JP2019144105A - Measurement device - Google Patents

Abstract

To provide a measurement device which can measure and output the weight of the unit area of fabric.SOLUTION: The measurement device includes; a mounted board; a mass meter; a camera; an output unit; and a processor. The output unit outputs a unit area mass showing the mass of the unit area of a fabric piece. The processor executes: mass measuring, imaging for measurement; processing an area for measurement; calculation; and outputting. The mass measuring acquires the mass of a fabric piece measured by the mass meter. The imaging for measurement acquires imaging data for measurement. The imaging data for measurement includes an image part for the fabric piece imaged by the camera. The processing of an area for measurement acquires an area for measuring a region corresponding to the fabric piece from the image part of the fabric piece in the imaging data for measurement. The calculation calculates the mass of the unit area from the mass and the area for measurement. The output processing outputs the mass of the unit area by an output unit.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a measuring device that measures and outputs a mass per unit area of a piece of dough.

  The applicant has proposed a line inspection method and a line inspection apparatus in Patent Document 1. In this line inspection method and line inspection apparatus, two-dimensional spatial texture features of the fabric are extracted, and the yarn crossing angle, the number of warps and the number of wefts are mathematically determined. The texture feature extraction algorithm includes the following steps (1) to (5). That is, (1) digital image data of a fabric is acquired from a digital still camera. (2) A window function process is performed on the digital image data. (3) Fast Fourier transform is performed on the digital image data subjected to the window function processing to obtain a Fourier spectrum. (4) Extract the peak of the Fourier spectrum. (5) The information (angle and frequency) of each peak is made to correspond to the texture feature amount (yarn crossing angle, number of warps and number of wefts) of the fabric. The filament inspection method and the filament inspection apparatus use a film, a sheet, a screen, or a plate on which a mesh-like filament is formed by printing or etching in addition to a woven fabric. For example, the line inspection method and the line inspection apparatus use an electromagnetic wave shielding filter for plasma display, a separation filter for biochemistry, a screen screen for printing, or a screen door as an inspection target.

Japanese Patent No. 4520794

  At the time of manufacturing a dough or a predetermined product made of dough, the quality of the dough as a product or material is managed at the manufacturing site. For example, at the manufacturing site, the unit area mass of the dough is managed. The unit area mass is the mass per unit area. Therefore, the inventor studied a measuring device that can smoothly measure the unit area mass of the dough regardless of the size (area) of the dough piece and output the unit area mass.

  An object of this invention is to provide the measuring apparatus which can measure and output the mass per unit area of dough.

  One aspect of the present invention is to image a placing table on which the dough piece is placed, a mass meter for measuring the mass of the dough piece placed on the placing table, and the dough piece placed on the placing table. A camera, an output device that outputs a unit area mass indicating a mass per unit area of the dough piece, and a processor, wherein the processor obtains a mass of the dough piece measured by the mass meter Processing, measurement imaging processing for acquiring measurement imaging data including an image portion of the fabric piece captured by the camera, and the measurement imaging data acquired in the measurement imaging processing Measurement area processing for acquiring the measurement area of the region corresponding to the fabric piece from the image portion of the fabric piece, the mass of the fabric piece acquired by the mass processing, and the area acquired by the measurement area processing Measurement Run the area, a calculation process for calculating the mass per unit area by the output processing for outputting the mass per unit area obtained by the calculation processing in the output device, and a measuring device.

  According to this measuring device, the unit area mass of the piece of cloth can be measured and output as a measurement result. By obtaining the measurement area of the region corresponding to the fabric piece from the image portion of the fabric piece included in the measurement imaging data, the unit area mass can be measured regardless of the shape of the fabric piece. For example, when measuring the unit area mass, it is not necessary to cut the dough piece from the dough into a predetermined shape. For example, the unit area mass of a fabric as a product or a raw material can be smoothly measured at the manufacturing site when manufacturing a fabric or a predetermined product made of fabric.

  The measuring apparatus includes an irradiator that irradiates infrared rays in an imaging range of the camera, and the camera includes an image sensor having sensitivity to infrared rays, images the infrared rays from the irradiator, and measures the measurement. The image pickup process may be a process of acquiring the measurement image pickup data including an image portion of the cloth piece by infrared rays reflected by the cloth piece. In this case, the measurement apparatus may include an infrared transmission filter between the mounting table and the camera. In the measurement apparatus, the camera may be an infrared camera.

  According to each above-mentioned composition, the image part of a cloth piece can be detected stably. The accuracy of the measurement area can be improved. Assume that the dough piece is a part of the dough having the following pattern. The aforementioned pattern is, for example, a pattern in which a plurality of figures having a predetermined shape of the same color as the placement surface are arranged on the entire cloth. The placement surface is the surface of the placement table on which the dough piece is placed. Examples of such a pattern include a polka dot pattern in which a plurality of polka dots having the same color as the placement surface are appropriately arranged. The above-described polka dot pattern will be described as an example. In measuring the unit area mass, when cutting a polka-dotted fabric to form a fabric piece, the cutting position of the fabric may be on the polka dot. When using visible light for imaging the fabric piece, in the visible light image corresponding to the imaging data obtained by this imaging, the background color (the color of the mounting surface) and the color of the cut polka dot portion at the outer edge of the fabric piece are the same color It becomes. As a result, it is conceivable that the image portion of the cloth piece cannot be detected properly, or special image analysis is required for the above-described detection. On the other hand, in the measurement imaging data using infrared rays for imaging the fabric piece, the influence of the polka dot pattern on the image portion of the fabric piece is eliminated or reduced. As a result, the boundary between the background (mounting surface) and the image portion of the fabric piece is stabilized, and the image portion of the fabric piece can be distinguished from the background. The work of changing the mounting table in accordance with the fabric pattern is not necessary.

  In the measurement apparatus, a reference sample with an area set to a reference value is placed on the mounting table, the camera images the reference sample placed on the mounting table, and the processor A calibration imaging process for acquiring calibration imaging data including an image part of the reference sample imaged by the calibration, and an image part of the reference sample included in the calibration imaging data acquired by the calibration imaging process A correction coefficient corresponding to the difference between the calibration area processing for acquiring the calibration area of the region corresponding to the reference sample from the reference value and the calibration area acquired by the calibration area processing is calculated. Correction coefficient processing is performed, and the calculation processing calculates the mass of the dough piece acquired by the mass processing and the measurement area acquired by the measurement area processing by the correction coefficient processing. Said Is a process to calculate the mass per unit area divided by the correction area corrected by the positive coefficient, may be.

  According to this configuration, the measurement area can be corrected by the correction coefficient. The measurement accuracy of unit area mass can be improved.

  ADVANTAGE OF THE INVENTION According to this invention, the measuring apparatus which can measure and output the mass per unit area of dough can be obtained.

It is a perspective view which shows an example of schematic structure of a measuring apparatus. It is a figure which shows an example of schematic structure of the main screen as an operation screen. The upper row shows the state before measurement of unit area mass. This corresponds to a state in which the dough piece is not placed on the placing table. The lower row shows the state after measurement of unit area mass. This corresponds to the state in which the dough piece is placed on the placing table. It is a figure which shows an example of schematic structure of the sub screen as an operation screen. This corresponds to the state in which the reference sample is placed on the mounting table. It is a flowchart of a main process. It is a flowchart of the 1st part of a calibration process. It is a flowchart of the 2nd part of a calibration process. It is a flowchart of an area process for measurement. It is a flowchart of the area process for 1st calibration. It is a flowchart of the area process for 2nd calibration. It is a flowchart of the area process for 3rd calibration. It is a flowchart of the area process for 4th calibration. It is a flowchart of the area process for 5th calibration. It is a flowchart of an actual measurement process. It is a flowchart of a correction coefficient process. It is a figure which shows the imaging data for a measurement. The upper row shows the first aspect. In the first aspect, infrared rays are used for imaging. The lower row shows the second embodiment. In the second aspect, visible light is used for imaging.

  Embodiments for carrying out the present invention will be described with reference to the drawings. The present invention is not limited to the configurations described below, and various configurations can be employed in the same technical idea. For example, some of the configurations shown below may be omitted or replaced with other configurations. Other configurations may be included.

<Measurement device>
The measuring apparatus 10 will be described with reference to FIG. FIG. 1 schematically shows a measuring apparatus 10. Therefore, in FIG. 1, a broken line is a hide line, a dashed-dotted line is a center line (reference line), and a dashed-two dotted line is an imaginary line.

The measuring device 10 is a device that measures the unit area mass N. In the embodiment, the measurement target of the unit area mass N is the dough piece 15. The fabric piece 15 is, for example, a part of the fabric cut out from the fabric. The dough is used as a material for a predetermined product. The unit area mass N is the mass per unit area. In the embodiment, the unit area is 1 m ² . However, the unit area may be an area different from 1 m ² . The unit area is appropriately determined in consideration of various conditions. The measuring device 10 is used, for example, at a production site of fabric or a production site of a predetermined product made of fabric. The quality of the dough is managed by the measuring device 10. The measuring apparatus 10 includes a mounting table 20, a mass meter 30, a camera 40, a storage chamber 45, an irradiator 50, an output device 60, and a controller 70.

  A dough piece 15 is placed on the mounting table 20. In the embodiment, the surface of the mounting table 20 on which the dough piece 15 is placed is referred to as a “mounting surface 22”. In the mounting table 20, any or all of the infrared reflectance, infrared absorption rate, and infrared transmittance of the mounting surface 22 may be different from the fabric piece 15. For example, in the mounting table 20, the infrared reflectance of the mounting surface 22 is preferably lower than that of the fabric piece 15, and the infrared absorption rate of the mounting surface 22 is preferably higher than that of the fabric piece 15. The rate should be higher than the dough piece 15. Generally, the fabric has a property of reflecting infrared rays. In the measuring apparatus 10, the following mounting table is adopted as the mounting table 20. That is, the mounting table 20 is made of acrylic, and the mounting surface 22 is a single color matte state. The color of the mounting surface 22 was black.

  The mass meter 30 measures the mass M of the object placed on the mounting table 20 and outputs the measured mass M. In the embodiment, the dough piece 15 is placed on the mounting table 20. In this case, the mass meter 30 outputs the mass M of the dough piece 15. In addition, the reference sample 17 is placed on the mounting table 20 (see FIG. 3). The reference sample 17 will be described later. The mass meter 30 is, for example, an electronic balance. In the measuring apparatus 10, a known mass meter can be adopted as the mass meter 30. Therefore, the other description regarding the mass meter 30 is omitted.

  The camera 40 is a digital camera. The camera 40 includes an image sensor having sensitivity to infrared rays. That is, the camera 40 can image infrared rays. However, the image sensor also has sensitivity to visible light. Therefore, the camera 40 can also capture visible light. The camera 40 is provided in a state facing the placement surface 22 above the placement surface 22. In the measurement apparatus 10, the camera 40 faces the placement surface 22. Therefore, the imaging direction of the camera 40 is a direction perpendicular to the placement surface 22. The camera 40 includes the placement surface 22 in the imaging range R1. The imaging range R1 is a range that is imaged by the camera 40. In FIG. 1, among the two rectangular frames indicated by the two-dot chain line on the placement surface 22, the inner rectangular frame indicates the imaging range R1. In the embodiment, the entire fabric piece 15 is included in the imaging range R1. That is, the cloth piece 15 has an arbitrary shape smaller than the imaging range R1. Accordingly, the camera 40 images the entire surface of the dough piece 15 in a state where the dough piece 15 is placed on the mounting table 20. In the embodiment, the reference sample 17 is also entirely included in the imaging range R1. That is, the reference sample 17 has a predetermined shape that is smaller than the imaging range R1. Along with this, the camera 40 images the entire surface of the reference sample 17 placed on the mounting table 20.

  The accommodation chamber 45 accommodates the camera 40. An infrared transmission filter 47 is provided on the bottom surface of the storage chamber 45. The storage chamber 45 has a structure in which a portion other than the infrared transmission filter 47 on the bottom is shielded from light. In a state where the camera 40 is accommodated in the accommodation chamber 45, the infrared transmission filter 47 is provided between the mounting table 20 and the camera 40. The infrared transmission filter 47 is a filter that absorbs ultraviolet rays and visible light and transmits infrared rays. Accordingly, of the light reflected by the fabric piece 15, visible light or the like is absorbed by the infrared transmission filter 47 and does not reach the camera 40. In other words, of the light reflected by the fabric piece 15, the infrared light passes through the infrared transmission filter 47 and reaches the camera 40. In the measuring apparatus 10, for example, a known infrared transmission filter that absorbs light having a wavelength of 800 nm or less can be employed as the infrared transmission filter 47. Therefore, the other description regarding the infrared transmission filter 47 is omitted.

  The irradiator 50 emits infrared rays. Examples of the irradiator 50 that can be employed in the measuring apparatus 10 include an infrared LED having a peak wavelength of 850 nm. The irradiator 50 illuminates the imaging range R <b> 1 with infrared rays from above the placement surface 22. In the measuring apparatus 10, the direction of infrared irradiation is a direction inclined with respect to the placement surface 22. Therefore, the irradiator 50 illuminates the imaging range R <b> 1 with infrared rays from obliquely above the placement surface 22. In the embodiment, the number of irradiators 50 in the measurement apparatus 10 is two. Two irradiators 50 are provided on both sides of the camera 40. A range on the mounting surface 22 illuminated by infrared rays is referred to as an “illumination range R2”. The illumination range R2 includes the imaging range R1. In the measurement apparatus 10, the two irradiators 50 are in a state in which the illumination ranges on the placement surface 22 by the respective irradiators 50 coincide with each other in the illumination range R2.

  However, the infrared irradiation direction and the number and arrangement of the irradiators 50 as described above are examples. The infrared irradiation direction and the number and arrangement of the irradiators 50 are appropriately determined in consideration of various conditions. For example, the number of irradiators 50 may be one, and the illumination range R2 may be illuminated by one irradiator 50. In addition, the range on the mounting surface 22 illuminated by each of the plurality of irradiators 50 may be different, and the entire illumination range R2 may be illuminated by the plurality of irradiators 50. In addition, the irradiator 50 may be disposed close to the mounting surface 22 on the mounting table 20 so as to illuminate the entire illumination range R2 from the outer peripheral side of the imaging range R1. In this case, the plurality of irradiators 50 may be arranged in a ring shape at the positions described above, or the ring irradiators 50 may be arranged at the positions described above.

  The output device 60 is a device that outputs a unit area mass N as a measurement result. In the measuring apparatus 10, the output device 60 is a display device. A liquid crystal display is illustrated as a display. However, the display employed as the output device 60 may be a display different from the liquid crystal display. That is, in the measuring apparatus 10, an operation screen including the unit area mass N is displayed on the display device as the output device 60. In FIG. 1, the illustration of the operation screen is omitted. The operation screen will be described later.

  The operation device 65 receives input of various instructions to the measurement apparatus 10. In the measuring apparatus 10, the operation device 65 has a specification including a touch pad. In this case, the operation device 65 becomes a touch panel together with the output device 60 which is a display device. The operator of the measurement apparatus 10 performs a predetermined operation on the operation device 65 using the touch pad while the operation screen is displayed on the output device 60. An example of the operation is a tap. The operation device 65 receives an input of an instruction corresponding to an operation by the operator. The operation device 65 outputs the received instruction. However, the operation device 65 may include a predetermined hard key. In addition, the operation device 65 may be a keyboard and a mouse.

  The controller 70 includes a processor 71, a storage 72, a memory 73, and a connection interface 74. In the embodiment, the connection interface 74 is described as “connection I / F 74”. The processor 71 executes arithmetic processing and controls the measuring apparatus 10. The processor 71 is, for example, a CPU.

  The storage 72 is a flash memory. However, the storage 72 may be a storage medium different from the flash memory. For example, the storage 72 may be a hard disk. The storage 72 stores a program. The program stored in the storage 72 includes a program for main processing (see FIG. 4). The main process program includes programs for each process shown in FIGS. The main processing program is installed in the storage 72 in advance.

  The memory 73 becomes a storage area when the processor 71 executes the program stored in the storage 72. In the memory 73, predetermined data is stored in a predetermined storage area during the execution of the process. The memory 73 is, for example, a RAM. In the measuring apparatus 10, in the controller 70, the processor 71 executes a program stored in the storage 72. Along with this, in the measurement apparatus 10, various processes are executed, and functions corresponding to the executed processes are realized.

  For example, the mass meter 30, the camera 40, and the operation device 65 are connected to the connection I / F 74. The mass M output from the mass meter 30 is input to the controller 70 via the connection I / F 74. The mass M from the mass meter 30 is output from the connection I / F 74 to the processor 71. The processor 71 acquires the mass M via the connection I / F 74. An imaging signal corresponding to a captured image captured by the camera 40 is input to the controller 70 via the connection I / F 74. An imaging signal from the camera 40 is output from the connection I / F 74 to the processor 71. The processor 71 acquires an imaging signal via the connection I / F 74. Along with this, the processor 71 acquires imaging data corresponding to the captured image. That is, the processor 71 processes the acquired imaging signal to generate imaging data. The instruction output from the operation device 65 is input to the controller 70 via the connection I / F 74. An instruction from the operation device 65 is output from the connection I / F 74 to the processor 71. The processor 71 acquires the above-described instruction via the connection I / F 74. In addition, the irradiator 50 and the output device 60 are connected to the connection I / F 74. In FIG. 1, illustration of the electrical wiring for connecting the mass meter 30, the camera 40, the irradiator 50, the output device 60 and the connection I / F 74 is omitted.

<Operation screen>
The operation screen will be described with reference to FIGS. In the measurement apparatus 10, the operation screen includes a main screen 80 and a sub screen 90. In the embodiment, when the main screen 80 and the sub screen 90 are not distinguished, or collectively referred to as an operation screen. The main screen 80 is displayed on the output device 60 with the start of the main process. The main screen 80 is an operation screen corresponding to the measurement of the unit area mass N, and is displayed on the output device 60 when the unit area mass N of the dough piece 15 is measured. The sub screen 90 is displayed when the calibration process (see FIGS. 5 and 6) is executed.

The calibration process is performed using the reference sample 17 whose area is set to the reference value. In the embodiment, examples of the reference sample 17 include a first sample, a second sample, a third sample, a fourth sample, and a fifth sample that are set to five types of reference values having different areas. The first sample is the reference sample 17 whose area is set to the first reference value “400 mm ² ”. Examples of the shape whose area is the first reference value include a square having a side dimension of 20 mm. The second sample is the reference sample 17 whose area is set to the second reference value “1600 mm ² ”. The shape whose area is the second reference value is exemplified by a square having a side dimension of 40 mm. The third sample is the reference sample 17 whose area is set to the third reference value “3600 mm ² ”. The shape whose area is the third reference value is exemplified by a square having a side dimension of 60 mm. The fourth sample is the reference sample 17 whose area is set to the fourth reference value “6400 mm ² ”. The shape whose area is the fourth reference value is exemplified by a square having a side dimension of 80 mm. The fifth sample is the reference sample 17 whose area is set to the fifth reference value “10000 mm ² ”. Examples of the shape whose area is the fifth reference value include a square having a side dimension of 100 mm. In the embodiment, when the first sample, the second sample, the third sample, the fourth sample, and the fifth sample are not distinguished or collectively referred to as “reference sample 17”. The above-described values as the first reference value, the second reference value, the third reference value, the fourth reference value, and the fifth reference value are examples. The reference value of the reference sample 17 is appropriately determined in consideration of various conditions. The shape of the reference sample 17 may be a rectangle or a polygon different from a square and a rectangle. Further, the shape of the reference sample 17 may be a circle, an ellipse, or an arbitrary shape different from the above-described shapes. The shape of the reference sample 17 is appropriately determined in consideration of various conditions.

  As in the case of the fabric piece 15, the reference sample 17 may have any or all of the infrared reflectance, the infrared absorption rate, and the infrared transmittance different from the placement surface 22. For example, the reference sample 17 may have an infrared reflectance higher than the placement surface 22, an infrared absorption rate may be lower than the placement surface 22, and an infrared transmittance may be lower than the placement surface 22. For example, the reference sample 17 can be formed of a material that reflects infrared rays from the placement surface 22, or can be in a state of reflecting infrared rays from the placement surface 22, as with the dough piece 15. In addition, the material forming the reference sample 17 may be a material that does not or hardly generates wrinkles or warpage. Further, when the reference sample 17 is formed by cutting a material having an area larger than the reference value, a material that can be easily cut into a shape having an area of the reference value may be selected as the material for forming the reference sample 17. For example, the material forming the reference sample 17 may be a material in which fuzzing does not occur or hardly occurs at the cut portion, or may be a material with low stretchability. For example, the reference sample 17 can be made of paper. In this case, the paper reference sample 17 may have a white surface color.

The main screen 80 includes a preview area 81, a measurement result area 82, and a calibration button 83 (see FIG. 2). The preview area 81 is an area for displaying a captured image corresponding to the imaging range R1. In the measurement apparatus 10, the captured image displayed in the preview area 81 is a moving image. The measurement result area 82 is an area for displaying the unit area mass N (g / m ² ) of the fabric piece 15 and the area (mm ² ) and mass (g) of the fabric piece 15. The calibration button 83 is an operation button for instructing execution of a calibration process (see S17 in FIG. 4, FIGS. 5 and 6). The calibration button 83 is associated with a calibration instruction. The calibration instruction is an instruction to execute calibration processing. When a tap on the calibration button 83 is received by the operation device 65, the processor 71 acquires a calibration instruction. Accordingly, the processor 71 starts calibration processing.

  The sub screen 90 includes a preview area 91, a first sample button 92, a second sample button 93, a third sample button 94, a fourth sample button 95, a fifth sample button 96, and a correction coefficient button 97. And a return button 98 (see FIG. 3). The preview area 91 is an area for displaying a captured image corresponding to the imaging range R1. In the measurement apparatus 10, the captured image displayed in the preview area 91 is a moving image.

  The first sample button 92 is an operation button for instructing execution of the first calibration imaging process (see S35 in FIG. 5). The first sample button 92 is associated with the first sample instruction. The first sample instruction is an instruction to execute the first calibration imaging process. The operator places the first sample on the mounting table 20. Thereafter, the operator taps the first sample button 92 in a state where the first sample is placed on the mounting table 20. It is assumed that the first sample button 92 is tapped and this tap is received by the operation device 65. In this case, the processor 71 acquires the first sample instruction. Accordingly, the processor 71 starts the first calibration imaging process.

  The second sample button 93 is an operation button for instructing execution of the second calibration imaging process (see S41 in FIG. 5). The second sample button 93 is associated with the second sample instruction. The second sample instruction is an instruction to execute the second calibration imaging process. The operator places the second sample on the mounting table 20. Thereafter, the operator taps the second sample button 93 in a state where the second sample is placed on the placing table 20. It is assumed that the second sample button 93 is tapped and this tap is received by the operation device 65. In this case, the processor 71 acquires the second sample instruction. Accordingly, the processor 71 starts the second calibration imaging process.

  The third sample button 94 is an operation button for instructing execution of the third calibration imaging process (see S47 in FIG. 5). The third sample button 94 is associated with a third sample instruction. The third sample instruction is an instruction to execute the third calibration imaging process. The operator places the third sample on the placing table 20. Thereafter, the operator taps the third sample button 94 in a state where the third sample is placed on the mounting table 20. It is assumed that the third sample button 94 is tapped and this tap is received by the operation device 65. In this case, the processor 71 obtains a third sample instruction. Accordingly, the processor 71 starts the third calibration imaging process.

  The fourth sample button 95 is an operation button for instructing execution of the fourth calibration imaging process (see S53 in FIG. 6). The fourth sample button 95 is associated with the fourth sample instruction. The fourth sample instruction is an instruction to execute the fourth calibration imaging process. The operator places the fourth sample on the placing table 20. Thereafter, the operator taps the fourth sample button 95 in a state where the fourth sample is placed on the placing table 20. It is assumed that the fourth sample button 95 is tapped and this tap is received by the operation device 65. In this case, the processor 71 acquires the fourth sample instruction. Accordingly, the processor 71 starts the fourth calibration imaging process.

  The fifth sample button 96 is an operation button for instructing execution of the fifth calibration imaging process (see S59 in FIG. 6). The fifth sample button 96 is associated with the fifth sample instruction. The fifth sample instruction is an instruction to execute the fifth calibration imaging process. The operator places the fifth sample on the placing table 20. Thereafter, the operator taps the fifth sample button 96 in a state where the fifth sample is placed on the placing table 20. It is assumed that the fifth sample button 96 is tapped and this tap is received by the operation device 65. In this case, the processor 71 acquires the fifth sample instruction. Accordingly, the processor 71 starts the fifth calibration imaging process.

  The correction coefficient button 97 is an operation button for instructing execution of correction coefficient processing (see S65 in FIG. 6 and FIG. 14). The correction coefficient button 97 is associated with a correction coefficient instruction. The correction coefficient instruction is an instruction to execute correction coefficient processing. For example, the operator taps the first sample button 92, the second sample button 93, the third sample button 94, the fourth sample button 95, and the fifth sample button 96, and then taps the correction coefficient button 97. It is assumed that the correction coefficient button 97 is tapped and this tap is received by the operation device 65. In this case, the processor 71 acquires a correction coefficient instruction. Accordingly, the processor 71 starts correction coefficient processing.

  The return button 98 is an operation button for instructing the end of the calibration process. The return button 98 is associated with a return instruction. The return instruction is an instruction to end the calibration process. For example, the operator taps the return button 98 when ending the calibration process. It is assumed that the return button 98 is tapped and this tap is received by the operation device 65. In this case, the processor 71 acquires a return instruction. Accordingly, the processor 71 ends the calibration process.

<Main processing>
The main process will be described with reference to FIG. The operator turns on the power of the measuring apparatus 10. Along with this, the processor 71 starts a main processing program stored in the storage 72 and starts the main processing. The irradiator 50 starts infrared irradiation.

  The processor 71 that has started the main process displays the main screen 80 (S11). The processor 71 outputs a display command for the main screen 80 to the output device 60. The output device 60 displays the main screen 80 in accordance with this display command (see the upper part of FIG. 2). The processor 71 activates the camera 40 in accordance with the execution of S11 (S13). The processor 71 outputs a start command to the camera 40. The camera 40 is activated in accordance with the activation command and starts imaging. The processor 71 acquires imaging data corresponding to the captured image captured by the camera 40. The processor 71 includes a captured image corresponding to the above-described captured data in the preview area 81 of the main screen 80. On the main screen 80, a captured image that matches the imaging range R1 is output to the preview area 81 (see FIG. 2). About the order of S11 and S13, you may perform S11 after performing S13.

  Next, the processor 71 determines whether or not a calibration instruction has been acquired (S15). The operator taps the calibration button 83. It is assumed that the tap of the calibration button 83 is received by the operation device 65. In this case, the processor 71 acquires a calibration instruction from the operation device 65. When the calibration instruction is acquired (S15: Yes), the processor 71 executes a calibration process (S17). The calibration process is a process for acquiring a correction coefficient. The calibration process and the correction coefficient will be described later. In the calibration process, the operation screen is switched from the main screen 80 to the sub screen 90. After executing S17, the processor 71 displays the main screen 80 (S19). S19 is executed in the same manner as S11. Therefore, the other description regarding S19 is abbreviate | omitted. After executing S19, the processor 71 returns the process to S15. Thereafter, the processor 71 repeatedly executes the processes after S15.

  When the calibration instruction has not been acquired (S15: No), the processor 71 executes mass processing (S21). The mass process is a process for obtaining the mass M of the dough piece 15 measured by the mass meter 30. The operator places the dough piece 15 on the placing table 20. The mass meter 30 measures the mass M of the dough piece 15 placed on the mounting table 20. In S <b> 21, the processor 71 acquires the mass M of the dough piece 15 measured by the mass meter 30. The processor 71 stores the mass M in the memory 73. The processor 71 acquires the value from the mass meter 30 as the mass M when the value from the mass meter 30 is greater than 0 and the value indicates a constant value for the set time. The set time is appropriately determined in consideration of various conditions. For example, the next time obtained by a prior experiment may be set as the set time. The above-described time is the time required for the mass M measured by the mass meter 30 to stabilize after placing the dough piece 15 on the mounting table 20.

  Subsequently, the processor 71 executes measurement imaging processing (S23). The imaging process for measurement is a process for acquiring imaging data for measurement. In the embodiment, the imaging data for measurement is referred to as “imaging data for measurement”. The measurement imaging data is image data including an image portion of the fabric piece 15 captured by the camera 40. Furthermore, the measurement imaging data is image data corresponding to an infrared image in which the infrared rays from the irradiator 50 are reflected by the fabric piece 15 on the mounting table 20. In the measurement apparatus 10, the measurement imaging data is still image data. In S <b> 23, the processor 71 outputs an imaging command to the camera 40. The camera 40 images the imaging range R1 according to the imaging command. The processor 71 acquires measurement imaging data corresponding to the captured image captured by the camera 40. The processor 71 stores the measurement imaging data in the memory 73. Regarding the order of S21 and S23, S21 may be executed after executing S23. However, the processor 71 may execute S23 on the condition that the value from the mass meter 30 is greater than 0 and the value indicates a constant value for the set time.

  After executing S23, the processor 71 executes measurement area processing (S25). The measurement area process is a process of acquiring the measurement area A of the region corresponding to the fabric piece 15 from the image portion of the fabric piece 15 included in the measurement imaging data acquired in S23. The measurement area process will be described later.

  Next, the processor 71 executes a calculation process (S27). The calculation process is a process of calculating a unit area mass N based on the mass M acquired in S21 and the measurement area A acquired in S25. In the calculation process, the measurement area A is corrected by a polynomial approximation curve including a correction coefficient (see S163 in FIG. 14), the mass M acquired in S21 is divided by the corrected correction area B, and the unit area mass N Is calculated. In the embodiment, the order of the above-described polynomial approximate curve is fourth.

The calculation process executed in S27 will be further described. The processor 71 obtains the measurement area A and the correction coefficient from the memory 73, and calculates the correction factor J by Expression (1). The measurement area A is stored in the memory 73 in S73 of FIG. The correction coefficient is stored in the memory 73 in S163 of FIG. In addition, the processor 71 calculates the correction area B by Expression (2). Thereby, the processor 71 acquires the unit area mass N by the equation (3).
J = Coeff ⁴ × A ⁴ + Coeff ³ × A ³ + Coeff ² × A ² + Coeff 1 × A + Coeff 0 (1)
B = (J + 1) × A (2)
N = M / B (3)
When the calibration process (see FIGS. 5 and 6) is not executed in S17, the correction area B is the same value as the measurement area A in S27. Therefore, the expression (3) is substantially “N = M / A”. The correction factor J or the correction coefficient stored in the memory 73 in S163 of FIG. 14 to be described later may be registered in the main processing program, for example. When S17 is not executed and the correction coefficient is not stored in the memory 73 after starting the currently executed main process (S163 in FIG. 14: not executed), the processor 71, in S35, registers the correction factor J or Use correction factors. The initial value of the correction factor J registered in the main processing program is set to zero. When the correction factor J is calculated by the equation (2), the processor 71 updates the correction factor J registered in the main processing program to the newly calculated correction factor J.

  Subsequently, the processor 71 executes output processing (S29). The output process is a process for causing the output device 60 to output the unit area mass N acquired in S27. In the embodiment, the correction area B and the mass M are output together with the unit area mass N. The processor 71 outputs an output command of the unit area mass N, the correction area B, and the mass M to the output device 60. The output device 60 outputs the unit area mass N, the correction area B, and the mass M in accordance with the output command. That is, the output device 60 displays the main screen 80 including the unit area mass N, the correction area B, and the mass M as measurement results in the measurement result region 82 (see the lower part of FIG. 2). After executing S29, the processor 71 returns the process to S15. Thereafter, the processor 71 repeatedly executes the processes after S15. The main process ends when the power of the measuring apparatus 10 is turned off. Irradiation of infrared rays from the irradiator 50 is continued until the power of the measuring apparatus 10 is turned off.

<Calibration process>
The calibration process executed in S17 of FIG. 4 will be described with reference to FIGS. The processor 71 having started the calibration process displays the sub screen 90 (S31). The processor 71 outputs a display command for the sub screen 90 to the output device 60. The output device 60 displays the sub screen 90 in accordance with this display command (see FIG. 3).

  Next, the processor 71 determines whether or not a first sample instruction has been acquired (S33). The operator taps the first sample button 92. However, it is assumed that the first sample is not set on the mounting table 20 and the first sample is not displayed in the preview area 91. In this case, the operator places the first sample on the mounting table 20 when tapping the first sample button 92. It is assumed that the tap of the first sample button 92 is received by the operation device 65. In this case, the processor 71 acquires the first sample instruction from the operation device 65.

  When the first sample instruction has not been acquired (S33: No), the processor 71 shifts the processing to S39. When the first sample instruction is acquired (S33: Yes), the processor 71 executes a first calibration imaging process (S35). The first calibration imaging process is a process of acquiring the next calibration imaging data. In the embodiment, the above-described calibration imaging data is referred to as “first calibration imaging data”. The first calibration imaging data is image data including an image portion of the first sample imaged by the camera 40. Further, the first calibration imaging data is image data corresponding to an infrared image in which infrared rays from the irradiator 50 are reflected by the first sample on the mounting table 20. In the measurement apparatus 10, the first calibration imaging data is still image data. In S <b> 35, the processor 71 outputs an imaging command to the camera 40. The camera 40 images the imaging range R1 according to the imaging command. The processor 71 acquires first calibration imaging data corresponding to the captured image captured by the camera 40. The processor 71 stores the first calibration imaging data in the memory 73.

  Subsequently, the processor 71 executes first calibration area processing (S37). The first calibration area process is a process of acquiring the area of the region corresponding to the first sample from the image portion of the first sample included in the first calibration imaging data acquired in S35. In the embodiment, the above-described area acquired by the first calibration area process is referred to as “first calibration area X1”. The first calibration area process will be described later. After executing S37, the processor 71 returns the process to S33. Thereafter, the processor 71 repeatedly executes the processes after S33.

  In S39, the processor 71 determines whether or not a second sample instruction has been acquired. The operator taps the second sample button 93. However, it is assumed that the second sample is not set on the mounting table 20 and the second sample is not displayed in the preview area 91. In this case, the operator places the second sample on the mounting table 20 when tapping the second sample button 93. It is assumed that the tap of the second sample button 93 is received by the operation device 65. In this case, the processor 71 acquires the second sample instruction from the operation device 65.

  When the second sample instruction has not been acquired (S39: No), the processor 71 shifts the processing to S45. When the second sample instruction is acquired (S39: Yes), the processor 71 executes the second calibration imaging process (S41). The second calibration imaging process is a process of acquiring the next calibration imaging data. In the embodiment, the above-described calibration imaging data is referred to as “second calibration imaging data”. The second calibration imaging data is image data including an image portion of the second sample imaged by the camera 40. Further, the second calibration imaging data is image data corresponding to an infrared image in which infrared rays from the irradiator 50 are reflected by the second sample on the mounting table 20. In the measurement apparatus 10, the second calibration imaging data is still image data. In S <b> 41, the processor 71 outputs an imaging command to the camera 40. The camera 40 images the imaging range R1 according to the imaging command. The processor 71 acquires second calibration imaging data corresponding to the captured image captured by the camera 40. The processor 71 stores the second calibration imaging data in the memory 73.

  Subsequently, the processor 71 executes second calibration area processing (S43). The second calibration area process is a process of acquiring the area of the region corresponding to the second sample from the image portion of the second sample included in the second calibration imaging data acquired in S41. In the embodiment, the above-described area acquired by the second calibration area process is referred to as “second calibration area X2”. The second calibration area process will be described later. After executing S43, the processor 71 returns the process to S33. Thereafter, the processor 71 repeatedly executes the processes after S33.

  In S45, the processor 71 determines whether or not a third sample instruction has been acquired. The operator taps the third sample button 94. However, it is assumed that the third sample is not set on the mounting table 20 and the third sample is not displayed in the preview area 91. In this case, the operator places the third sample on the mounting table 20 when tapping the third sample button 94. It is assumed that the tap of the third sample button 94 is received by the operation device 65. In this case, the processor 71 acquires a third sample instruction from the operation device 65.

  When the third sample instruction has not been acquired (S45: No), the processor 71 shifts the processing to S51 of FIG. When the third sample instruction is acquired (S45: Yes), the processor 71 executes the third calibration imaging process (S47). The third calibration imaging process is a process of acquiring the next calibration imaging data. In the embodiment, the above-described calibration imaging data is referred to as “third calibration imaging data”. The third calibration imaging data is image data including the image portion of the third sample imaged by the camera 40. Further, the third calibration imaging data is image data corresponding to an infrared image in which the infrared rays from the irradiator 50 are reflected by the third sample on the mounting table 20. In the measuring apparatus 10, the third calibration imaging data is still image data. In S47, the processor 71 outputs an imaging command to the camera 40. The camera 40 images the imaging range R1 according to the imaging command. The processor 71 acquires third calibration imaging data corresponding to the captured image captured by the camera 40. The processor 71 stores the third calibration imaging data in the memory 73.

  Subsequently, the processor 71 executes third calibration area processing (S49). The third calibration area process is a process of acquiring the area of the region corresponding to the third sample from the image portion of the third sample included in the third calibration imaging data acquired in S47. In the embodiment, the above-described area acquired by the third calibration area process is referred to as “third calibration area X3”. The third calibration area process will be described later. After executing S49, the processor 71 returns the process to S33. Thereafter, the processor 71 repeatedly executes the processes after S33.

  In S51 of FIG. 6, the processor 71 determines whether or not a fourth sample instruction has been acquired. The operator taps the fourth sample button 95. However, it is assumed that the fourth sample is not set on the mounting table 20 and the fourth sample is not displayed in the preview area 91. In this case, the operator places the fourth sample on the mounting table 20 when tapping the fourth sample button 95. It is assumed that the tap of the fourth sample button 95 is received by the operation device 65. In this case, the processor 71 acquires the fourth sample instruction from the operation device 65.

  When the fourth sample instruction has not been acquired (S51: No), the processor 71 shifts the processing to S57. When the fourth sample instruction is acquired (S51: Yes), the processor 71 executes a fourth calibration imaging process (S53). The fourth calibration imaging process is a process of acquiring the next calibration imaging data. In the embodiment, the above-described calibration imaging data is referred to as “fourth calibration imaging data”. The fourth calibration imaging data is image data including an image portion of the fourth sample imaged by the camera 40. Further, the fourth calibration imaging data is image data corresponding to an infrared image in which the infrared light from the irradiator 50 is reflected by the fourth sample on the mounting table 20. In the measurement apparatus 10, the fourth calibration imaging data is still image data. In S <b> 53, the processor 71 outputs an imaging command to the camera 40. The camera 40 images the imaging range R1 according to the imaging command. The processor 71 acquires fourth calibration imaging data corresponding to the captured image captured by the camera 40. The processor 71 stores the fourth calibration imaging data in the memory 73.

  Subsequently, the processor 71 executes a fourth calibration area process (S55). The fourth calibration area process is a process of acquiring the area of the region corresponding to the fourth sample from the image portion of the fourth sample included in the fourth calibration imaging data acquired in S53. In the embodiment, the aforementioned area acquired by the fourth calibration area process is referred to as “fourth calibration area X4”. The fourth calibration area process will be described later. After executing S55, the processor 71 returns the process to S33 of FIG. Thereafter, the processor 71 repeatedly executes the processes after S33.

  In S57, the processor 71 determines whether or not a fifth sample instruction has been acquired. The operator taps the fifth sample button 96. However, it is assumed that the fifth sample is not set on the mounting table 20 and the fifth sample is not displayed in the preview area 91. In this case, the operator places the fifth sample on the mounting table 20 when tapping the fifth sample button 96. It is assumed that the tap of the fifth sample button 96 is received by the operation device 65. In this case, the processor 71 acquires the fifth sample instruction from the operation device 65.

  When the fifth sample instruction has not been acquired (S57: No), the processor 71 shifts the processing to S63. When the fifth sample instruction is acquired (S57: Yes), the processor 71 executes a fifth calibration imaging process (S59). The fifth calibration imaging process is a process of acquiring the next calibration imaging data. In the embodiment, the above-described calibration imaging data is referred to as “fifth calibration imaging data”. The fifth calibration imaging data is image data including the image portion of the fifth sample imaged by the camera 40. Further, the fifth calibration imaging data is image data corresponding to an infrared image in which the infrared rays from the irradiator 50 are reflected by the fifth sample on the mounting table 20. In the measuring apparatus 10, the fifth calibration imaging data is still image data. In S <b> 53, the processor 71 outputs an imaging command to the camera 40. The camera 40 images the imaging range R1 according to the imaging command. The processor 71 acquires fifth calibration imaging data corresponding to the captured image captured by the camera 40. The processor 71 stores the fifth calibration imaging data in the memory 73.

  Subsequently, the processor 71 executes a fifth calibration area process (S61). The fifth calibration area process is a process of acquiring the area of the region corresponding to the fifth sample from the image portion of the fifth sample included in the fifth calibration imaging data acquired in S59. In the embodiment, the above-mentioned area acquired by the fifth calibration area process is referred to as “fifth calibration area X5”. The fifth calibration area process will be described later. After executing S61, the processor 71 returns the process to S33 of FIG. Thereafter, the processor 71 repeatedly executes the processes after S33.

  In S63, the processor 71 determines whether a correction coefficient instruction has been acquired. The operator taps the correction coefficient button 97. It is assumed that the tap of the correction coefficient button 97 is received by the operation device 65. In this case, the processor 71 acquires a correction coefficient instruction from the operation device 65.

When the correction coefficient instruction has not been acquired (S63: No), the processor 71 shifts the processing to S67. When the correction coefficient instruction is acquired (S63: Yes), the processor 71 executes a correction coefficient process (S65). The correction coefficient process is a process for calculating a correction coefficient corresponding to the first difference value, the second difference value, the third difference value, the fourth difference value, and the fifth difference value. The first difference value is a difference between the first reference value (400 mm ² ) and the first calibration area X1. The second difference value is a difference between the second reference value (1600 mm ² ) and the second calibration area X2. The third difference value is a difference between the third reference value (3600 mm ² ) and the third calibration area X3. The fourth difference value is a difference between the fourth reference value (6400 mm ² ) and the fourth calibration area X4. The fifth difference value is a difference between the fifth reference value (10000 mm ² ) and the fifth calibration area X5. In the correction coefficient processing, the coefficient of the fourth-order polynomial used in S27 of FIG. 3 (see the above formula (1)) is acquired by the Gaussian elimination method. The correction coefficient process will be described later. Thereafter, the processor 71 ends the calibration process.

  In S67, the processor 71 determines whether or not a return instruction has been acquired. When the return instruction has not been acquired (S67: No), the processor 71 returns the process to S33 of FIG. Thereafter, the processor 71 repeatedly executes the processes after S33. When the return instruction is acquired (S67: Yes), the processor 71 ends the calibration process.

<Measurement area treatment>
The measurement area process executed in S25 of FIG. 4 will be described with reference to FIG. The processor 71 that has started the measurement area process executes an actual measurement process (S71). The measurement area A that is acquired in the measurement area process is acquired by the actual measurement process executed in S71. The actual measurement process will be described later. After executing S71, the processor 71 stores the measurement area A acquired in the actual measurement process in the memory 73 (S73). Thereafter, the processor 71 ends the measurement area process.

<Area processing for first calibration>
The first calibration area process executed in S37 of FIG. 5 will be described with reference to FIG. The processor 71 that has started the first calibration area process executes an actual measurement process (S81). The first calibration area X1 that is acquired in the first calibration area process is acquired by the actual measurement process executed in S81. The actual measurement process will be described later. After executing S81, the processor 71 stores the first calibration area X1 acquired in the actual measurement process in the memory 73 (S83). Thereafter, the processor 71 ends the first calibration area process.

<Second calibration area treatment>
The second calibration area process executed in S43 of FIG. 5 will be described with reference to FIG. The processor 71 that has started the second calibration area process executes an actual measurement process (S91). The second calibration area X2 acquired in the second calibration area process is acquired by the actual measurement process executed in S91. The actual measurement process will be described later. After executing S91, the processor 71 stores the second calibration area X2 acquired in the actual measurement process in the memory 73 (S93). Thereafter, the processor 71 ends the second calibration area process.

<Third calibration area processing>
The third calibration area process executed in S49 of FIG. 5 will be described with reference to FIG. The processor 71 that has started the third calibration area process executes an actual measurement process (S101). The third calibration area X3 that is acquired in the third calibration area process is acquired by the actual measurement process executed in S101. The actual measurement process will be described later. After executing S101, the processor 71 stores the third calibration area X3 acquired in the actual measurement process in the memory 73 (S103). Thereafter, the processor 71 ends the third calibration area process.

<Fourth calibration area treatment>
The fourth calibration area process executed in S55 of FIG. 6 will be described with reference to FIG. The processor 71 that has started the fourth calibration area process executes an actual measurement process (S111). The fourth calibration area X4 that is acquired in the fourth calibration area process is acquired by the actual measurement process executed in S111. The actual measurement process will be described later. After executing S111, the processor 71 stores the fourth calibration area X4 acquired in the actual measurement process in the memory 73 (S113). Thereafter, the processor 71 ends the fourth calibration area process.

<Fifth calibration area treatment>
The fifth calibration area process executed in S61 of FIG. 6 will be described with reference to FIG. The processor 71 that has started the fifth calibration area process executes an actual measurement process (S121). The fifth calibration area X5 obtained in the fifth calibration area process is acquired by the actual measurement process executed in S121. The actual measurement process will be described later. After executing S121, the processor 71 stores the fifth calibration area X5 acquired in the actual measurement process in the memory 73 (S123). Thereafter, the processor 71 ends the fifth calibration area process.

<Measurement process>
The actual measurement processing executed in S71 of FIG. 7, S81 of FIG. 8, S91 of FIG. 9, S101 of FIG. 10, S111 of FIG. 11, and S121 of FIG. 12 will be described with reference to FIG. In the embodiment, when measurement imaging data, first calibration imaging data, second calibration imaging data, third calibration imaging data, fourth calibration imaging data, and fifth calibration imaging data are not distinguished, or these Are collectively referred to as “imaging data”. When the dough piece 15 and the first sample, the second sample, the third sample, the fourth sample, and the fifth sample as the reference sample 17 are not distinguished from each other or are collectively referred to, they are referred to as “detected objects”. When the measurement area A, the first calibration area X1, the second calibration area X2, the third calibration area X3, the fourth calibration area X4, and the fifth calibration area X5 are not distinguished or are collectively referred to. , Simply referred to as “area” or “area of the object to be detected”.

  Therefore, when the actual measurement process is executed in S71 of FIG. 7, the imaging data indicates the measurement imaging data during the description of the actual measurement process. In this case, the area detected by the actual measurement process is the image portion of the fabric piece 15 included in the measurement imaging data, and the area is the measurement area A. When the actual measurement process is performed in S81 of FIG. 8, during the description of the actual measurement process, the imaging data indicates the first calibration imaging data. In this case, the region detected by the actual measurement process is the image portion of the first sample as the reference sample 17 included in the first calibration imaging data, and the area is the first calibration area X1. When the actual measurement process is performed in S91 of FIG. 9, during the description of the actual measurement process, the imaging data indicates the second calibration imaging data. In this case, the region detected by the actual measurement process is the image portion of the second sample as the reference sample 17 included in the second calibration imaging data, and the area is the second calibration area X2. When the actual measurement process is performed in S101 of FIG. 10, during the description of the actual measurement process, the imaging data indicates the third calibration imaging data. In this case, the region detected by the actual measurement process is the image portion of the third sample as the reference sample 17 included in the third calibration imaging data, and the area is the third calibration area X3. When the actual measurement process is executed in S111 of FIG. 11, during the description of the actual measurement process, the imaging data indicates the fourth calibration imaging data. In this case, the region detected by the actual measurement process is the image portion of the fourth sample as the reference sample 17 included in the fourth calibration imaging data, and the area is the fourth calibration area X4. When the actual measurement process is performed in S121 of FIG. 12, during the description of the actual measurement process, the imaging data indicates the fifth calibration imaging data. In this case, the region detected by the actual measurement process is the image portion of the fifth sample as the reference sample 17 included in the fifth calibration imaging data, and the area is the fifth calibration area X5.

  The processor 71 that has started the actual measurement process executes the binarization process using the imaging data as a processing target (S131). The binarization process is a process for binarizing imaging data. By the binarization process, the imaging data is converted into two-tone image data of white and black. The binarization process is a well-known image process that has already been put into practical use. Therefore, the other description regarding S131 is abbreviate | omitted.

  Subsequently, the processor 71 executes the closing process on the imaging data processed in S131 as a processing target (S133). The closing process is a process of executing the expansion process a predetermined number of times and then repeating the contraction process the same number of times as the expansion process. The expansion process is a process of converting black pixels adjacent to the periphery (top, bottom, left and right) of white pixels into white pixels. The contraction process is a process of converting white pixels adjacent to the periphery (up / down / left / right) of a black pixel into black pixels. The closing process, the expansion process, and the contraction process are known image processes that have already been put into practical use. Therefore, the other description regarding S133 is omitted.

  Next, the processor 71 executes a labeling process on the imaging data processed in S133 as a processing target (S135). The labeling process is a process for assigning different labels to black pixels and white pixels. According to the labeling process, among the pixels forming the captured image corresponding to the captured data, the next first pixel is labeled differently from the next second pixel. The first pixel is a pixel that forms an image portion of the detected object included in the imaging data. Taking the case where the object to be detected is a fabric piece 15 as an example, the first pixel is a black image portion in the measurement imaging data after the labeling process of the first aspect shown on the right side of the upper stage of FIG. (Refer to the portion indicated by the reference numeral “15” in the image data). The second pixel is a pixel that forms an image portion excluding the detected object included in the imaging data. In other words, the second pixel is a pixel other than the first pixel among the pixels that form the captured image corresponding to the captured data. For example, when the object to be detected is an object whose shape has a shape whose reference value is the area itself, the second pixel is a pixel that forms an image portion of the mounting surface 22 in the next range included in the imaging data. . The aforementioned range is the range of the mounting surface 22 in the imaging range R1 that is exposed without being covered by the detection object. The labeling process is a known image process that has already been put into practical use. Therefore, the other description regarding S135 is omitted.

After executing S135, the processor 71 acquires the area of the object to be detected (S137). Although not described above, the area value per pixel is registered in the actual measurement processing program included in the main processing program. In S137, the processor 71 specifies the number of the first pixels described above. The processor 71 obtains the area of the detected object based on the product of the specified number and the above-described area value. For example, it is assumed that the number of first pixels is C and the area value per pixel is Dmm ² / pixel. In this case, the processor 71 acquires the value obtained by “C × D” as the area of the detected object. Thereafter, the processor 71 ends the actual measurement process.

<Correction coefficient processing>
The correction coefficient process executed in S65 of FIG. 6 will be described with reference to FIG. The processor 71 that has started the correction coefficient processing acquires the first calibration area X1 from the memory 73 (S141). The first calibration area X1 is stored in the memory 73 in S83 of FIG. Subsequently, the processor 71 acquires the first correction value Y1 (S143). The first correction value Y1 is calculated by the following equation (4). In equation (4), the value “400 mm ² ” corresponds to the first reference value of 400 mm ² . The processor 71 acquires the calculated value as the first correction value Y1. The processor 71 stores the first correction value Y1 in the memory 73.
Y1 = (400−X1) / X1 (4)
After executing S143, the processor 71 acquires the second calibration area X2 from the memory 73 (S145). The second calibration area X2 is stored in the memory 73 in S93 of FIG. Subsequently, the processor 71 acquires the second correction value Y2 (S147). The second correction value Y2 is calculated by the following equation (5). The value “1600 mm ² ” in Equation (5) corresponds to the second reference value of 1600 mm ² . The processor 71 acquires the calculated value as the second correction value Y2. The processor 71 stores the second correction value Y2 in the memory 73.
Y2 = (1600−X2) / X2 (5)
After executing S147, the processor 71 acquires the third calibration area X3 from the memory 73 (S149). The third calibration area X3 is stored in the memory 73 in S103 of FIG. Subsequently, the processor 71 acquires a third correction value Y3 (S151). The third correction value Y3 is calculated by the following equation (6). The value “3600 mm ² ” in Equation (6) corresponds to the third reference value 3600 mm ² . The processor 71 acquires the calculated value as the third correction value Y3. The processor 71 stores the third correction value Y3 in the memory 73.
Y3 = (3600−X3) / X3 (6)
After executing S151, the processor 71 acquires the fourth calibration area X4 from the memory 73 (S153). The fourth calibration area X4 is stored in the memory 73 in S113 of FIG. Subsequently, the processor 71 acquires a fourth correction value Y4 (S155). The fourth correction value Y4 is calculated by the following equation (7). The value “6400 mm ² ” in Expression (7) corresponds to the fourth reference value 6400 mm ² . The processor 71 acquires the calculated value as the fourth correction value Y4. The processor 71 stores the fourth correction value Y4 in the memory 73.
Y4 = (6400−X4) / X4 (7)
After executing S155, the processor 71 acquires the fifth calibration area X5 from the memory 73 (S157). The fifth calibration area X5 is stored in the memory 73 in S123 of FIG. Subsequently, the processor 71 acquires the fifth correction value Y5 (S159). The fifth correction value Y5 is calculated by the following equation (8). In formula (8), the value “10000 mm ² ” corresponds to the fifth reference value 10000 mm ² . The processor 71 acquires the calculated value as the fifth correction value Y5. The processor 71 stores the fifth correction value Y5 in the memory 73.
Y5 = (10000−X5) / X5 (8)
Next, the processor 71 calculates a correction coefficient (S161). A Gaussian elimination method is used to calculate the correction coefficient. In the Gaussian elimination method, the first calibration area X1, the second calibration area X2, the third calibration area X3, the fourth calibration area X4, and the fifth calibration area X5 are used as input values of the matrix X. The first correction value Y1, the second correction value Y2, the third correction value Y3, the fourth correction value Y4, and the fifth correction value Y5 are used as input values of the matrix Y. Here, in S161, a predetermined function in a known program is appropriately used. In the embodiment, a fourth-order array is calculated as a correction coefficient by the Gaussian elimination method. That is, in S161, a fourth-order correction coefficient is calculated.

  Subsequently, the processor 71 stores the correction coefficient “Coeff [5] = xx [5]” calculated in S161 in the memory 73 (S163). Coeff [5] includes [Coeff0, Coeff1, Coeff2, Coeff3, Coeff4] (0th, 1st, 2nd, 3rd, 4th) as correction coefficients. The matrix xx [5] has a value corresponding to [Coeff0, Coeff1, Coeff2, Coeff3, Coeff4] [xx0, xx1, xx2, xx3, xx4] (0th order, first order, second order, third order, fourth order). ). After executing S163, the processor 71 ends the correction coefficient processing.

<Example>
The inventor has performed the above-described calibration processing using a measuring device corresponding to the measuring device 10 this time. This will be described. The reference sample 17 was the same as the first sample, the second sample, the third sample, the fourth sample, and the fifth sample described above.

In the first calibration area process (see FIG. 8) for the first sample (first reference value: 400 mm ² ), the first calibration area X1 “389.6 mm ² ” is acquired in the actual measurement process of S81. (See S137 in FIG. 13), and the above-described value is stored as the first calibration area X1 (see S83 in FIG. 8).

In the second calibration area process (see FIG. 9) for the second sample (second reference value: 1600 mm ² ), the second calibration area X2 “1588.9 mm ² ” is acquired in the actual measurement process of S91. (See S137 in FIG. 13), and the above-mentioned value is stored as the second calibration area X2 (see S93 in FIG. 9).

In the third calibration area process (see FIG. 10) for the third sample (third reference value: 3600 mm ² ), the third calibration area X3 “3599.5 mm ² ” is acquired in the actual measurement process of S101. (See S137 in FIG. 13), and the above-mentioned value is stored as the third calibration area X3 (see S103 in FIG. 10).

In the fourth calibration area process (see FIG. 11) for the fourth sample (fourth reference value: 6400 mm ² ), the fourth calibration area X4 “6334.8 mm ² ” is acquired in the actual measurement process of S111. (See S137 in FIG. 13), and the above-mentioned value is stored as the fourth calibration area X4 (see S113 in FIG. 11).

In the fifth calibration area process (see FIG. 12) for the fifth sample (fifth reference value: 10000 mm ² ), the fifth calibration area X5 “9975.9 mm ² ” is acquired in the actual measurement process of S121. (See S137 in FIG. 13), and the above-described value is stored as the fifth calibration area X5 (see S123 in FIG. 12).

In the correction coefficient process (FIG. 14), the following values were acquired as the first correction value Y1, the second correction value Y2, the third correction value Y3, the fourth correction value Y4, and the fifth correction value Y5. That is, in S143, the first correction value Y1 “0.026694045” is acquired from the above-described equation (4). The first difference value (400−X1) was 10.4 mm ² . In S147, the second correction value Y2 “0.006985965” is acquired from the above-described equation (5). The second difference value (1600−X2) was 11.1 mm ² . In S151, the third correction value Y3 “0.000138908” is acquired from the above-described equation (6). The third difference value (3600−X3) was 0.5 mm ² . In S <b> 155, the fourth correction value Y <b> 4 “0.0039530665” is acquired from the above-described equation (7). The fourth difference value (6400−X4) was 25.2 mm ² . In S <b> 159, the fifth correction value Y <b> 5 “0.0024158822” is acquired from the above-described equation (8). The fifth difference value (10000−X5) was 24.1 mm ² .

In the correction coefficient processing, the following correction coefficients are calculated by the Gaussian elimination method using each value as described above, and the calculated correction coefficients are stored (see S161 and S163 in FIG. 14). In this case, the above-described equation (1) becomes the following equation (9).
Coeff0 = 0.0372790078891326000000000
Coeff1 = 0.0000303485836542386000000
Coeff2 = 0.0000000085293095598340900
Coeff3 = 0.0000000000009581917945669
Coeff4 = 0.0000000000000000373938979
J = 0.0000000000000000373938979 × A ⁴ + 0.0000000000009581917945669 × A ³ + 0.0000000085293095598340900 × A ² + 0.0000303485836542386000000 × A + 0.0372790078891326000000000 (9)
<Effect of embodiment>
According to the embodiment, the following effects can be obtained.

  (1) The measuring apparatus 10 includes a mounting table 20, a mass meter 30, a camera 40, an output device 60, and a controller 70 (see FIG. 1). The controller 70 includes a processor 71. In the measuring apparatus 10, the processor 71 executes main processing (see FIG. 4). In the main processing, the processor 71 executes mass processing, measurement imaging processing, measurement area processing, calculation processing, and output processing (see S21 to S29 in FIG. 4). In other words, the processor 71 acquires the mass M of the dough piece 15 measured by the mass meter 30 in the mass processing. In the measurement imaging process, the processor 71 acquires measurement imaging data including the image portion of the fabric piece 15 captured by the camera 40. In the measurement area processing, the processor 71 acquires the measurement area A of the region corresponding to the fabric piece 15 from the image portion of the fabric piece 15 included in the measurement imaging data (see S71 in FIG. 7 and S137 in FIG. 13). . In the calculation process, the processor 71 calculates the unit area mass N from the mass M and the measurement area A. In the output process, the processor 71 causes the output unit 60 to output the unit area mass N.

  Therefore, the unit area mass N of the dough piece 15 can be measured and output as a measurement result. That is, the output device 60 can display the unit area mass N in the measurement result area 82 of the main screen 80 (see the lower part of FIG. 2). By obtaining the measurement area A of the region corresponding to the fabric piece 15 from the image portion of the fabric piece 15 included in the measurement imaging data, the unit area mass N can be measured regardless of the shape of the fabric piece 15. it can. For example, when measuring the unit area mass N, it is not necessary to cut the dough piece 15 from the dough into a predetermined shape. For example, the unit area mass N of the dough as a product or a raw material can be measured smoothly at the manufacturing site when the dough is manufactured or when a predetermined product made of the dough is manufactured.

  (2) The measuring apparatus 10 includes a storage chamber 45 and an irradiator 50 (see FIG. 1). The accommodation chamber 45 accommodates the camera 40. An infrared transmission filter 47 is provided on the bottom surface of the storage chamber 45. In a state where the camera 40 is accommodated in the accommodation chamber 45, the infrared transmission filter 47 is provided between the mounting table 20 and the camera 40. The irradiator 50 irradiates the imaging range R1 with infrared rays. The camera 40 includes an image sensor having sensitivity to infrared rays. The camera 40 images the fabric piece 15 in a state where the infrared ray is irradiated from the irradiator 50 and the infrared ray from the irradiator 50 is reflected by the fabric piece 15. In this case, the processor 71 acquires measurement imaging data including an image portion of the fabric piece 15 by infrared rays reflected by the fabric piece 15 (see S23 in FIG. 4).

  Therefore, the image portion of the fabric piece 15 can be detected stably. The accuracy of the measurement area A can be improved. Unlike the fabric piece 15 of the embodiment, it is assumed that the fabric piece is a part of the fabric having the following pattern. The aforementioned pattern is, for example, a pattern in which a plurality of figures having a predetermined shape of the same color as the placement surface 22 are arranged on the entire cloth. Examples of such a pattern include a polka dot pattern in which a plurality of polka dots having the same color as the placement surface 22 are appropriately arranged. The above-described polka dot pattern will be described as an example. When the unit area mass N is measured, when the polka dot fabric is cut out to form a fabric piece, the cutting position of the fabric may be on the polka dot. When visible light is used for imaging the fabric piece, in the visible light image corresponding to the imaging data obtained by this imaging, the background color (the color of the mounting surface 22) and the color of the cut polka dot portion at the outer edge of the fabric piece are the same. Become a color. As a result, it is conceivable that the image portion of the cloth piece cannot be detected properly, or special image analysis is required for the above-described detection. On the other hand, in the measurement imaging data using infrared rays for imaging the fabric piece, the influence of the polka dot pattern on the image portion of the fabric piece is eliminated or reduced. As a result, the boundary between the background (mounting surface 22) and the image portion of the fabric piece is stabilized, and the image portion of the fabric piece can be distinguished from the background. The operation | work which changes the mounting base 20 according to the pattern of cloth | dough becomes unnecessary. The accommodation chamber 45 has a structure in which a portion other than the infrared transmission filter 47 on the bottom is shielded from light, so that infrared rays are captured by the camera 40 without being affected by visible light or the like in the environment where the measurement apparatus 10 is installed. be able to.

  The inventor compared the image portion of the fabric piece 15 specified by the labeling process in S135 of FIG. 13 in the following first aspect and second aspect. In the first aspect, the irradiator 50 irradiates the imaging range R1 with infrared rays. The measuring device of the first aspect corresponds to the measuring device 10. The imaging data for measurement includes an image portion of the fabric piece 15 by infrared rays reflected by the fabric piece 15 (see “Before measurement area processing” shown on the left side of FIG. 15). In the second aspect, a visible light LED is employed as the irradiator, and the irradiator irradiates the imaging range R1 with visible light. In the measurement apparatus of the second aspect, the infrared transmission filter 47 is omitted. The imaging data for measurement includes an image portion of the fabric piece 15 by visible light reflected by the fabric piece 15 (see “before measurement area processing” shown on the left side of the lower part of FIG. 15). In the first embodiment and the second embodiment, the other conditions are the same.

  In the first aspect, the outer edge of the image portion of the fabric piece 15 specified by the labeling process is equivalent to the outer edge of the image portion of the fabric piece 15 included in the measurement imaging data before the measurement area processing (see FIG. 7). (See the upper part of FIG. 15). That is, in the first aspect, it is possible to detect an image portion of the fabric piece 15 that is the same as or close to the actual shape of the fabric piece 15. In the second aspect, the outer edge of the image part of the cloth piece 15 specified by the labeling process is compared with the outer edge of the image part of the cloth piece 15 included in the measurement imaging data before the measurement area process, as compared with the first aspect. They are different (see the lower part of FIG. 15). From such a result, the inventor considers that the following points should be taken into consideration in determining the specifications of the measuring apparatus. That is, the inventor preferably employs the measuring device 10 corresponding to the measuring device of the first aspect when it is necessary to measure the unit area mass N of the fabric as a product or material with high accuracy at the manufacturing site. I think. On the other hand, the inventor considers that the measurement device of the second aspect can be adopted when, for example, the measurement of the unit area mass N at the manufacturing site is simple. In FIG. 15, a rectangular frame indicated by a one-dot chain line in each of the following frames is an illustration for explanation. Each of the above-described frames is a frame including the measurement imaging data after the labeling process of the first aspect and the frame including the measurement imaging data after the labeling process of the second aspect. That is, the rectangular frame indicated by the alternate long and short dash line in the first aspect corresponds to the illustrated range of the measurement imaging data before the measurement area processing of the first aspect and includes the measurement imaging data after the labeling processing of the first aspect. And the boundary line of the mounting surface 22 included in the measurement imaging data. The rectangular frame indicated by the alternate long and short dash line in the second aspect corresponds to the illustrated range of the measurement imaging data before the measurement area processing of the second aspect, and includes the measurement imaging data after the labeling processing of the second aspect. It is a boundary line between the background and the mounting surface 22 included in the measurement imaging data.

  (3) In the measuring apparatus 10, the processor 71 executes a calibration process (see FIGS. 5 and 6). When the calibration process is executed, the reference sample 17 is placed on the mounting table 20, and the camera 40 images the reference sample 17 (see FIG. 3). In the calibration process, the processor 71 performs the first calibration imaging process and the first calibration area process, the second calibration imaging process and the second calibration area process, the third calibration imaging process and the third calibration use. An area process, a fourth calibration imaging process, a fourth calibration area process, a fifth calibration imaging process, a fifth calibration area process, and a correction coefficient process are executed (S35, S37, S41, FIG. 5). (See S43, S47, S49 and S53, S55, S59, S61, S65 in FIG. 6).

  In the first calibration imaging process, the processor 71 acquires first calibration imaging data including an image portion of the first sample as the reference sample 17 captured by the camera 40. In the first calibration area processing, the processor 71 acquires the first calibration area X1 of the region corresponding to the first sample from the image portion of the first sample included in the first calibration imaging data (S81 and FIG. 8). (See S137 in FIG. 13). In the second calibration imaging process, the processor 71 acquires second calibration imaging data including the image portion of the second sample as the reference sample 17 captured by the camera 40. In the second calibration area process, the processor 71 acquires the second calibration area X2 of the region corresponding to the second sample from the image portion of the second sample included in the second calibration imaging data (S91 and FIG. 9). (See S137 in FIG. 13). In the third calibration imaging process, the processor 71 acquires third calibration imaging data including the image portion of the third sample as the reference sample 17 captured by the camera 40. In the third calibration area process, the processor 71 acquires the third calibration area X3 of the region corresponding to the third sample from the image portion of the third sample included in the third calibration imaging data (S101 and FIG. 10). (See S137 in FIG. 13). In the fourth calibration imaging process, the processor 71 acquires fourth calibration imaging data including the image portion of the fourth sample as the reference sample 17 captured by the camera 40. In the fourth calibration area process, the processor 71 acquires the fourth calibration area X4 of the region corresponding to the fourth sample from the image portion of the fourth sample included in the fourth calibration imaging data (S111 and FIG. 11). (See S137 in FIG. 13). In the fifth calibration imaging process, the processor 71 acquires fifth calibration imaging data including the image portion of the fifth sample as the reference sample 17 captured by the camera 40. In the fifth calibration area process, the processor 71 obtains the fifth calibration area X5 of the region corresponding to the fifth sample from the image portion of the fifth sample included in the fifth calibration imaging data (S121 and FIG. 12). (See S137 in FIG. 13).

In the correction coefficient processing, the processor 71 calculates correction coefficients corresponding to the first difference value, the second difference value, the third difference value, the fourth difference value, and the fifth difference value (see S161 in FIG. 14). The first difference value is a difference between the first reference value (400 mm ² ) of the first sample and the first calibration area X1. The second difference value is a difference between the second reference value (1600 mm ² ) of the second sample and the second calibration area X2. The third difference value is a difference between the third reference value (3600 mm ² ) of the third sample and the third calibration area X3. The fourth difference value is a difference between the fourth reference value (6400 mm ² ) of the fourth sample and the fourth calibration area X4. The fifth difference value is a difference between the fifth reference value (10000 mm ² ) of the fifth sample and the fifth calibration area X5. That is, in the correction coefficient processing, the processor 71 performs the first correction value Y1 corresponding to the first difference value, the second correction value Y2 corresponding to the second difference value, and the third correction value Y3 corresponding to the third difference value. Then, a fourth correction value Y4 corresponding to the fourth difference value and a fifth correction value Y5 corresponding to the fifth difference value are acquired (see S143, S147, S151, S155, and S159 in FIG. 13). Next, the processor 71 uses the first calibration area X1, the second calibration area X2, the third calibration area X3, the fourth calibration area X4, and the fifth calibration area X5 as input values of the matrix X, and A Gaussian elimination method is executed using the first correction value Y1, the second correction value Y2, the third correction value Y3, the fourth correction value Y4, and the fifth correction value Y5 as input values of the matrix Y, and the correction coefficient is calculated. (See S161 in FIG. 14).

  Therefore, the measurement area A can be corrected by the correction coefficient. In the calculation process of the main process (see S27 in FIG. 4), the processor 71 calculates a unit area mass N obtained by dividing the mass M by the correction area B. The correction area B is an area obtained by correcting the measurement area A by the correction factor J including the correction coefficient calculated by the Gaussian elimination method. In the measuring apparatus 10, the correction factor J is a quartic polynomial approximate curve. With the measuring device 10, the measurement accuracy of the unit area mass N can be improved. The same applies to the measurement device of the second aspect described above. That is, by executing the calibration process with the measurement device of the second aspect described above, the above-described effects can be obtained even with the measurement device of the second aspect.

<Modification>
The embodiment can also be performed as follows. Some configurations of the modifications shown below can be appropriately combined and employed. Hereinafter, points different from the above will be described, and description of similar points will be omitted as appropriate.

  (1) The measuring apparatus 10 includes a storage chamber 45 (see FIG. 1). The camera 40 is accommodated in the accommodation chamber 45. An infrared transmission filter 47 is provided on the bottom surface of the storage chamber 45. In the measuring device, the storage chamber 45 may be omitted. The infrared transmission filter may be directly attached to the lens unit of the camera 40. Even with such a configuration, an infrared transmission filter can be provided between the mounting table 20 and the camera 40 in the measurement apparatus. Similar to the measurement apparatus 10 described above, infrared rays can be imaged by the camera 40 without being affected by visible light or the like in the environment where the measurement apparatus is installed.

  (2) The measuring apparatus 10 includes a camera 40 and an infrared transmission filter 47 (see FIG. 1). In the measurement apparatus, an infrared camera may be employed as the camera. The aforementioned infrared camera that can be used in the measurement apparatus is a camera that is also called a night vision camera, and does not include a camera that is called a thermography for temperature measurement. In this case, the infrared transmission filter 47 provided separately from the camera 40 in the measurement apparatus 10 may be omitted.

  (3) The measuring apparatus 10 employs a display device as the output device 60 (see FIG. 1). The output device may be a device different from the display device. For example, the output device may be a printer. In this case, in the output process executed in S29 of the main process (see FIG. 4), the unit area mass N is printed on a predetermined sheet. The output device may be a speaker. In this case, in the output process described above, the unit area mass N is output as a sound. In addition, the output device may include two or more devices of a display device, a printer, and a speaker.

  (4) As the reference sample 17, the first sample, the second sample, the third sample, the fourth sample, and the fifth sample are illustrated. In this case, the sub screen 90 includes a first sample button 92, a second sample button 93, a third sample button 94, a fourth sample button 95, and a fifth sample button 96 (see FIG. 3). The calibration process has a format corresponding to the above-described five types of reference samples 17 (see FIGS. 5 and 6). That is, the calibration processing includes S33 to S37, S39 to S43, S45 to S49, S51 to S55, and S57 to S61. The correction coefficient processing executed in S65 of FIG. 6 includes S141 and S143. , S145 and S147, S149 and S151, S153 and S155, and S157 and S159 (see FIG. 14). S33 to S37, S141, and S143 correspond to the first sample. S39 to S43, S145, and S147 correspond to the second sample. S45 to S49, S149, and S151 correspond to the third sample. S51 to S55, S153, and S155 correspond to the fourth sample. S57 to S61, S157, and S159 correspond to the fifth sample. In S161 of FIG. 14, the first calibration area X1, the second calibration area X2, the third calibration area X3, the fourth calibration area X4, and the fifth calibration area X5 are input to the matrix X, and A Gaussian elimination method is executed using the first correction value Y1, the second correction value Y2, the third correction value Y3, the fourth correction value Y4, and the fifth correction value Y5 as input values of the matrix Y.

  A sample different from the first sample, the second sample, the third sample, the fourth sample, and the fifth sample may be adopted as the reference sample 17. The sample as the reference sample 17 may be, for example, three types, four types, or six types or more. In the calibration process, a series of processes similar to S33 to S37, S39 to S43, S45 to S49, S51 to S55, and S57 to S61 are repeated by the number of reference samples 17. In the correction coefficient process, a series of processes similar to those of S141, S143, S145, S147, S149, S151, S153, S155, S157, and S159 are repeated by the number of reference samples 17. Further, in the Gaussian elimination method executed in S161, the number of calibration areas corresponding to the number of reference samples 17 is set as the input value of the matrix X, and the number of correction values corresponding to the number of reference samples 17 is set as the matrix Y. Input value.

  An example will be described in which the reference sample 17 includes three types of a first sample, a second sample, and a third sample. In the calibration process, S51 to S61 are omitted. If S45 is negative (see S45 in FIG. 5: No), the processor 71 shifts the processing to S63 in FIG. In the correction coefficient process, S153 to S159 are omitted. In S161, the processor 71 uses the first calibration area X1, the second calibration area X2, and the third calibration area X3 as input values of the matrix X, and the first correction value Y1, the second correction value Y2, and the third correction. The Gaussian elimination method is executed using the value Y3 as the input value of the matrix Y, and the correction coefficient is calculated. Even in such a case, it is possible to calculate a fourth-order correction coefficient by Gaussian elimination. However, the correction coefficient may be an order different from the fourth order. The order of the correction coefficient is appropriately determined in consideration of various conditions.

  (5) In the measurement apparatus 10, during measurement of the unit area mass N, it is assumed that a foreign object that is not a measurement target exists together with the fabric piece 15 in the imaging range R <b> 1 on the mounting table 20. In this case, the imaging data for measurement includes the image portion of the foreign matter as well as the image portion of the fabric piece 15. In the measurement area process executed in S29 of the main process (see FIG. 4), the following process may be executed. That is, in the actual measurement process (see FIG. 13) executed in S71 of FIG. 7, different labels are provided for the pixels that form the image portion of the fabric piece 15 and the pixels that form the image portion of the foreign matter by the labeling process of S135. Is attached. However, the foreign material is assumed to be smaller than the fabric piece 15. If the foreign material is larger than the fabric piece 15, it is considered that the operator notices the foreign material. Therefore, in S137, the processor 71 specifies the number of pixels (see the “first pixel” described above) labeled with a large number of pixels among the above-described pixels. Thereby, the unit area mass N of the dough piece 15 can be measured smoothly. In this case, the pixel that forms the image portion of the foreign object is the second pixel described above.

  (6) As the reference sample 17, it is possible to adopt a sample in which the material itself that reflects infrared rays has a shape whose area is a reference value (see FIG. 2). In addition, the reference sample 17 may have a form in which a figure whose area is set to the reference value is expressed as a material having an area larger than the reference value. Printing is exemplified as the above-described method of expressing the figure to be the reference sample 17. In this case, in the imaging range R1, in the region where the above-described figure serving as the reference sample 17 is expressed and in other regions, the infrared reflectance and infrared absorption are the same as in the case of the reference sample 17 and the mounting surface 22 described above. Any or all of the rate and infrared transmittance may be different. For example, the portion of the graphic that will be the reference sample 17 can be in a state of reflecting infrared rays from a region where the graphic that is to be arranged within the imaging range R1 is not represented. The area where the figure is not expressed is an area of the material where the figure is not expressed when the area of the material where the figure is expressed is larger than the imaging range R1, and the area of the material where the figure is expressed is the imaging range. In the case of being smaller than R1, it is an area including the material area where the figure is not expressed and the placement surface 22. When the reference sample 17 is configured to represent a figure in which the area is set to a reference value on a material having an area larger than the reference value, S81 in FIG. 8, S91 in FIG. 9, S101 in FIG. 10, S111 in FIG. In the actual measurement process (see FIG. 13) executed in S121 of FIG. 12, the processor 71 sets the area to the first reference value, the second reference value, the third reference value, the fourth reference value, and the fifth reference value. Further, the above-described respective graphic portions are set as objects to be detected, and the area thereof is obtained in the same manner as described above (see S137 in FIG. 13).

  (7) The measuring device 10 measures the unit area mass N. The main screen 80 includes a measurement result area 82, and the unit area mass N, the correction area B, and the mass M are output to the measurement result area 82 (see the lower part of FIG. 2). The measuring device 10 may measure the warp yarn and weft yarn crossing angle of the fabric piece 15 and output it. Further, the measuring device 10 may measure the number of wefts and the number of warps per unit length of the fabric piece 15 and output them. For the measurement of the yarn crossing angle, the number of warps, and the number of wefts, the processing algorithm disclosed in Patent Document 1 described above can be employed. Therefore, the description regarding the measurement of the yarn crossing angle, the number of warps, and the number of wefts is omitted.

DESCRIPTION OF SYMBOLS 10 Measuring apparatus, 15 Dough piece, 17 Reference sample, 20 Mounting stand 22 Mounting surface, 30 Mass meter, 40 Camera, 45 Storage chamber 47 Infrared transmission filter, 50 Irradiator, 60 Output device, 65 Operation device 70 Controller 71 processor, 72 storage, 73 memory 74 connection interface (connection I / F), 80 main screen 81 preview area, 82 measurement result area, 83 calibration button 90 sub-screen, 91 preview area, 92 first sample button 93 second Sample button, 94 Third sample button, 95 Fourth sample button, 96 Fifth sample button, 97 Correction factor button, 98 Back button, A Measurement area, B Correction area, M Mass, N Unit area mass, R1 Imaging range, R2 Illumination Range, X1 First calibration area X2 Second comparison Use area, X3 third calibration area, X4 fourth calibration area X5 fifth calibration area

Claims (5)

A mounting table on which a piece of dough is placed;
A mass meter for measuring the mass of the dough piece placed on the table,
A camera that images the dough pieces placed on the table;
An output device for outputting a unit area mass indicating a mass per unit area of the dough piece;
And a processor,
The processor is
Mass processing to obtain the mass of the dough piece measured by the mass meter,
An imaging process for measurement for acquiring imaging data for measurement including an image portion of the fabric piece imaged by the camera;
Measurement area processing for acquiring a measurement area of a region corresponding to the fabric piece from an image portion of the fabric piece included in the measurement imaging data acquired in the measurement imaging process;
A calculation process for calculating the unit area mass by the mass of the dough piece acquired by the mass process and the measurement area acquired by the area process for measurement,
And an output process for causing the output device to output the unit area mass acquired in the calculation process. An irradiator that irradiates infrared rays to the imaging range of the camera,
The camera
Including an image sensor having sensitivity to infrared rays,
Imaging in a state where infrared rays are emitted from the irradiator,
The measurement apparatus according to claim 1, wherein the measurement imaging process is a process of acquiring the measurement imaging data including an image portion of the fabric piece by infrared rays reflected by the fabric piece.   The measuring apparatus according to claim 2, further comprising an infrared transmission filter between the mounting table and the camera.   The measurement apparatus according to claim 2, wherein the camera is an infrared camera. On the mounting table, a reference sample whose area is set to the reference value is placed,
The camera images the reference sample placed on the mounting table,
The processor is
A calibration imaging process for acquiring calibration imaging data including an image portion of the reference sample imaged by the camera;
Calibration area processing for acquiring a calibration area of a region corresponding to the reference sample from an image portion of the reference sample included in the calibration imaging data acquired in the calibration imaging processing;
A correction coefficient process for calculating a correction coefficient according to a difference between the reference value and the calibration area acquired in the calibration area process;
The calculation process is a correction area obtained by correcting the mass of the dough piece acquired by the mass process by the correction coefficient calculated by the correction coefficient process by correcting the measurement area acquired by the measurement area process. The measuring apparatus according to claim 1, which is a process of calculating the divided unit area mass.