JP2020079775A - Image processing device of sheet material - Google Patents

Abstract

To provide an image processing device which can suppress erroneous detection of a region of a sheet material for the sheet material in a deep color.SOLUTION: An image processing device of a sheet material includes: a conveyance part which conveys the sheet material; a white inspection table; an imaging part which obtains an image by imaging the sheet material passing above the inspection table; and a sheet material image acquisition part which detects a region of the sheet material on the basis of a lightness difference between the white inspection table and the sheet material from the obtained image to obtain a sheet material image.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an image processing apparatus for a sheet material including a dark color sheet material.

  In the linen supply industry, large amounts of laundry such as towels (bath towels, face towels) and sheets are processed. This laundry is checked as a result of being used and is rejected by a person when it is contaminated or is soiled. Also, it has been attempted to automate the check of the laundry (for example, refer to Patent Document 1).

  In addition, since most of the laundry to be processed is white, a black inspection table is used for these towels, sheets, and other cloth pieces (sheet materials), and an area other than the black inspection table color is obtained from the obtained image. Is used as the cloth piece region (see, for example, Patent Document 2).

JP 2000-329701 A JP, 2014-202700, A

  However, in recent years, due to the diversification of needs in the hotel industry and the like, not only white-based but also dark-colored sheet materials such as brown, navy blue, and black are increasingly used. If you try to detect the area of the sheet material of dark color sheet material in a situation where white and dark color sheet material are mixed, there is not much difference in brightness from the black inspection table, so false detection There was a risk of

  Then, the objective of this invention is providing the image processing apparatus which can suppress the erroneous detection of the area|region of a sheet material about a dark-colored sheet material.

An image processing apparatus for a sheet material according to the present invention, a conveying unit for conveying the sheet material,
A white inspection table,
An image capturing unit that captures an image by capturing an image of the sheet material that passes over the inspection table,
A sheet material image acquisition unit that detects a region of the sheet material based on the brightness difference between the white inspection table and the sheet material from the obtained image, and obtains a sheet material image,
Equipped with.

  According to the image processing apparatus for a sheet material according to the present invention, it is possible to suppress erroneous detection of the area of the sheet material for the dark-colored sheet material. As a result, even if sheet materials having different shades of color are conveyed randomly, it is possible to accurately inspect all types of sheet materials.

FIG. 3 is a plan view showing the configuration of the image processing apparatus according to the first embodiment. FIG. 2 is a schematic diagram showing a configuration of an image pickup optical system viewed from a direction perpendicular to a vertical direction of the image processing apparatus of FIG. 1 and a sheet material conveying direction. FIG. 3 is a block diagram showing the configuration of the image processing apparatus according to the first embodiment. It is a schematic plan view which shows the case where the area|region of a dark-colored sheet material is detected using a white inspection stand. It is a schematic plan view which shows the case where the area|region of a white type|system|group sheet material and a dark color type|system|group sheet material is detected using a white inspection stand and a black inspection stand. FIG. 4B is a flowchart of a sheet material image acquisition method for detecting an area of a dark-colored sheet material using the white inspection table of FIG. 4A and acquiring a sheet material image. FIG. 4B is a flowchart of a sheet material image acquisition method that acquires a sheet material image by detecting regions of dark-colored sheet material and white sheet material using the black inspection table and the white inspection table in FIG. 4B. FIG. 9 is a schematic plan view showing holes of a dark-colored sheet material detected by the inspection method in the image processing method according to the second embodiment. FIG. 6B is an enlarged plan view of the hole of FIG. 6A. FIG. 6 is a schematic plan view showing an image obtained when the sheet material is soiled and holes are on a black inspection table. FIG. 7 is a schematic plan view showing an image obtained when the sheet material is stained and the holes are on a white inspection table. 9 is a flowchart of a method for detecting a defect of a sheet material in the image processing method according to the second embodiment.

An image processing apparatus for a sheet material according to a first aspect includes a conveyance unit that conveys a sheet material,
A white inspection table,
An image capturing unit that captures an image by capturing an image of the sheet material that passes over the inspection table,
A sheet material image acquisition unit that detects a region of the sheet material based on the brightness difference between the white inspection table and the sheet material from the obtained image, and obtains a sheet material image,
Equipped with.

  The sheet material image processing device according to a second aspect is the sheet material image processing apparatus according to the first aspect, wherein the inspection base is a black color extending in parallel with the white inspection base in a direction intersecting a conveyance direction of the sheet material. Further has an inspection table, the sheet material image acquisition unit, from the obtained image based on the brightness difference between the white inspection table or the black inspection table and the sheet material, the area of the sheet material. The sheet material image may be obtained by detection.

  The image processing apparatus for a sheet material according to a third aspect may further include an inspection unit for detecting a defect in the sheet material based on the sheet material image in the first or second aspect.

  Hereinafter, a sheet material image processing apparatus and a sheet material image processing method according to embodiments will be described with reference to the accompanying drawings. In the drawings, substantially the same members are designated by the same reference numerals.

(Embodiment 1)
<Image processing device for sheet materials>
FIG. 1 is a plan view showing the configuration of the image processing device 10 according to the first embodiment. FIG. 2 is a schematic diagram showing the configuration of the image pickup optical system viewed from a direction perpendicular to the vertical direction of the image processing apparatus of FIG. 1 and the sheet material conveyance direction. FIG. 3 is a block diagram showing the configuration of the image processing apparatus 10 according to the first embodiment. In the figure, for convenience, the sheet material 1 is indicated as the X direction, the width direction perpendicular to the sheet material conveyance direction is the Y direction, and the vertically upward direction is the Z direction.

The sheet material image processing apparatus 10 according to the first embodiment includes a conveying unit 11 that conveys the sheet material 1, a white inspection table 12 on which the sheet material passes, and the sheet that passes on the inspection table. An image capturing unit 14 that captures an image of a material to obtain an image, and a sheet material image acquisition unit 35a that obtains a sheet material image are provided. The sheet material image acquisition unit 35a detects the area of the sheet material from the obtained image based on the difference in brightness between the white inspection table 12 and the sheet material 1 to obtain the sheet material image.
As a result, even a dark-colored sheet material has a large difference in brightness from the white inspection table, so that erroneous detection of the area of the sheet material can be suppressed.

  The constituent members that make up the image processing apparatus 10 will be described below.

<Conveyor>
The sheet material 1 is transported to the inspection table 12 by the transport unit 11. In the figure, for convenience, the carrying direction is the X direction. The conveyor 11 can use, for example, a belt conveyor.

<Inspection table>
As the inspection table 12, a white inspection table can be used as shown in FIG. 4A. Further, as shown in FIG. 4B, the inspection table 12 extends in parallel with each other in a direction (Y direction) intersecting the transport direction (X direction). An inspection table having a black inspection table 12a and a white inspection table 12b can be used.

<Light source part>
For the light source unit 13, any ordinary light source such as a lamp or an LED can be used. Diffuse illumination for radiating diffused light is preferable.

<Imaging unit>
As shown in FIG. 2, the image pickup section 14 is arranged above the light source sections 13a and 13b. Further, the imaging unit 14 is not at the regular reflection position with respect to the light source units 13a and 13b, and can obtain an image by diffuse reflection light. The image of the sheet material 1 can be obtained by the imaging unit 14.
The imaging unit 14 can use a line camera or an area camera. The image capturing section 14 may include, for example, an image sensor such as a CCD or a CMOS, and an image capturing control unit that controls the image sensor.

<Control unit (computer device)>
The control unit 30 is, for example, a computer device. A general-purpose computer device can be used as the computer device, and includes, for example, a processing unit 31, a storage unit 32, and a display unit 33, as shown in FIG. Further, an input device, a storage device, an interface, etc. may be further included.
The control unit 30 controls the transport unit 11, the light source unit 13, and the imaging unit 14.

<Processing unit>
The processing unit 31 may be, for example, a central processing operator (CPU), a microcomputer, or a processing device capable of executing computer-executable instructions.

<Memory>
The storage unit 32 may be, for example, at least one of ROM, EEPROM, RAM, flash SSD, hard disk, USB memory, magnetic disk, optical disk, magneto-optical disk, and the like.
The storage unit 32 includes a program 35. When the control unit 30 is connected to the network, the program 35 may be downloaded from the network as needed.

<Program>
The program 35 may include the sheet material image acquisition unit 35a. The sheet material image acquisition unit 35a is read from the storage unit 32 and executed by the processing unit 31 at the time of execution. The sheet material image acquisition unit 35a can detect the area of the sheet material from the obtained image based on the difference in brightness between the white inspection table 12 and the sheet material 1 to obtain the sheet material image.

<Sheet material image acquisition unit>
FIG. 4A is a schematic plan view showing a case where the region of the dark-colored sheet material 1 is detected using the white inspection table 12. FIG. 4B is a schematic plan view showing a case where the areas of the dark color type sheet material 1a and the white type sheet material 1b are detected by using the black inspection table 12a and the white inspection table 12b. FIG. 5A is a flowchart of a sheet material image acquisition method for detecting a region of the dark-colored sheet material 1 using the white inspection table 12 of FIG. 4A and acquiring a sheet material image. FIG. 5B shows a sheet material image acquisition method for acquiring a sheet material image by detecting areas of the dark-colored sheet material 1a and the white sheet material 1b using the black inspection table 12a and the white inspection table 12b. It is a flowchart.

First, a method of detecting the region of the dark-colored sheet material 1 using only the white inspection table 12 of FIG. 4A and acquiring the sheet material image will be described.
(1) With respect to the image obtained for the sheet material on the white inspection table, the change in brightness is obtained in the direction intersecting the conveyance direction (S01).
(2) Next, in the obtained image, a region in which the brightness sharply decreases from a value corresponding to white (for example, around 250 when the image is 8 bits) and a change in the opposite direction in the direction intersecting the conveyance direction. Both the area having (abrupt change from dark color to white) is determined as the boundary between the white inspection table 12 and the sheet material 1a, and the area between the both boundaries is detected as the area of the sheet material. Here, for example, the brightness of black is 10, and the brightness of white is 250. That is, the lightness of the white inspection table 12 is about 250, and it is considered that the lightness of the region of the dark-colored sheet material 1a is closer to 10 rather than 250.
By the above, a sheet material image can be obtained. In this case, since the white inspection table 12 is used, erroneous detection can be suppressed even with a dark-colored sheet material.

Next, using the white inspection table 12b and the black inspection table 12a in FIG. 4B, a method of detecting the regions of the dark-colored sheet material 1a and the white-based sheet material 1b and acquiring the sheet material image explain.
(1) In the image obtained for the sheet material on the black inspection table, the change in brightness is obtained in the direction intersecting the transport direction (S11).
(2) Next, in the obtained image, in the direction intersecting the conveyance direction, both the region where the lightness sharply increases from around 10 corresponding to black and the region having the opposite change are inspected for black. The boundary between the table 12a and the sheet materials 1a and 1b is determined, and the area between the boundaries is detected as the sheet material area (S12). In the case of the white sheet material 1b, the difference in brightness from the black inspection table 12a becomes large, so that the area of the sheet material can be easily detected. On the other hand, in the case of the dark-colored sheet material 1a, the difference in brightness from the black inspection table 12a is small, and it may be difficult to detect the area of the sheet material.
(3) Next, with respect to the image obtained for the sheet material on the white inspection table, the change in the lightness is obtained in the direction intersecting the transport direction (S13).
(4) Next, in the obtained image, both the region where the brightness sharply increases from around 250 corresponding to white and the region having the opposite change in the direction intersecting the transport direction are inspected for white. The boundary between the table 12b and the sheet materials 1a and 1b is determined, and the area between the boundaries is detected as the area of the sheet materials 1a and 1b (S14). In this case, in the case of the dark-colored sheet material 1a, the difference in lightness from the white inspection table 12b becomes large, so that the area of the sheet material can be easily detected. On the other hand, in the case of the white sheet material 1b, the difference in brightness from the white inspection table 12b is small, and it may be difficult to detect the area of the sheet material.
As described above, even when sheet materials having different shades of color are mixed, the area of the sheet material is detected and the sheet material image is acquired for both the dark sheet material 1a and the white sheet material 1b. be able to.

  The inspection unit 35b may be included if necessary. The inspection unit 35b inspects the sheet material for defects, for example, based on the sheet material image obtained by the sheet material image acquisition unit. The defects of the sheet material include, for example, holes and stains. At the time of execution, the inspection unit 35b is also read from the storage unit 32 and executed by the processing unit 31.

<Display>
The display unit 33 may display the image obtained by the sheet material image acquisition unit 35a, for example.

(Embodiment 2)
6A and 6B are schematic plan views showing the holes 3 of the dark-colored sheet material 1 detected by the inspection method in the image processing method according to the second embodiment. FIG. 6B is an enlarged plan view of FIG. 6A. FIG. 7A is a schematic plan view showing an image obtained when the stains 2, 4 and the hole 3 of the sheet material 1 are on the black inspection table 12a. FIG. 7B is a schematic plan view showing an image obtained when the stains 2, 4 and the hole 3 of the sheet material 1 are on the white inspection table 12b.

  Examples of defects in the sheet material 1 include dirt and holes (breakage). The stains include white stains 2 and black stains 4 as shown in FIGS. 7A and 7B. In the case of the conventional single-color inspection table, only one image can be obtained, and there is a problem that it is difficult to distinguish stains from holes.

  In the image processing method according to the second embodiment, an image obtained for the sheet materials 1a and 1b on the black inspection table 12a and an image obtained for the sheet materials 1a and 1b on the white inspection table 12b are used. By comparing the above, it is determined whether the defect of the sheet material is the stains 2 and 4 or the hole (breakage) 3, and whether the stain is the white stain 2 or the black stain 4. Can be determined.

FIG. 8 is a flowchart of a method of detecting a defect of a sheet material in the image processing method according to the second embodiment.
(1) In the sheet material image, that is, inside the boundary with the inspection table, areas 2, 3, and 4 different from the average brightness of the sheet materials 1a and 1b are detected as defects (S21).
(2) The sheet material images obtained for the sheet materials 1a and 1b on the black inspection table 12a are compared with the sheet material images obtained for the sheet materials 1a and 1b on the white inspection table 12b. (S22).
(3) Of the above defects 2, 3, and 4, a defect in which the brightness is greatly changed between the sheet material image obtained on the black inspection table 12a and the sheet material image obtained on the white inspection table 12b, It is detected as a hole (break) 3 (S23). This is because in the case of holes, the colors of the inspection tables 12a and 12b are reflected as they are. That is, the other defects 2 and 4 do not change in brightness due to the inspection tables 12a and 12b, and are considered to be stains instead of holes.
(4) With respect to the defects 2 and 4 which are determined to be stains, the defect having high lightness is detected as the white stain 2 and the defect having low lightness is detected as the black stain 4 based on the lightness (S24).
As described above, by using the black inspection table 12a and the white inspection table 12b together, it is determined whether the defects 2, 3 and 4 are the stains 2 and 4 or the holes (breaks) 3, and As for the stain, it can be determined whether the stain is the white stain 2 or the black stain 4.

  It should be noted that the present disclosure includes appropriate combination of any of the various embodiments and/or examples described above, and each of the embodiments and/or The effects of the embodiment can be achieved.

  According to the image processing apparatus for a sheet material according to the present invention, it is possible to suppress erroneous detection of the area of the sheet material for the dark-colored sheet material.

1, 1a, 1b Sheet material 2 White stains 3 Holes (tear)
4 Black-based dirt 10 Image processing device 11 Conveying unit 12, 12a, 12b Inspection table 13, 13a, 13b Light source unit 14, 14a, 14b, 14c Imaging unit 30 Control unit (computer device)
31 processing unit 32 storage unit 33 display unit 35 program 35a sheet material image acquisition unit 35b inspection unit

Claims (3)

A transport unit for transporting the sheet material,
A white inspection table,
An image capturing unit that captures an image by capturing an image of the sheet material passing over the inspection table,
A sheet material image acquisition unit that detects a region of the sheet material based on the brightness difference between the white inspection table and the sheet material from the obtained image, and obtains a sheet material image,
An image processing apparatus for a sheet material, comprising:   The inspection table further has a black inspection table extending in parallel with the white inspection table in a direction intersecting the sheet material conveyance direction, the sheet material image acquisition unit, the image obtained The image processing apparatus according to claim 1, wherein an area of the sheet material is detected based on a difference in brightness between the white inspection table or the black inspection table and the sheet material to obtain a sheet material image.   The image processing apparatus according to claim 1, further comprising an inspection unit that detects a defect in the sheet material based on the sheet material image.

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