Surface inspection device and surface inspection method

Abstract

To efficiently detect distortions and sink marks on a surface of resin products, etc.SOLUTION: A surface inspection device 10 turns on a line laser light source 15 disposed in a light source device 14 to emit line laser light, and an imaging device 13 is used to capture an image of an inspection object 40b that reflects the line laser light. Then, the surface inspection device 10 calculates a regression line R for each line based on pixel values of a plurality of pixels forming the line laser light in the image, and calculates residuals between the regression line R and coordinates of the pixels forming each line. The surface inspection device 10 determines whether or not the residual of each pixel forming each line is within a predetermined threshold. The surface inspection device 10 determines the inspection object 40b to be a non-defective product if the residuals for all lines are within the predetermined threshold, and determines the inspection object 40b to be a defective product if there are pixels in each line whose residuals are not within the predetermined threshold.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a surface inspection device and a surface inspection method for efficiently detecting distortions and sink marks on the surface of a resin product or the like. [Background technology]

[0002] Conventionally, there are known techniques for inspecting defects on the surface of an object. For example, Patent Document 1 discloses a technique in which a linear laser light source emitting infrared light irradiates an object to be inspected having a non-mirror surface such as a rolled steel strip with infrared light, and an image of the reflected light is subjected to differentiation and binarization processing to inspect the quality based on whether or not a part of a line segment disappears. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2005-134362 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned Patent Document 1 has a problem that, depending on the threshold value for binarizing the differential image after differentiation, even if the surface of the object has irregularities, some of the line segments do not disappear, and it is determined that the surface of the object does not have irregularities. In particular, when the surface of the object is a mirror surface, the intensity of the reflected wave becomes strong, so that it is highly likely that some of the line segments do not disappear.

[0005] The present invention has been made to solve the problems (issues) associated with the above-mentioned conventional technology, and has an object to provide a surface inspection device and a surface inspection method that can efficiently detect distortions and sink marks on the surface of resin products, etc. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the present invention provides a surface inspection device for inspecting the surface of an inspection object, comprising a light source device that irradiates a line light toward the inspection object, an imaging unit that captures an image of the inspection object reflecting the line light irradiated from the light source device, a regression line calculation means that calculates a regression line based on pixel values ​​of a plurality of pixels that form the line light in the image, and a judgment means that judges whether the surface of the inspection object is good or bad based on the residual between the regression line calculated by the regression line calculation means and each pixel that forms the line light.

[0007] Further, in the present invention, in the above-mentioned invention, the judgment means judges that the inspection object is a pass product when the residual between the regression line calculated by the regression line calculation means and each pixel forming the line light is each below a predetermined threshold value.

[0008] Further, in the present invention, in the above-mentioned invention, the judgment means judges that the inspection object is defective when there is a pixel for which the residual between the regression line calculated by the regression line calculation means and each pixel forming the line light is greater than a predetermined threshold value.

[0009] Further, in the present invention, in the above-mentioned invention, the judgment means judges that the inspection object is defective when there are multiple consecutive pixels in which the residual between the regression line calculated by the regression line calculation means and each pixel forming the line light is greater than a predetermined threshold value.

[0010] In addition, in the above invention, the present invention further includes a filter section that transmits light of a predetermined wavelength band from the reflected light of the object to be inspected, and the imaging section captures the image formed by the light of the predetermined wavelength band that has transmitted through the filter section.

[0011] In addition, in the above invention, the light source device irradiates a plurality of lines of light toward the object to be inspected, and the imaging unit captures the image of the object to be inspected reflecting the plurality of lines of light irradiated from the light source device.

[0012] The present invention also provides a surface inspection method in a surface inspection device that inspects the surface of an object to be inspected, the method including an irradiation step in which a predetermined light source device irradiates a line light toward the object to be inspected, an imaging step in which a predetermined imaging unit captures an image of the object to be inspected that reflects the line light irradiated from the light source device, a regression line calculation step in which a regression line is calculated based on pixel values ​​of a plurality of pixels that form the line light in the image, and a judgment step in which the quality of the surface of the object to be inspected is judged based on the residual between the regression line calculated by the regression line calculation step and each pixel that forms the line light. Effect of the Invention

[0013] According to the present invention, distortions and sink marks on the surface of a resin product or the like can be efficiently detected. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is an explanatory diagram for explaining an overview of a surface inspection device according to an embodiment. [Diagram 2] FIG. 2 is a functional block diagram showing the configuration of the surface inspection apparatus shown in FIG. [Diagram 3] FIG. 3 is a diagram showing an example of an image captured by the surface inspection device. [Figure 4] FIG. 4 is an explanatory diagram for explaining calculation of a regression line by the surface inspecting device. [Diagram 5] FIG. 5 is an explanatory diagram for explaining pass / fail judgment of an object to be inspected by the surface inspection device. [Figure 6] FIG. 6 is a flowchart showing a processing procedure of the surface inspection apparatus shown in FIG. [Figure 7] FIG. 7 is a diagram showing an example of a captured image by a surface inspecting device according to a modified example. [Figure 8] FIG. 8 is an explanatory diagram for explaining pass / fail judgment of an object to be inspected by the surface inspection apparatus according to the modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment of a surface inspection device according to the present invention will be described in detail with reference to the drawings.

[0016] <Overview of Surface Inspection Device 10> An overview of the surface inspection device 10 according to this embodiment will be described. Fig. 1 is an explanatory diagram for explaining the overview of the surface inspection device 10 according to the embodiment. As shown in Fig. 1, an imaging device 13 and a light source device 14 are connected to the surface inspection device 10. Furthermore, inspection objects 40a, 40b, and 40c (hereinafter, sometimes collectively referred to as "inspection objects 40") are placed on pedestals 41a, 41b, and 41c, respectively, and are moved in the direction of the arrow by a belt conveyor 50.

[0017] The surface inspection device 10 turns on the line laser light source 15 arranged in the light source device 14 and irradiates the line laser light (S1). When the inspection object 40b reaches a predetermined position, the surface inspection device 10 uses the imaging device 13 to capture an image of the inspection object 40b reflecting the line laser light (S2). Whether the inspection object 40b has reached the predetermined position or not is determined, for example, by receiving a notification from a control device (not shown) of the belt conveyor 50 that the inspection object 40b has reached the predetermined position. Then, the surface inspection device 10 calculates a regression line R for each line based on pixel values ​​of a plurality of pixels forming the line laser light in the image (S3).

[0018] Then, the surface inspection apparatus 10 calculates the residual between the coordinates of the pixels forming each line and the regression line (S4).Then, the surface inspection apparatus 10 judges whether the residual of each line is within a predetermined threshold value or not (S5).If the residual of all lines is within the predetermined threshold value, the inspection object 40b is judged as a non-defective product, and if there is a pixel in each line whose residual is larger than the predetermined threshold value, the inspection object 40b is judged as a defective product.

[0019] <Configuration of Surface Inspection Apparatus 10> Next, the configuration of the surface inspection device 10 shown in Fig. 1 will be described. Fig. 2 is a functional block diagram showing the configuration of the surface inspection device 10 shown in Fig. 1. As shown in Fig. 2, the surface inspection device 10 has a storage unit 16 and a control unit 17, and is connected to a display unit 11, an input unit 12, an imaging device 13, and a light source device 14. The display unit 11 is a display device such as a liquid crystal display that displays various information. The input unit 12 is an input device such as a mouse or a keyboard.

[0020] The imaging device 13 has an imaging section 13a and a filter 13b. The imaging section 13a is a camera that images the inspection target 40. Here, the imaging section 13a is a camera that images only near-infrared wavelengths that are not affected by ambient light. The filter 13b is an optical filter that transmits light in a specific wavelength band and does not transmit light other than the wavelength band. Here, the filter 13b is an optical filter that transmits light in the near-infrared wavelength band and does not transmit light other than the near-infrared wavelength band.

[0021] The light source device 14 has line laser light sources 15a, 15b, 15c, 15d, and 15e (hereinafter, sometimes collectively referred to as "line laser light source 15"). The line laser light source 15 is a light source that projects laser irradiation as a line rather than a point using a laser light source and an optical lens. Here, a case where five line laser light sources 15 are used is shown, but depending on the size of the inspection target 40, for example, three line laser light sources 15 or ten line laser light sources 15 may be used. Note that the line laser light source 15 may generate a line-shaped light using an LED or a discharge lamp and an optical lens.

[0022] The storage unit 16 is a storage device such as a hard disk drive or a non-volatile memory, and stores image data 16a, regression line data 16b, and threshold data 16c. The image data 16a is data obtained by capturing an image of an inspection target 40 reflecting a line laser light by the imaging device 13. The regression line data 16b is data obtained by calculating parameters of a regression line using pixel coordinates of a plurality of pixels in the image data 16a whose line-shaped pixels have a luminance of 240 or more within a range of 0 to 255. The threshold data 16c is data representing the upper and lower limits of a predetermined residual from the regression line.

[0023] The control unit 17 is a control unit that controls the entire surface inspection device 10, and includes a light source control unit 17a, an image capture processing unit 17b, a regression line calculation unit 17c, a determination unit 17d, and a display control unit 17e. In practice, these programs are loaded into a CPU and executed, causing the light source control unit 17a, the image capture processing unit 17b, the regression line calculation unit 17c, the determination unit 17d, and the display control unit 17e to execute processes corresponding thereto.

[0024] The light source control unit 17a is a control unit that performs on / off control of the line laser light source 15 of the light source device 14 in order to inspect the surface condition of the inspection object 40. The imaging processing unit 17b is a processing unit that controls the imaging device 13 to capture an image of the inspection object 40 placed on the pedestal 41 after the line laser is irradiated onto the inspection object 40 from the light source device 14.

[0025] The regression line calculation unit 17c is a processing unit that identifies pixels whose pixel values ​​are greater than a predetermined threshold value from the image data 16a, and calculates a regression line based on the coordinates of the identified pixels. Here, the predetermined threshold value is set to 240 if the pixel values ​​are in the range of 0 to 255, for example.

[0026] The determination unit 17d is a processing unit that determines whether the surface of the inspection object 40 is a non-defective product. Specifically, if the residual between the pixel coordinates of the pixels whose pixel values ​​specified by the regression line calculation unit 17c are greater than a predetermined threshold and the coordinates calculated from the regression line is within a predetermined threshold, the inspection object 40 is determined to be a non-defective product, and if there is a pixel whose value is greater than the predetermined threshold, the inspection object 40 is determined to be a defective product.

[0027] When the inspection object 40 is judged to be a pass product by the judgment unit 17d, the display control unit 17e controls the predetermined display unit 11 to display "pass product". When the inspection object 40 is judged to be a fail product by the judgment unit 17d, the display control unit 17e controls the predetermined display unit 11 to display "fail product".

[0028] <Calculation of regression line> Next, calculation of the captured image P and regression line R by the surface inspection device 10 will be described. Fig. 3 is a diagram showing an example of the captured image P by the surface inspection device 10. As shown in Fig. 3, when the inspection object 40 reaches a predetermined position, the surface inspection device 10 captures an image of the inspection object 40 reflecting the line laser light. When three line laser lights are irradiated onto the inspection object 40, the line lights L1, L2, and L3 of the line laser are captured in the image of the inspection object 40.

[0029] Then, the surface inspection device 10 identifies a plurality of pixels that constitute the line lights L1, L2, and L3 among the pixels that form the captured image P. Specifically, the surface inspection device 10 identifies pixels whose pixel values ​​are equal to or greater than a predetermined threshold value among all pixels that form the captured image P. Then, the surface inspection device 10 recognizes a straight line by performing, for example, a Hough transform using data on the identified plurality of pixels. After that, a regression line is calculated from the coordinates of a plurality of pixels of the coordinates of the recognized straight line.

[0030] 4, for example, pixels forming a line of light L3 having pixel values ​​equal to or greater than a predetermined threshold are shown on the xy coordinate axis, and the difference between the coordinates of the pixels and the regression line R in the y-axis direction is taken as a residual E, and the parameters of the regression line R are calculated using the least squares method based on this residual E. The same process is performed on the remaining line lights L1 and L2, and the parameters of the regression lines R are calculated.

[0031] <About pass / fail judgment> Next, a description will be given of the pass / fail judgment of the inspection object 40 by the surface inspection device 10. Fig. 5 is an explanatory diagram for explaining the pass / fail judgment of the inspection object 40 by the surface inspection device 10. The surface inspection device 10 judges the pass / fail of the inspection object 40 based on the parameters of the regression line R calculated by the regression line calculation unit 17c, and a residual upper limit value Eu and a residual lower limit value El from the regression line R that are set in advance.

[0032] As shown in Figure 5(a), if the residuals of all pixels forming a specified line light L3 are smaller than the residual upper limit value Eu and larger than the residual lower limit value El, and the data of all pixels in the other line lights L1 and L2 are smaller than the residual upper limit value Eu and larger than the residual lower limit value El, the surface inspection device 10 judges the inspection object 40 to be a pass product.

[0033] 5(b), when the residuals of some pixels in the predetermined line light L3 are smaller than the residual lower limit value El, the surface inspection device 10 judges the inspection object 40 to be defective. Note that the surface inspection device 10 also judges the inspection object 40 to be defective when the data of some pixels in the predetermined line light L3 are larger than the residual upper limit value Eu. Note that the surface inspection device 10 also judges the inspection object 40 to be defective when the data of some pixels in the line light L1 or line light L2 are smaller than the residual lower limit value El or larger than the residual upper limit value Eu.

[0034] <Processing Procedure of Surface Inspection Device 10> Next, a description will be given of the processing procedure of the surface inspecting device 10. Fig. 6 is a flowchart showing the processing procedure of the surface inspecting device 10 shown in Fig. 1. As shown in Fig. 6, the surface inspecting device 10 turns on the light source device 14 to irradiate light (step S101).

[0035] When the inspection target 40 reaches a predetermined position, the surface inspection device 10 captures an image (step S102). Then, the surface inspection device 10 identifies pixels having pixel values ​​greater than a predetermined threshold value among the pixels forming the image, and detects a straight line from the identified pixels (step S103). After that, the surface inspection device 10 calculates a regression line R based on the coordinates of the pixels forming the line laser light of the image (step S104).

[0036] Then, the surface inspecting device 10 calculates the residual between the coordinates of a plurality of pixels forming the line laser light of the image and the regression line R (step S105). After that, the surface inspecting device 10 judges whether the residual is within a predetermined threshold value or not (step S106). If there is a pixel whose residual is larger or smaller than the predetermined threshold value (step S106: No), the surface inspecting device 10 controls the display of "defective product" on the predetermined display unit 11 (step S110).

[0037] On the other hand, if the residual is within the predetermined threshold value (step S106: Yes), the surface inspecting apparatus 10 judges whether the selected straight line is the last straight line (step S107). If the selected straight line is not the last straight line (step S107: No), the surface inspecting apparatus 10 selects the next straight line (step S108) and proceeds to step S104.

[0038] If the selected straight line is the last straight line (step S107: Yes), the surface inspecting apparatus 10 controls the predetermined display unit 11 to display "non-defective" (step S109).

[0039] As described above, in this embodiment, the surface inspection device 10 irradiates the inspection object 40 with a line laser light by the light source device 14, and captures an image of the inspection object 40b reflecting the line laser light by the imaging device 13. Then, the surface inspection device 10 identifies pixels having pixel values ​​greater than a predetermined threshold value among a plurality of pixels forming the image. The surface inspection device 10 calculates a regression line R based on the pixel coordinates of the identified plurality of pixels, and determines the quality of the inspection object 40 based on whether or not the residual between the pixel coordinates of the plurality of pixels and the regression line R is lower than a predetermined upper threshold value and larger than a predetermined lower threshold value. Therefore, it is possible to efficiently detect distortions and sink marks on the surface of a resin product or the like.

[0040] <Modification> In the above embodiment, the pass / fail judgment of the inspection object 40 is described based on the residual between the pixel coordinates of the image and the coordinates calculated from the regression line R. However, in the modified example, the pass / fail judgment of the inspection object 40 is described based on whether the residual exceeds a predetermined threshold value a predetermined number of times in succession.

[0041] Fig. 7 is a diagram showing an example of a captured image P of a surface inspection device according to a modified example. As shown in Fig. 7, the surface inspection device irradiates an inspection object 40 with a line laser light from a light source device 14, and captures an image of an inspection object 40b reflecting the line laser light using an imaging device 13. Here, a case is shown in which a distortion characteristic appears in the line light L3.

[0042] The surface inspection device identifies a plurality of pixels constituting the line lights L1, L2, and L3 among the pixels forming the captured image P. Specifically, the surface inspection device identifies pixels whose pixel values ​​are equal to or greater than a predetermined threshold value among all pixels forming the captured image P. Then, the surface inspection device recognizes a straight line by performing, for example, a Hough transform using data on the identified plurality of pixels. After that, a regression line R is calculated from the coordinates of a plurality of pixels of the recognized straight line.

[0043] As shown in FIG. 8, the regression line R is calculated by, for example, identifying pixels that form the line light L3 and whose pixel values ​​are equal to or greater than a predetermined threshold value, and taking the difference between the coordinates of these pixels and the regression line R in the y-axis direction as the residual E. Based on this residual E, the parameters of the regression line R are calculated using the least squares method.

[0044] Thereafter, the surface inspection device judges the quality of the inspection object 40 based on the residual threshold value for each of the line lights L1, L2, and L3. For example, the surface inspection device shows a pixel corresponding to the line light L3 on an xy coordinate system, and calculates the difference in the y-axis direction between the coordinate of this pixel and the regression line R as the residual E. Then, when this residual E exceeds the residual lower limit value El five consecutive times as shown in Fig. 8, the inspection object 40 is judged to be a defective product. Note that the number of consecutive times when the residual exceeds the residual upper limit value Eu or the residual lower limit value El is not limited to five times.

[0045] In the above embodiment, the surface inspection apparatus 10 judges the pass / fail of the inspection object 40 based on the residual between the regression line R and pixels whose pixel values ​​are equal to or greater than a predetermined threshold value. However, the present invention is not limited to this. Once the surface inspection apparatus 10 calculates the regression line R, it may calculate the error between the coordinates of pixels whose pixel values ​​are equal to or greater than a predetermined threshold value and the normal direction of the regression line R (the direction perpendicular to the regression line R), and judge pass / fail based on whether this error is within a predetermined threshold value.

[0046] In addition, in the above embodiment, the surface inspection device calculates the residual for each of the multiple pixels that make up the line lights L1, L2, and L3 among the pixels that form the image, and determines whether the object 40 is good or bad. However, the present invention is not limited to this, and the average of the residuals for consecutive pixels (for example, five consecutive pixels) among the multiple pixels that make up the line lights L1, L2, and L3 may be calculated, and the pass / fail of the object 40 to be inspected may be determined based on whether the average value is within a predetermined threshold value.

[0047] The configurations illustrated in the above embodiments are merely functional schematics, and are not necessarily physically configured as illustrated. In other words, the form of distribution and integration of each device is not limited to that illustrated, and all or part of the devices can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc. [Industrial Applicability]

[0048] The surface inspection device and the surface inspection method according to the present invention are suitable for efficiently detecting distortions and sink marks on the surface of resin products and the like. [Explanation of symbols]

[0049] 10 Surface inspection equipment 11 Display section 12 Input section 13 Imaging device 13a Imaging section 13b Filter 14 Light source device 15a, 15b, 15c, 15d, 15e Line laser light source 16 Memory section 16a Image data 16b Regression Line Data 16c Threshold Data 17 Control section 17a Light source control unit 17b Imaging processing section 17c Regression line calculation section 17d Judgment section 17e Display control section 40a, 40b, 40c Inspection object 41a, 41b, 41c Pedestal 50 Conveyor Belt E residual Eu residual upper limit El residual lower bound L1, L2, L3 line light P Captured image R regression line

Claims

1. A surface inspection device for inspecting a surface of an inspection object, comprising: a light source device that irradiates a line of light toward the inspection object; an imaging unit that captures an image of the inspection object reflecting the line light irradiated from the light source device; a regression line calculation means for calculating a regression line based on pixel values ​​of a plurality of pixels forming the line light in the image; a determining means for determining whether a surface of the inspection object is good or bad based on a residual between the regression line calculated by the regression line calculating means and each pixel forming the line light; A surface inspection device comprising:

2. The determination means is 2. A surface inspection device according to claim 1, wherein the object to be inspected is determined to be a non-defective product when residuals between the regression line calculated by the regression line calculation means and each pixel forming the line of light are each equal to or smaller than a predetermined threshold value.

3. The determination means is 2. A surface inspection device according to claim 1, wherein the object to be inspected is determined to be defective when there is a pixel in which the residual between the regression line calculated by the regression line calculation means and each pixel forming the line of light is greater than a predetermined threshold value.

4. The determination means is 2. A surface inspection device according to claim 1, wherein the object to be inspected is determined to be defective when there are a plurality of consecutive pixels in which the residual between the regression line calculated by the regression line calculation means and each pixel forming the line of light is greater than a predetermined threshold value.

5. a filter unit that transmits light of a predetermined wavelength band among the reflected light from the inspection object, The imaging unit includes:

2. The surface inspection device according to claim 1, wherein the image formed by light of the predetermined wavelength band transmitted through the filter section is captured.

6. The light source device is Irradiating a plurality of lines of light toward the inspection object; The imaging unit includes: The image of the inspection object reflecting the plurality of line lights irradiated from the light source device is captured.

6. The surface inspection device according to claim 1,

7. A surface inspection method for a surface inspection device that inspects a surface of an inspection object, comprising: an irradiation step in which a predetermined light source device irradiates a line of light toward the inspection object; an imaging step of imaging an image of the inspection object reflecting the line light irradiated from the light source device by a predetermined imaging unit; a regression line calculation step of calculating a regression line based on pixel values ​​of a plurality of pixels forming the line light in the image; a judging step of judging whether a surface of the inspection object is good or bad based on a residual between the regression line calculated in the regression line calculating step and each pixel forming the line light; A surface inspection method comprising:

Images