Also, the image data acquisition unit 351 stores the image data acquired from the far-infrared camera 240 in the storage unit 340 as far-infrared image information 344.

[0041] The heating instruction unit 352 instructs the heating unit 220 to perform heating for a predetermined period of time. For example, the heating instruction unit 352 can give an instruction to the heating unit 220 at an arbitrary timing, such as after the visible light camera 230 or the far-infrared camera 240 has acquired image data in the state before heating.

[0042] The first classification unit 353 performs a first classification using the image data included in the visible light image information 343 and the far-infrared image information 344 with reference to the classification information 341. For example, as the first classification, the first classification unit 353 performs a relatively easily executable classification process according to conditions such as whether visible light is transmitted or not, and whether far-infrared light is transmitted or not.

[0043] For example, the first classification unit 353 refers to the image data included in the visible light image information 343, and classifies the waste to be classified, which is determined to have a first pattern that is transparent and transmits visible light, as glass or acrylic. Also, the first classification unit 353 refers to the image data included in the far-infrared image information 344, and classifies the waste to be classified, which is determined to have a second pattern that is transparent and transmits far-infrared light, as polyethylene. For example, as described above, the first classification unit 353 can perform classification according to conditions such as whether visible light or far-infrared light is transmitted, as the first classification, among the information included in the classification information 341.

[0044] In addition to the above classification process, the first classification unit 353 may be configured to classify whether the waste is metal. For example, as shown in FIG. 6, when the waste is metal, the thermal conductivity is often higher compared to when the waste is other than metal. Therefore, the first classification unit 353 refers to the heated image data included in the far-infrared image information 344, and classifies the waste to be classified, which can be determined to be metal with high thermal conductivity from the heated state, as metal. For example, the first classification unit 353 can classify whether the waste is metal by comparing with the previously prepared heated image data for metal classification. Also, the first classification unit 353 may further classify the metal into painted metal and unpainted metal in more detail according to the presence or absence of metallic luster by using the image data included in the visible light image information 343 in combination. Note that the first classification unit 353 may determine the presence or absence of metallic luster based on an arbitrary criterion.

[0045] The exclusion unit 354 specifies the waste that is not the target of the classification process by the second classification unit among the waste to be classified according to the first classification result by the first classification unit 353. In other words, the exclusion unit 354 excludes the waste classified as a specific material such as glass or acrylic, polyethylene, or metal by the first classification by the first classification unit 353 from the target of the classification process by the second classification unit.

[0046] The comparison target acquisition unit 355 acquires the image data to be compared by the comparison unit 356. For example, the comparison target acquisition unit 355 acquires the comparison image data corresponding to each material that may be the classification target by referring to the comparison image information 342.

[0047] The comparison unit 356 performs a second classification for classifying waste by comparing the post-heating image data included in the far-infrared image information 344 with the comparison image data acquired by the comparison target acquisition unit 355. For example, as shown in FIG. 7, the comparison unit 356 performs classification by comparison on the waste that has not been excluded by the exclusion unit 354 among the waste to be classified. In other words, the comparison unit 356 does not perform comparison with the comparison image data for the waste excluded by the exclusion unit 354.

[0048] For example, the comparison unit 356 can classify waste according to, for example, specifying the comparison image data most similar to the waste to be classified. As an example, the comparison unit 356 extracts feature amounts from the waste that has not been excluded and included in the post-heating image data. In addition, the comparison unit 356 extracts feature amounts from each of the comparison image data corresponding to each material. Then, the comparison unit 356 specifies the comparison image data most similar to the waste to be classified, such as by calculating the distance between the extracted feature amounts. For example, the comparison unit 356 specifies the comparison image data with the shortest distance between the feature amounts as the comparison image data most similar to the waste to be classified. Thereafter, the comparison unit 356 classifies that the waste to be classified is the material corresponding to the specified comparison image data. Note that the comparison unit 356 may be configured to classify the waste to be classified according to, for example, the difference between the image data of the waste to be classified and the image data when water included in the comparison image information 342 is heated. In addition, the comparison unit 356 may perform classification by comparison using a method other than the above-exemplified method.

[0049] The output unit 357 outputs the results of the first classification by the first classification unit 353 and the second classification by the comparison unit 356. For example, the output unit 357 displays the classification results by the first classification unit 353 and the comparison unit 356 on the screen display unit 320, or transmits them to an external device via the communication I / F unit 330. The output unit 357 may also output the classification results by the first classification unit 353 and the comparison unit 356 by superimposing them on the image data acquired by the visible light camera 230 or the image data acquired by the far-infrared camera 240.

[0050] The above is a configuration example of the classification device 300. Next, with reference to FIG. 8, an operation example of the classification device 300 will be described.

[0051] FIG. 8 is a flowchart showing an operation example of the classification device 300. Referring to FIG. 8, the image data acquisition unit 351 acquires the image data acquired by the visible light camera 230 and the far-infrared camera 240 in the state before heating by the heating unit 220 (step S101). Also, the image data acquisition unit 351 acquires the image data acquired by the far-infrared camera 240 after heating by the heating unit 220 (step S102). The image data acquisition unit 351 may also acquire the image data acquired by the visible light camera 230 after heating by the heating unit 220.

[0052] The first classification unit 353 refers to the classification information 341 and performs a first classification using the image data included in the visible light image information 343 and the far-infrared image information 344 (step S103). For example, as the first classification, the first classification unit 353 performs a classification according to conditions such as whether or not visible light is transmitted and whether or not far-infrared light is transmitted. In addition to the above examples, the first classification unit 353 may perform a classification such as whether or not it is a metal.

[0053] The external exclusion unit 354 identifies waste that is not subject to the classification process by the second classification unit among the waste to be classified, according to the first classification result by the first classification unit 353 (step S104). In other words, the external exclusion unit 354 excludes waste classified as being of a specific material such as glass or acrylic, polyethylene, or metal by the first classification by the first classification unit 353 from the objects of the classification process by the second classification unit.

[0054] The comparison target acquisition unit 355 and the comparison unit 356 perform a second classification for classifying waste by comparing image data (step S105). For example, the comparison unit 356 can perform classification by comparison on the waste that has not been excluded by the external exclusion unit 354 among the waste to be classified.

[0055] The output unit 357 outputs the classification results by the first classification unit 353 and the comparison unit 356 (step S106). For example, the output unit 357 can display the classification results by the first classification unit 353 and the comparison unit 356 on the screen display unit 320 or transmit them to an external device via the communication I / F unit 330.

[0056] The above is an example of the operation of the classification device 300.

[0057] In this way, a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed on the surface of the pedestal portion 210. According to such a configuration, by acquiring image data using the visible light camera 230 and the far-infrared camera 240, it is possible to confirm the first pattern and the second pattern that pass through the waste for waste that transmits visible light or far-infrared rays. As a result, the classification system 100 can easily confirm whether visible light or far-infrared rays pass through the waste.

[0058] Further, the classification device 300 has a comparison unit 356. According to such a configuration, the classification device 300 can classify waste according to the result of comparison by the comparison unit 356. In this way, by performing classification according to comparison, waste can be classified without actually calculating the thermal conductivity or the like.

[0059] Further, the classification device 300 has a first classification unit 353 and an exclusion unit 354. According to such a configuration, the exclusion unit 354 can exclude the waste classified by the first classification by the first classification unit 353 from the objects of the classification process by the second classification unit according to the first classification result by the first classification unit 353. As a result, the comparison unit 356 can perform classification by comparison only on the waste not excluded by the exclusion unit 354. As a result, the objects for classification by comparison can be narrowed down, and the cost at the time of classification by comparison can be suppressed.

[0060] Note that the configuration of the classification device 300 may be other than that illustrated in FIG. 5. For example, the classification device 300 may not have the first classification unit 353 and the exclusion unit 354. In this case, the comparison unit 356 can perform classification by comparison on all waste to be classified. When the comparison unit 356 is configured in this way, the comparison image information 342 may include comparison image data obtained using a far-infrared camera 240 or the like after heating a material that may be a classification target, including glass, metal, etc. for a predetermined time. Further, the classification device 300 may not have a function as a second classification unit. In this case, the classification device 300 can classify only the waste that can be classified by the first classification.

[0061] In addition, as shown in FIG. 9, the classification system 100 may be configured to place each reference substance together with the waste on the pedestal portion 210 and then heat it to acquire image data using a far-infrared camera 240 or the like. For example, the classification system 100 may place the reference substance on a predetermined area of the pedestal portion 210. In such a configuration, instead of acquiring the reference image data from the reference image information 342, the reference object acquisition unit 355 can acquire the reference image data from the post-heating image data included in the far-infrared image information 344. For example, the reference object acquisition unit 355 may acquire the reference image data by cutting out the portion corresponding to the reference substance from the image data captured using the far-infrared camera after heating for a predetermined time. Thus, the information about the object to be compared with the waste to be classified may be stored in the storage unit 340 in advance, or may be acquired together when acquiring the image data about the waste to be classified. Note that in the case of the above configuration, the reference image information 342 may not be stored in the storage unit 340.

[0062] In addition, as illustrated in FIG. 10, the processing device 200 may include an illumination device 250 such as an LED (Light Emitting Diode) capable of outputting arbitrary different wavelengths. In such a configuration, the visible light camera 230 and the far-infrared camera 240 may be configured to acquire image data corresponding to each of the plurality of wavelengths irradiated by the illumination device 250. Further, the classification device 300 may be configured to classify the waste according to the absorption characteristics and reflection characteristics of each wavelength according to the image data acquired under the irradiation of each wavelength. In addition, the processing device 200 may include a mid-infrared camera or the like instead of the far-infrared camera 240.

[0063] [Second Embodiment] Next, with reference to FIGS. 11 to 14, a configuration example of the processing device 400 and the classification device 500 will be described. FIG. 11 is a diagram showing a configuration example of the processing device 400. FIG. 12 is a diagram showing a hardware configuration example of the classification device 500. FIG. 13 is a block diagram showing a configuration example of the classification device 500. FIG. 14 is a flowchart showing an operation example of the classification device 500.

[0064] In the second embodiment of the present disclosure, a processing device 400 that performs processing necessary for classification such as imaging processing on waste will be described. In addition, a classification device 500 that classifies waste according to the result of the processing by the processing device 400 will be described.

[0065] First, with reference to FIG. 11, a configuration example of the processing device 400 will be described. Referring to FIG. 11, the processing device 400 includes a pedestal portion 410, a visible light camera 420, and a far-infrared camera 430.

[0066] The pedestal portion 410 can place waste to be classified. In addition, on the surface of the pedestal portion 410 where the waste is placed, a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed. Further, the visible light camera 420 and the far-infrared camera 430 can image the waste placed on the pedestal portion 410.

[0067] As described above, the processing device 400 has a pedestal portion 410 on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed. According to such a configuration, by acquiring image data using the visible light camera 420 or the far-infrared camera 430, for waste that transmits visible light or far-infrared rays, the first pattern and the second pattern that transmit through the waste can be confirmed. As a result, it is possible to easily confirm whether visible light or far-infrared rays pass through the waste.

[0068] The above is a configuration example of the processing device 400. Subsequently, with reference to FIGS. 12 to 14, a configuration example of the classification device 500 will be described. FIG. 12 shows a hardware configuration example of the classification device 500. Referring to FIG. 12, the classification device 500 has, as an example, the following hardware configuration. · CPU (Central Processing Unit) 501 (arithmetic unit) · ROM (Read Only Memory) 502 (storage device) · RAM (Random Access Memory) 503 (storage device) · Program group 504 loaded into RAM 503 · Storage device 505 that stores program group 504 · Drive device 506 that reads and writes to recording medium 510 outside the information processing device · Communication interface 507 connected to communication network 511 outside the information processing device · Input / output interface 508 that performs data input / output · Bus 509 that connects each component

[0069] Also, the classification device 500 can realize the functions of the image data acquisition unit 521 and the classification unit 522 shown in FIG. 13 by the CPU 501 acquiring the program group 504 and the CPU 501 executing it. Note that the program group 504 is stored in the storage device 505 or the ROM 502 in advance, and is loaded into the RAM 503 or the like by the CPU 501 as needed and executed. Also, the program group 504 may be supplied to the CPU 501 via the communication network 511, or may be stored in the recording medium 510 in advance, and the drive device 506 may read the program and supply it to the CPU 501.

[0070] Note that FIG. 12 shows an example of the hardware configuration of the classification device 500. The hardware configuration of the classification device 500 is not limited to the above-described case. For example, the classification device 500 may be configured from a part of the above-described configuration, such as not having the drive device 506. Further, the CPU 501 may be a GPU or the like exemplified in the first embodiment.

[0071] The image data acquisition unit 521 acquires image data acquired by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal portion on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed on the surface. For example, the image data acquisition unit 521 may acquire both the image data acquired by the visible light camera and the image data acquired by the infrared camera.

[0072] The classification unit 522 (first classification unit) performs classification according to whether visible light or far-infrared rays pass through, using the image data acquired by the image data acquisition unit 521. For example, the classification unit 522 can perform the first classification described in the first embodiment.

[0073] The above is an example of the configuration of the classification device 500. Subsequently, an example of the operation of the classification device 500 will be described with reference to FIG. 14.

[0074] FIG. 14 is a flowchart showing an example of the operation of the classification device 500. Referring to FIG. 14, the image data acquisition unit 521 acquires image data acquired by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal portion on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed on the surface (step S201).

[0075] The classification unit 522 (first classification unit) performs classification according to whether visible light or far-infrared rays pass through, using the image data acquired by the image data acquisition unit 521 (step S202).

[0076] As described above, the classification device 500 includes an image data acquisition unit 521 and a classification unit 522. According to such a configuration, the classification unit 522 can perform classification according to whether visible light or far-infrared rays pass through, using the image data acquired by the image data acquisition unit 521. As a result, the classification device 500 can easily determine whether visible light or far-infrared rays pass through the waste according to the first pattern or the second pattern, so that more accurate classification can be realized.

[0077] Note that the above-described classification device 500 can be realized by incorporating a predetermined program into an information processing device such as the classification device 500. Specifically, a program according to another aspect of the present disclosure causes an information processing device to acquire comparison image data for comparison when classifying waste, and after heating for a predetermined time, image data including the waste to be classified, which is captured using a far-infrared camera, and the acquired comparison image data, and compares them to classify the waste.

[0078] Also, a classification method executed by an information processing device such as the above-described classification device 500 is a method in which the information processing device acquires comparison image data for comparison when classifying waste, and after heating for a predetermined time, compares image data including the waste to be classified, which is captured using a far-infrared camera, with the acquired comparison image data to classify the waste.

[0079] Even in the case of a program, a computer-readable recording medium recording the program, a classification method, etc. having the above-described configuration, the object of the present disclosure described above can be achieved in order to exhibit the same operations and effects as the above-described classification device 500.

[0080] <Supplementary Note> Some or all of the above embodiments may also be described as follows. Hereinafter, an outline of a classification device and the like in the present disclosure will be described. However, the present disclosure is not limited to the following configuration.

[0081] (Supplementary Note 1) A pedestal for placing waste to be classified, A visible light camera for imaging the waste placed on the pedestal, An infrared camera for imaging the waste placed on the pedestal, and On the surface of the pedestal, a first pattern distinguishable by visible light and a second pattern distinguishable by infrared rays are formed. Processing device. (Appendix 2) The processing device according to Appendix 1, having a heating unit for heating the waste placed on the pedestal, The visible light camera images the waste placed on the pedestal at least before heating by the heating unit, The infrared camera images the waste placed on the pedestal before and after heating by the heating unit. Processing device. (Appendix 3) The processing device according to Appendix 2, wherein the second pattern is formed by the heating unit installed on the surface of the pedestal. Processing device. (Appendix 4) An image data acquisition unit that acquires image data obtained by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal on which a first pattern distinguishable by visible light and a second pattern distinguishable by infrared rays are formed on the surface; A classification unit that classifies according to whether visible light or infrared rays can pass through, using the image data acquired by the image data acquisition unit. and Classification device. (Appendix 5) The classification device according to Appendix 4, A comparison target acquisition unit that acquires comparison image data as a comparison target when classifying waste; A comparison unit that classifies waste by comparing image data including the waste to be classified, imaged using an infrared camera after heating for a predetermined time, with the comparison image data acquired by the comparison target acquisition unit. An excluding unit that excludes waste that is not a comparison target by the comparison unit from the waste to be classified according to the classification result by the classification unit, has, The comparison unit performs classification by comparison on the waste not excluded by the excluding unit. Classification device. (Appendix 6) The classification device according to Appendix 5, The image data captured using the far-infrared camera after heating for a predetermined time is captured with a comparison substance installed in addition to the waste to be classified. The comparison target acquisition unit acquires comparison image data from the image data captured using the far-infrared camera after heating for a predetermined time. Classification device. (Appendix 7) The classification device according to any one of Appendices 4 to 6, The classification unit performs classification according to whether the waste to be classified transmits visible light or far-infrared light, and also performs classification according to whether the waste to be classified is metal. Classification device. (Appendix 8) The classification device according to any one of Appendices 4 to 7, The image data acquisition unit acquires the image data acquired by the visible light camera or the far-infrared camera with the waste to be classified placed on the pedestal portion where the first pattern and the second pattern formed by the heating unit used when heating the waste to be classified are formed. Classification device. (Appendix 9) An information processing device, acquires comparison image data for comparison when classifying waste, classifies the waste by comparing the image data including the waste to be classified captured using the far-infrared camera after heating for a predetermined time with the acquired comparison image data. Classification method. (Appendix 10) In the information processing device, Obtain comparison image data to be used as a comparison target when classifying waste, After heating for a predetermined time, compare the image data including the waste to be classified, which is captured using an infrared camera, with the obtained comparison image data to classify the waste A program for realizing the process.

[0082] Note that part or all of the configurations described in Appendices 5 to 8, which are subordinate to the classification device described in Appendix 4, may also be subordinate to the classification method described in Appendix 9, the program described in Process 10, etc. in the same subordinate relationship. Furthermore, not limited to Appendices 9 and 10, within the scope not departing from the above-described embodiments, part or all of the configurations described as appendices can similarly be made subordinate to various hardware, software, various recording means for recording software, or systems. For example, part or all of the configurations described in Appendices 5 to 8 may be subordinate to a classification system having the processing device described in Appendix 1 and the classification device described in Appendix 4 in the same subordinate relationship.

[0083] Note that the programs described in the above embodiments and appendices are stored in a storage device or recorded on a computer-readable recording medium. For example, the recording medium is a portable medium such as a flexible disk, an optical disk, a magneto-optical disk, and a semiconductor memory.

[0084] The present disclosure has been described with reference to the above embodiments, but the present disclosure is not limited to the above-described embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. And each embodiment can be combined with other embodiments as appropriate.

Description of Reference Numerals

[0085] 100 Classification system 200 Processing device 210 Pedestal part 220 Heating part 230 Visible Light Camera 240 Far-Infrared Camera 250 Lighting Device 300 Classification Device 310 Operation Input Unit 320 Screen Display Unit 330 Communication I / F Unit 340 Memory Unit 341 Classification Information 342 Comparison Image Information 343 Visible Light Image Information 344 Far-Infrared Image Information 345 Program 350 Arithmetic Processing Unit 351 Image Data Acquisition Unit 352 Heating Instruction Unit 353 First Classification Unit 354 Exclusion Unit 355 Comparison Target Acquisition Unit 356 Comparison Unit 357 Output Unit 400 Processing Device 410 Pedestal Unit 420 Visible Light Camera 430 Far-Infrared Camera 500 Classification Device 501 CPU 502 ROM 503 RAM 504 Program Group 505 Memory Device 506 Drive Device 507 Communication Interface 508 Input / Output Interface 509 Bus 510 Recording Medium 511 Communication Network 521 Image Data Acquisition Unit 522 Classification Unit

Claims

1. A pedestal for placing waste to be classified, A visible light camera for imaging the waste placed on the pedestal, An infrared camera for imaging the waste placed on the pedestal, Having, On the surface of the pedestal for placing waste, a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed. Processing device.

2. The processing device according to claim 1, Having a heating unit for heating the waste placed on the pedestal, The visible light camera images the waste placed on the pedestal at least before heating by the heating unit, The infrared camera images the waste placed on the pedestal before and after heating by the heating unit. Processing device.

3. The processing device according to claim 2, The second pattern is formed by the heating unit installed on the surface of the pedestal. Processing device.

4. An image data acquisition unit that acquires image data obtained by a visible light camera or an infrared camera in a state where waste to be classified is placed on a pedestal on which a first pattern distinguishable by visible light and a second pattern distinguishable by far-infrared rays are formed on the surface, A classification unit that classifies according to whether visible light or far-infrared rays pass through, using the image data acquired by the image data acquisition unit. Having Classification device.

5. The classification device according to claim 4, A comparison target acquisition unit that acquires comparison target image data that is a comparison target when classifying waste, A comparison unit that classifies waste by comparing image data including the waste to be classified, imaged using an infrared camera after heating for a predetermined time, and the comparison target image data acquired by the comparison target acquisition unit, An exclusion unit that excludes waste that is not a comparison target by the comparison unit among the waste to be classified according to the classification result by the classification unit. Having The comparison unit performs classification by comparison on the waste that has not been excluded by the exclusion unit. Classification device.

6. The classification device according to claim 5, The image data imaged using an infrared camera after heating for a predetermined time is imaged with a comparison substance installed in addition to the waste to be classified, The comparison target acquisition unit acquires comparison target image data from the image data imaged using an infrared camera after heating for a predetermined time. Classification device.

7. The classification device according to claim 4, The classification unit performs classification according to whether the waste to be classified transmits visible light or far-infrared rays, and also performs classification according to whether the waste to be classified is metal. Classification device.

8. The classification device according to claim 4, The image data acquisition unit acquires the image data acquired by a visible light camera or a far-infrared camera with the waste to be classified placed on the pedestal portion on which the first pattern and the second pattern formed by the heating unit used when heating the waste to be classified are formed. Classification device.

9. An information processing device, acquires comparison image data as a comparison target when classifying waste, classifies the waste by comparing the image data including the waste to be classified, which is captured using a far-infrared camera after heating for a predetermined time, with the acquired comparison image data. Classification method.

10. In an information processing device, acquires comparison image data as a comparison target when classifying waste, classifies the waste by comparing the image data including the waste to be classified, which is captured using a far-infrared camera after heating for a predetermined time, with the acquired comparison image data. Program for realizing the process.

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