JP6683088B2 - Surface texture inspection device, surface texture inspection method and program - Google Patents

Description

  The present invention relates to a surface texture inspection device, a surface texture inspection method, and a program.

  Is the machined steel product manufactured by performing various types of machining after hot forming etc. on an intermediate material typified by slabs and billets, etc., has an appropriate surface texture at the time of shipment? Whether or not (surface inspection) is performed. The surface inspection of such machined steel material is often performed as an inspection by tapping sound or an inspection by visual inspection, but in the case of these inspection methods, the skill of the inspector is largely responsible. In particular, visual inspection has a plurality of inspection items such as magnetic particle flaw detection and visual inspection, which complicates the work. In such machined steel material, minute scratches due to machining are generated on the surface, or the surface of the material after hot forming the billet etc. which is an intermediate material of the base material remains on the surface of the machined steel material. Various surface property changes, such as turning on, may occur. Inspection of the surface properties so that the machined steel material that has such microscopic scratches on the surface and residual surface (background) of the material after hot forming the billet, which is an intermediate material, does not flow out as a shameful flaw. Is required to be accurate.

  An example of the machined steel material as described above is, for example, a disk-shaped processed product or an intermediate material manufactured by adjusting the shape of the material after hot forming a billet or the like which is an intermediate material by mechanical cutting. Examples thereof include a cylindrical processed product produced by adjusting the outer diameter of the material after hot forming a billet or the like by mechanical cutting or the like. As an inspection method for these machined steel materials, in Patent Document 1 below, for example, an inspection device by a so-called optical cutting method, which irradiates a surface of the machined steel material with a line laser, and images the entire surface, and a machine Optical inspection and the like have been proposed in which the surface condition is monitored by the change in the received light intensity of the light projected on the surface of the processed steel material.

  However, the remaining surface of the material after the hot forming of the billet, which is an intermediate material, that may exist on the surface of the machined steel material, and the harmful scratches such as rust, are extremely uneven with a roughness of 100 μm or less. Since it is small, it cannot be detected by the optical cutting method as proposed in Patent Document 1 below.

  Therefore, as a method of detecting minute unevenness, in Patent Document 2 below, slit laser light (linear light) is irradiated onto the surface of a machined product to focus the irradiation light on the concave portion and the irradiation light on the convex portion. A technique has been proposed that focuses on a change in the width of irradiation light caused by scattering of light. This technique utilizes the characteristics that the width of the irradiation light is small if the surface of the machined product is smooth and the width of the irradiation light is large if there are recesses.

JP, 2003-240521, A JP 2002-346925A

  However, the inspection technique proposed in Patent Document 2 is a technique for inspecting only a specific portion of the surface of a machined product, and additionally uses a change in the line width of irradiation light in a part of the machined product. However, there is a problem in that the visibility of the position of the defective portion is poor due to this technology. Further, in the technique proposed in Patent Document 2 above, since a two-dimensional imaging of a portion having a large surface roughness (unevenness) is not performed, a portion having a large surface roughness is processed by using various image processing. Cannot be extracted or the size of a portion having a high surface roughness cannot be specified. Furthermore, since the change in the line width of the linear laser beam is slight, there is a problem that the visibility is low only with the projected image of the irradiation light.

  As described above, when inspecting the surface texture of a machined product, the billet or the like, which is an intermediate material, is hot formed regardless of whether the unevenness information by the light cutting method or the brightness change information of the illumination reflected light is used. Under the present circumstances, it is impossible to clearly reveal the part where the background of the material is left behind and rust etc. Although it is possible to image the surface of the machined product based on the brightness information of the reflected light from the illumination, it is affected by noise components in the surroundings (for example, machined skin and dust), and the defective part is affected. It is extremely difficult to separate the normal part from the normal part.

  Therefore, the present invention has been made in view of the above problems, and an object of the present invention is to provide a machined product obtained by machining an intermediate material, to leave a background residual portion and rust of the intermediate material. It is an object of the present invention to provide a surface texture inspection device, a surface texture inspection method, and a program capable of inspecting the surface shape of a machined product while becoming apparent.

  In order to solve the above problems, according to one aspect of the present invention, there is provided a surface texture inspection device that uses a machined product made of an intermediate material as an inspection object, and a line is formed on a surface of the moving inspection object. A linear laser beam, and by imaging the surface irradiated with the linear laser beam, a light-section image that is a captured image of the linear laser beam on the surface is moved to the inspected object. A plurality of inspected image pickup devices that are generated along the direction, and an arithmetic process that performs image processing on the light-section image generated by the inspected image pickup device to determine the surface texture of the surface of the inspected object. And a lighting device for irradiating the surface of the object to be inspected with the linear laser light, and an image of the surface irradiated with the linear laser light. And an imaging device for A plurality of light-section images, based on a striped image frame in which light-section lines, which are line segments corresponding to the linear laser light irradiation portion, are sequentially arranged along the moving direction, the object to be inspected. Depth image showing the concavo-convex state of the surface, a luminance image showing the luminance distribution of the linear laser light on the surface of the inspection object, and the movement of the linear laser light on the surface of the inspection object An image calculation unit that calculates a line width image in which the distribution of the line width in the direction is associated with a luminance value, and the depth image, the luminance image, and the line width image that have been calculated, based on the inspected object. A detection processing unit for detecting the surface texture of the, and the detection processing unit, based on the line width image, the residual surface portion or rust of the intermediate material as a material, on the surface of the inspection object. Surface texture inspection to detect the presence or absence Location is provided.

  It is preferable that the detection processing unit detects the background residual portion and the rust based on whether or not the luminance value of the line width image is equal to or more than a first threshold value for detecting the background residual portion and rust. .

  The image calculation unit calculates, for each light cutting line in the striped image frame, a difference between the line width and a predetermined threshold line width at each position in the extending direction of the light cutting line, and is calculated. It is preferable to calculate the line width image by assigning a brightness value according to the magnitude of the difference.

  The image calculation unit calculates the barycentric position in the line width direction of the light cutting line along the moving direction of the inspection object, and a reference position that is a position in the moving direction designated in advance with respect to the light cutting image. It is preferable to calculate the depth image based on the amount of displacement from the position of the center of gravity.

  The detection processing unit, the brightness value of the depth image and the brightness image, to identify the defect site based on whether the second threshold for defect site identification or more, about the identified defect site It is preferable to extract feature amount information regarding the form and brightness value of the defective portion, and to determine a defect existing on the surface of the inspection subject based on the extracted feature amount information.

  The detection processing unit may detect the defective portion in the depth image and the luminance image other than the portion where the background remaining portion or the rust is detected based on the line width image.

  The imaging device for an object to be inspected may include at least two imaging devices for imaging the surface irradiated with the linear laser light from an upstream side in the moving direction and a downstream side in the moving direction, respectively. preferable.

  Further, in order to solve the above problems, according to another aspect of the present invention, there is provided a surface texture inspection method using a machined product made of an intermediate material as an inspected object, wherein the moving inspected object is Light that is an imaged image of the linear laser light on the surface by irradiating the surface with linear laser light from an illuminating device and capturing the surface irradiated with the linear laser light with an imaging device. An optical cutting image generating step of generating a plurality of cutting images along the moving direction of the object to be inspected, and a line segment corresponding to the irradiation portion of the linear laser light in each of the plurality of optical cutting images by the arithmetic processing device. On the basis of a striped image frame in which the optical cutting lines are arranged in order along the moving direction, a depth image showing the concavo-convex state of the surface of the inspection object, and the linear shape on the surface of the inspection object. Luminance of laser light An image calculation step of calculating a luminance image representing the line width image in which the distribution of the line width in the moving direction of the linear laser light on the surface of the object to be inspected is associated with a luminance value; A detection processing step of detecting a surface texture of the inspection object based on the depth image, the brightness image, and the line width image calculated by the device, wherein the detection processing step includes the line width image. Based on the above, there is provided a surface texture inspection method for detecting whether or not a background residual portion or rust made of the intermediate material is present on the surface of the inspection object.

  Further, in order to solve the above-mentioned problems, according to still another aspect of the present invention, a machined product made of an intermediate material is used as an inspection object, and a linear laser beam is applied to the surface of the moving inspection object. By irradiating, and by imaging the surface irradiated with the linear laser light, a light-section image that is a captured image of the linear laser light on the surface along the moving direction of the inspected object. In a computer capable of mutually communicating with a plurality of inspected image pickup devices to be generated, a light cutting line which is a line segment corresponding to the irradiation portion of the linear laser light in each of the plurality of generated light cutting images is described above. Based on the striped image frames arranged in order along the moving direction, a depth image showing the concavo-convex state of the surface of the inspection object, and the brightness distribution of the linear laser light on the surface of the inspection object. Luminance image and the inspection object A line width image in which the distribution of the line width in the moving direction of the linear laser light on the surface is associated with a luminance value, an image calculation function, the calculated depth image, the luminance image and the A detection processing function for detecting the surface texture of the inspected object based on a line width image, and the detection processing function is based on the line width image, and a background residual portion made of the intermediate material as a material or A program is provided for detecting whether or not rust is present on the surface of the inspection object.

  As described above, according to the present invention, for a machined product obtained by machining a material after hot forming a billet or the like as an intermediate material, after hot forming the billet or the like as an intermediate material It becomes possible to inspect the surface shape of the machined product while demonstrating the remaining surface of the material and the rust remaining on the surface of the material.

It is a block diagram showing typically composition of a surface texture inspection device concerning an embodiment of the present invention. It is explanatory drawing which showed typically an example of a structure of the to-be-inspected object imaging device which concerns on the same embodiment. It is explanatory drawing which showed typically an example of a structure of the to-be-inspected object imaging device which concerns on the same embodiment. It is explanatory drawing for demonstrating the mode of reflection in the normal to-be-tested object surface. It is explanatory drawing for demonstrating the mode of reflection in the rough surface part of a to-be-inspected object. It is explanatory drawing which showed typically the light-section image at the time of imaging the normal to-be-tested object surface. It is explanatory drawing which showed typically the light-section image at the time of imaging the to-be-inspected object surface containing a recessed part. It is explanatory drawing which showed typically the light section image at the time of imaging the to-be-inspected object surface containing a rough surface part. FIG. 3 is a block diagram showing an example of a configuration of an image processing unit included in the arithmetic processing device according to the same embodiment. It is an explanatory view showing an example of a striped image frame concerning the embodiment. It is an explanatory view for explaining the optical cutting process concerning the embodiment. It is an explanatory view for explaining the optical cutting process concerning the embodiment. It is explanatory drawing which showed the two-dimensional array of the light-section line displacement which concerns on the same embodiment. It is explanatory drawing which showed the two-dimensional array of the total of the brightness | luminance which concerns on the same embodiment. It is explanatory drawing which showed the two-dimensional array of the pixel number of the bright line which concerns on the same embodiment. It is explanatory drawing which showed the relationship between the displacement of a light-section line and the height of a defect. It is an explanatory view for explaining approximate correction processing of a light section line concerning the embodiment. It is explanatory drawing for demonstrating the line width of the light-section line in a normal part and a rough surface part. It is explanatory drawing for demonstrating the line width of the optical cutting line in a normal part. It is explanatory drawing for demonstrating the line width of the optical cutting line in a rough surface part. It is an explanatory view for explaining a line width image concerning the embodiment. It is explanatory drawing which showed typically an example of the logic table used by the surface texture detection process which concerns on the same embodiment. It is a flow chart showing an example of a flow of a surface texture inspection method concerning the embodiment. It is a block diagram showing an example of hardware constitutions of an arithmetic processing unit concerning the embodiment. It is explanatory drawing for demonstrating an Example. It is explanatory drawing for demonstrating an Example.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the present specification and the drawings, constituent elements having substantially the same functional configuration are designated by the same reference numerals, and duplicate description will be omitted.

(Embodiment)
<Overall structure of surface texture inspection device>
First, the overall configuration of the surface texture inspection apparatus 10 according to the embodiment of the present invention will be described with reference to FIG. FIG. 1 is an explanatory diagram showing an example of the configuration of the surface texture inspection device 10 according to the present embodiment.

  The surface texture inspection device 10 according to the present embodiment is a machined product obtained by machining a material after hot forming a billet or the like which is an intermediate material (hereinafter, simply referred to as a “machined product using an intermediate material”). Is referred to as the inspection object 1 and is an apparatus for inspecting the surface texture of the inspection object 1 moving in a predetermined direction.

  Here, the intermediate material is, for example, a material such as a slab or a billet before it becomes a final product. After hot forming of such an intermediate material, mechanical processing such as polishing and cutting is performed to manufacture a machined product of interest in the present embodiment. As such a machined product, for example, a disk-shaped product produced by hot-forming a billet or the like, which is a kind of intermediate material containing iron (Fe) as a main component, and then shaping the material by mechanical cutting. Examples include a processed product and a cylindrical processed product produced by adjusting the outer diameter of the material after hot forming a billet or the like by mechanical cutting or the like. Further, the intermediate material is not limited to one containing iron as a main component, and may be one containing a non-ferrous metal as a main component.

  As shown in FIG. 1, the surface texture inspection apparatus 10 according to the present embodiment images an object to be inspected, which images the surface of the object to be inspected 1 (in particular, the machined surface of a machined product that is the object to be inspected 1). The apparatus 100 is mainly provided with an arithmetic processing unit 200 that performs image processing on an image obtained as a result of imaging.

  The inspected object imaging device 100 is installed above the moving inspected object 1 as described in detail below. The inspected object imaging apparatus 100 is an apparatus that sequentially images the surface of the inspected object 1 moving in a predetermined direction, and outputs a captured image obtained as a result of the imaging to the arithmetic processing apparatus 200. The imaging processing by the device under test imaging apparatus 100 is controlled by the arithmetic processing apparatus 200. In general, for example, a PLG (Pulse Logic Generator) or the like is provided in a transport line for transporting a machined product that is the inspection object 1 in order to detect the moving speed of the inspection object 1. There is. Therefore, the arithmetic processing device 200 periodically transmits a control signal to the inspected object imaging device 100 based on the 1-pulse PLG signal input from the PLG, and the inspected object imaging device 100 is controlled based on the control signal. Can be operated. Thereby, the inspected object imaging apparatus 100 can image the surface of the inspected object 1 every time the inspected object 1 moves for a predetermined distance or for a predetermined time.

  As described above, the arithmetic processing device 200 controls the overall imaging process of the surface of the inspection object 1 in the inspection object imaging device 100. Further, the arithmetic processing device 200 generates a striped image frame using the captured image generated by the inspection target imaging device 100, and performs image processing on the striped image frame, so that the inspection target 1 Various defects that may be present on the surface (for example, scratches accompanied by changes in unevenness, pattern-based scratches, the surface residual portion of the surface of the material after hot forming the intermediate material (below, It is simply referred to as a "remaining background portion made of an intermediate material") and rust).

  Below, these inspected object imaging device 100 and arithmetic processing device 200 will be described in detail.

<About the device under test imaging device 100>
Subsequently, an example of the configuration of the inspected object imaging apparatus 100 according to the present embodiment will be described in detail with reference to FIGS. 2A to 4C.
FIG. 2A and FIG. 2B are explanatory diagrams schematically showing an example of the configuration of the inspected object imaging apparatus according to the present embodiment. FIG. 3A is an explanatory diagram for explaining a state of reflection on a normal surface of the inspection object, and FIG. 3B is an explanatory diagram for explaining a state of reflection on a rough surface portion of the inspection object. FIG. 4A is an explanatory diagram schematically showing a light section image when a normal surface of an object to be inspected is imaged. FIG. 4B is an explanatory diagram schematically showing a light section image when an image of the surface of the inspection object including the concave portion is picked up. FIG. 4C is an explanatory diagram schematically showing a light section image when an image of the surface of the inspection object including the rough surface portion is captured.

  2A is a schematic diagram of the inspected object imaging apparatus 100 when viewed from above the inspected object 1, and the lower diagram in FIG. 2A is the inspected object imaging apparatus 100. FIG. 3 is a schematic view of the case when viewed from the side of the inspection object 1. Similarly, the diagram shown in the upper stage of FIG. 2B is a schematic diagram of the inspected device imaging apparatus 100 viewed from above the inspected device 1, and the diagram shown in the lower stage of FIG. 2B is the inspected device. 3 is a schematic diagram of the imaging device 100 when viewed from the side of the device under test 1. FIG.

  Further, in the following description, for convenience, the moving direction of the machined product as the inspection object 1 is defined as the y-axis positive direction, and the direction orthogonal to the moving direction is defined as the x-axis positive direction. The positive direction is the z-axis positive direction.

  As schematically shown in FIG. 2A, the inspected device imaging device 100 according to the present embodiment includes an illumination device 101 and an area camera 103 which is an example of the imaging device. The illumination device 101 and the area camera 103 are fixed by a known means (not shown) so that their installation positions do not change.

  The illuminating device 101 is a device that illuminates the surface of the inspection object 1 by irradiating the surface of the machined product that is the inspection object 1 with predetermined light. The illuminating device 101 has at least a laser light source that irradiates the surface of the inspection object 1 with a linear laser beam L.

  The illumination device 101 includes, for example, a light source unit that emits a laser beam having a predetermined wavelength such as a visible light band, and a laser beam emitted from the light source unit that is condensed in the line width direction while expanding in the x-axis direction. And a lens (for example, a cylindrical lens, a rod lens, a Powell lens, etc.) for making linear light. By changing the focus of the lens in the line width direction, the thickness of the linear laser light L at the laser irradiation position along the y-axis direction (that is, the line width of the linear laser light L) is adjusted. It becomes possible. The line width of the linear laser beam L immediately before reaching the surface of the inspection object 1 can be set to, for example, about several hundreds μm (for example, about 200 μm).

  A linear bright portion is formed along the x-axis direction in a portion of the surface of the DUT 1 irradiated with the linear laser light L. The line segment corresponding to this linear bright portion is called a light cutting line.

  The area camera 103, which is an example of an imaging device, is a device that captures an image of the entire surface of the DUT 1 irradiated with the linear laser light L. The area camera 103 includes a lens having a predetermined open aperture value and a focal length, and various sensors such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor) that function as an image sensor. The area camera 103 may be a monochrome camera or a color camera.

  The focal length and angle of view of the lens mounted on the area camera 103, and the distance between the illuminating device 101 and the image sensor of the area camera 103 are not particularly specified, but x of the surface of the inspection object 1 is not specified. The selection is preferably such that the entire direction fits within the field of view VF. Further, the size and pixel size of the image pickup device mounted on the area camera 103 are not particularly specified, but it is preferable to use a larger image pickup device in consideration of the image quality and the image resolution of the generated image. From the viewpoint of image processing described below, it is preferable that the line width of the linear laser beam L is adjusted to be about 2 to 4 pixels on the image sensor.

  The area camera 103 images the linear laser light L radiated on the surface of the object 1 to be inspected, so that a light cutting line which is a line segment corresponding to the irradiation portion of the linear laser light L is imaged. Also, a so-called light section image is generated. When the area camera 103 generates such a light section image, it outputs the generated light section image to the arithmetic processing device 200.

  Here, the optical positional relationship between the illuminating device 101 and the area camera 103 can be set as appropriate. For example, as shown in FIG. 2A, the illuminating device 101 is arranged in the vertical direction of the DUT 1. The linear laser light L is provided above and irradiates the inspected object 1 with a linear laser beam L perpendicularly, and the area camera 103 linearly emits the linear laser beam from a direction of an angle φ with respect to the vertical direction (z-axis direction). It can be arranged to image the reflected light of L.

  It is preferable that the angle φ shown in FIG. 2A be as large as possible within a range where there are no restrictions on the installation of the area camera 103. This allows the area camera 103 to capture the irregular reflection of the light section line. The size of φ shown in FIG. 2A is preferably about 30 to 60 degrees, for example.

  2A illustrates a case where only one area camera, which is an example of an image pickup apparatus, is provided in the image pickup apparatus 100 for inspecting an object to be inspected, as illustrated in FIG. The apparatus 100 includes at least two area cameras 103 and 105 so that the surface of the DUT 1 irradiated with the linear laser beam L can be imaged from the upstream side in the moving direction and the downstream side in the moving direction. You may have. At this time, as shown in FIG. 2B, it is preferable that the area camera 103 and the area camera 105 are evenly arranged at an angle φ on the upstream side and the downstream side in the moving direction of the DUT 1.

  As will be described below with reference to specific examples, there may be a case where the surface residual portion, the uneven scratches, and the like have a directional property in the inclination of the surface along the moving direction. As shown in FIG. 2B, by providing area cameras on the upstream side and the downstream side in the moving direction and using the light section images output from the respective area cameras, regardless of the directionality of the tilt, It is possible to more accurately inspect the surface texture of the device under test 1.

  The specific configurations, set values, and the like of each device included in the device-to-be-inspected imaging device 100 according to the present embodiment will be listed below. Such a configuration, set values, and the like are merely examples, and the device under test imaging apparatus 100 according to the present invention is not limited to the following specific examples.

○ Inspection object (machined product)
Width (length in the x-axis direction): about 600 mm to 1750 mm ○ Lighting device 101
Irradiate red laser light from a laser light source with an output of 100 mW. The line width of the linear laser beam L with which the surface of the DUT 1 is irradiated is 0.25 mm (250 μm). However, the line width in this case is defined as 13.5% from the peak intensity value.
Area camera A CCD of 2048 pixels × 2048 pixels (pixel size: 5.5 μm × 5.5 μm) is mounted as an image sensor, and the frame rate is 200 fps. The focal length of the lens is 24 mm and the angle of view is 26 °. The pixel size of the imaged image is 0.25 mm × 0.25 mm, and the line width of the linear laser light L is captured with the width of the bright line of 2 to 4 pixels on the imaged image. When the width of the object to be inspected is large, it is possible to arrange a plurality of area cameras in the width direction, if necessary, for reasons such as ensuring pixel resolution.
Image acquisition method Images are continuously acquired in synchronization with a signal output from the PLG when the device under test 1 is moving. Specifically, an image is taken every time the inspected object 1 advances in 5 msec. At this time, two area cameras installed as shown in FIG. 2B are synchronized and the same field of view is simultaneously imaged. The illuminating device 101 is provided above the vertical direction, irradiates the linear laser light L downward in the vertical direction, and the installation angle φ of the two area cameras is ± 45 degrees. Although the imaging resolution is determined according to the size of the target scratch or the like, the capture pitch was set to 0.25 mm and was made to match the pixel size of the image sensor.

  Subsequently, the light section image captured by the inspected object imaging apparatus 100 will be described in detail with reference to FIGS. 3A to 4C.

  The machined product of interest in the present embodiment as the inspected object 1 has been subjected to mechanical processing such as polishing and grinding, so that its surface has a substantially constant surface texture and is not specular. strong. Therefore, the surface of the normal portion (hereinafter, also simply referred to as “normal portion”) that does not have a scratch with unevenness, a residual surface portion, rust, etc., has an extremely small unevenness of 10 μm or less. As a result, the linear laser light L applied to the normal portion exhibits almost the same reflection characteristics as schematically shown in FIG. 3A and is imaged by the area camera. In this case, in the light section image captured by the area camera, the line width of the light section line has a substantially constant value, as schematically shown in FIG. 4A. Further, in the case where the surface of the machined product has a concave portion or a convex portion, as shown in FIG. 4B, which is a schematic view of the light-section image of the recess, the light-section image has a substantially constant light-section line. The optical cutting line is bent while keeping the width.

  On the other hand, the surface remaining portion and the surface of the rust that are the focus of attention in the present embodiment have irregularities of about 100 μm, and are rougher than the normal portion. As shown schematically in FIG. 3B, the residual surface portion and the rust (hereinafter collectively referred to as “rough surface portion”) function as a diffusion surface due to the roughness of the surface. Therefore, the linear laser light L with which the rough surface portion is irradiated causes irregular reflection. In the light-section line in the light-section image captured by the area camera, the line width of the portion corresponding to the rough surface portion is compared with the normal portion as schematically shown in FIG. 4C because of the diffuse reflection as described above. Be expanded.

  In the arithmetic processing device 200 described in detail below, based on the line width of the light cutting line in the light cutting image as schematically shown in FIGS. 4A to 4C, the residual surface portion and rust are made visible. Further, the arithmetic processing device 200 generates information about the surface shape of the inspection object 1 by a so-called optical cutting method using the optical cutting image, and detects uneven scratches and the like existing on the surface of the inspection object 1.

  The configuration of the inspected object imaging apparatus 100 according to the present embodiment and the light section image generated by the inspected object imaging apparatus 100 have been described above in detail with reference to FIGS. 2A to 4C.

<Overall Configuration of Arithmetic Processing Device 200>
Subsequently, returning to FIG. 1 again, the overall configuration of the arithmetic processing device 200 according to the present embodiment will be described.
The arithmetic processing device 200 according to the present embodiment mainly includes, for example, as illustrated in FIG. 1, an imaging control unit 201, an image processing unit 203, a display control unit 205, and a storage unit 207.

  The imaging control unit 201 is realized by a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a communication device, and the like. The imaging control unit 201 implements imaging control of the inspection object 1 by the inspection object imaging device 100 according to the present embodiment. More specifically, the imaging control unit 201 sends a control signal for starting the oscillation of the laser light to the illumination device 101 when starting the imaging of the inspection object 1.

  Further, as mentioned earlier, the PLG signal is periodically sent from the transport line of the inspection object 1 (for example, one pulse of the PLG signal is moved every time the inspection object 1 moves 0.25 mm). The control unit 201 sends a trigger signal for starting imaging to the area cameras 103 and 105 each time the PLG signal is acquired.

  The image processing unit 203 is realized by, for example, a CPU, a ROM, a RAM, a communication device, and the like. The image processing unit 203 uses the image pickup data of the light section image acquired from the inspected object image pickup apparatus 100 (more specifically, the area cameras 103 and 105 of the inspected object image pickup apparatus 100), and a stripe image frame described later. To generate. After that, the generated striped image frame is subjected to image processing as described below to inspect the surface texture of the machined product that is the inspection object 1, and to check various defects that may exist on the surface. To detect. When the image processing unit 203 finishes the defect detection process on the surface of the inspection object 1, the image processing unit 203 transmits information about the obtained detection result to the display control unit 205.

  The image processing unit 203 will be described later in detail.

  The display control unit 205 is realized by, for example, a CPU, a ROM, a RAM, an output device, and the like. The display control unit 205 transmits the surface texture inspection result of the machined product, which is the inspection target 1, transmitted from the image processing unit 203 to an output device such as a display included in the arithmetic processing device 200 or the outside of the arithmetic processing device 200. Display control is performed when displaying on the provided output device or the like. As a result, the user of the surface texture inspection device 10 can grasp the inspection result regarding the surface texture of the machined product which is the inspection object 1 on the spot.

  The storage unit 207 is realized by, for example, a RAM, a storage device, or the like included in the arithmetic processing device 200 according to this embodiment. In the storage unit 207, various parameters necessary to be saved when the arithmetic processing device 200 according to the present embodiment performs some processing, the progress of processing, or various databases or programs are appropriately stored. Will be recorded. In the storage unit 207, the image pickup control unit 201, the image processing unit 203, the display control unit 205, and the like can execute read / write processing.

<About the image processing unit 203>
Next, the image processing unit 203 included in the arithmetic processing device 200 according to the present embodiment will be described in detail with reference to FIG. FIG. 5 is a block diagram showing an example of the configuration of the image processing unit included in the arithmetic processing device according to the present embodiment.

  As shown in FIG. 5, the image processing unit 203 according to the present embodiment mainly includes a data acquisition unit 211, a stripe image frame generation unit 213, an image calculation unit 215, and a detection processing unit 225.

  The data acquisition unit 211 is realized by, for example, a CPU, a ROM, a RAM, a communication device, and the like. The data acquisition unit 211 acquires image data (digital multi-valued image data) of a light section image output from the inspected object imaging device 100 (more specifically, the area cameras 103 and 105), and the storage unit 207 and the like. The images are sequentially stored in the image memory provided in. By sequentially using these digital multi-valued image data along the moving direction of the inspection object 1, a striped image frame as described later is generated.

  The light-section image acquired by the data acquisition unit 211 is, as described above, a linear laser beam irradiated on the surface of the DUT 1 at a position along the moving direction of the surface of the DUT 1. It is an image of L. By setting the gain of the area camera and the aperture of the lens appropriately in advance, for example, the portion of the light-section image irradiated with the linear laser light L is displayed in white, and the other portion is displayed in black. It can be an image. Further, the unevenness superposed on the light cutting line existing in the light cutting image or the line width of the light cutting line itself has various defects including the cross-sectional shape of the surface of the inspection object 1 and the rough surface portion existing on the surface. Includes information about etc.

  The striped image frame generation unit 213 is realized by, for example, a CPU, ROM, RAM and the like. The striped image frame generation unit 213 sequentially acquires the light section images stored along the moving direction of the DUT 1 from the image memory provided in the storage unit 207 or the like. After that, the striped image frame generation unit 213 utilizes the area including the light cutting line in each of the acquired light cutting images, and sequentially acquires the images of the area including the light cutting line along the moving direction of the DUT 1. By arranging them, a striped image frame is generated.

  The number of light section images forming one stripe image frame may be set appropriately, but for example, one stripe image frame may be composed of 256 light section images. As described above, each light section image exists at every imaging interval of the light section image (for example, 0.25 mm interval). Therefore, one striped image frame composed of 256 light section images based on the light section images taken at 0.25 mm intervals is 64 mm (= 256 × 0) on the surface of the DUT 1 along the movement direction. This corresponds to the result of imaging in the range of 0.25 mm).

  FIG. 6 shows an example of the striped image frame generated by the striped image frame generation unit 213. The striped image frame shown in FIG. 6 shows 16 light-section images out of 256 light-section images. In the striped image frame shown in FIG. 6, one line segment extending in the horizontal direction of the drawing corresponds to one light-section image, and the horizontal direction of the drawing corresponds to the x-axis direction in FIG. 2A and the like. are doing. In the striped image frame shown in FIG. 6, the vertical direction of the drawing corresponds to the y-axis direction (that is, the moving direction of the device under test 1) in FIG. 2A and the like.

  When the stripe image frame generation unit 213 generates the stripe image frame as shown in FIG. 6, the stripe image frame generation unit 213 outputs the generated stripe image frame to the image calculation unit 215 described later. In addition, the striped image frame generation unit 213 may associate the data corresponding to the generated striped image frame with time information regarding the date and time when the striped image frame was generated, and store the history information in the storage unit 207 or the like. .

  The image calculation unit 215 is realized by, for example, a CPU, a ROM, a RAM, and the like. The image calculation unit 215, based on the striped image frame generated by the striped image frame generation unit 213, the depth image indicating the concavo-convex state on the surface of the inspection object 1 and the linear laser beam on the surface of the inspection object 1. A brightness image representing the brightness distribution of L and a line width image in which the distribution of the line width in the moving direction of the linear laser light L on the surface of the inspection object 1 is associated with the brightness value are calculated. As shown in FIG. 5, the image calculation unit 215 includes a light section line processing unit 217, a depth image calculation unit 219, a luminance image calculation unit 221, and a line width image calculation unit 223.

The light section line processing unit 217 is realized by, for example, a CPU, a ROM, a RAM, and the like. The light section line processing unit 217 calculates the light section line feature amount including the displacement amount of the light section line (the degree of bending of the bright line) for each light section line included in the striped image frame. Hereinafter, the processing executed by the optical cutting line processing unit 217 and the calculated optical cutting line characteristic amount will be described in detail with reference to FIGS. 7A and 7B.
FIG. 7A is an explanatory diagram schematically showing a striped image frame. FIG. 7B is an explanatory diagram for explaining the optical cutting line processing performed by the optical cutting line processing unit.

In FIG. 7A, it is assumed that there are N light cutting lines in one striped image frame and the horizontal length of the striped image frame is M pixels. Further, one light section image including one light section line is composed of vertical y _n pixels × horizontal M pixels. It should be noted that the size of the vertical pixel number y _n of one light-section image including one light-section line (in other words, the number of vertical pixels cut out when a striped image frame is generated from one light-section image). The size of y _n ) can be determined by roughly calculating the range of the height of the concave portion or the convex portion that may exist in the inspection object 1 in advance based on past operation data and the like. is there.

Here, for convenience of description, the X axis is taken in the x-axis direction (the horizontal direction of the striped image frame in FIG. 7A) orthogonal to the moving direction of the DUT 1, and the y-axis direction corresponding to the moving direction of the DUT 1 is taken. It is assumed that the Y axis is taken (in the vertical direction of the striped image frame in FIG. 7A) and the position of the pixel in the striped image frame is represented by XY coordinates. In the following description, the position of the m-th pixel (1 ≦ m ≦ M) from the left side of the j (1 ≦ j ≦ N) th light section line existing in the striped image frame (that is, represented by X _{j, m} ). Position).

The light cutting line processing unit 217 first determines the X coordinate position (the position represented by X _{j, m} in this description) of the light cutting line of interest (hereinafter, also simply referred to as “line”). When the selection is made, as shown in FIG. 7B, the distribution of the pixel values (that is, the brightness values of the light cutting lines) associated with the pixels at the focused X coordinate position of the focused line is referred to. At this time, the light cutting line processing unit 217 does not perform the process described below for all the pixels at the X coordinate position in the light cutting image, but instead, the reference position Y _s of the Y coordinate in the light cutting image. For the pixels belonging to the range of W before and after (that is, the pixels belonging to the range of Y _s −W to Y _s + W), the processing described below is performed.

Here, the reference position Y _s Y-coordinate is the position in the y-axis direction specified in advance for j-th line of the light section image of fringe image frame. The parameter W that defines the processing range can be determined as follows. That is, the range of the height of the concave portion or the convex portion that may be present in the inspection object 1 is specified based on the past operation data, and the range of the front and rear W of the reference position Y _s of the Y coordinate in the light section image is determined. The size of the parameter W may be roughly calculated in advance so as to be included in the light section image and then appropriately determined. If the value of the parameter W can be reduced, the processing load of the optical cutting line processing unit 217 described later can be reduced.

Light section line processor 217, first, from among the pixels included in the range of Y _s -W~Y _s + _W, has a luminance value equal to or larger than a predetermined threshold value Th for identifying pixels corresponding to the light section line Identify the pixel. In the example shown in FIG. 7B, the three pixels represented by Y _{j, k} , Y _{j, k + 1} , Y _{j, k + 2} respectively have luminance values I _{j, k} , I _{j, k + 1} , I _j that are equal to or greater than the threshold Th. _{, K + 2} . Therefore, the light section line processing unit 217 sets the number p _{j, m} = 3 _, which is the sum of pixels having a luminance value equal to or higher than the predetermined threshold value Th in the line width direction. The number p _{j, m} obtained by adding the pixels having the luminance value equal to or higher than the predetermined threshold value Th in the line width direction is a value corresponding to the number of pixels of the bright line at the position (j, m), so to speak, and the light cutting line feature amount. one of. In addition, the optical cutting line processing unit 217 performs information (Y _{j, k} , I _{j, k} ), (Y _{j, k + 1} , I _{j, k + 1} ), (Y _{j, k + 2} ) regarding the extracted pixels in the following processing. , I _{j, k + 2} ) (hereinafter sometimes simply abbreviated as (Y, I)), the optical cut line feature quantity is calculated.

Further, the light section line processing unit 217 calculates the total brightness K _{j, m} of the extracted pixels by using the parameter p _{j, m} and the information (Y, I) regarding the extracted pixels. In the case of the example shown in FIG. 7B, the sum of the brightness calculated by the light section line processing unit 217 is K _{j, m} = I _{j, k} + I _{j, k + 1} + I _{j, k + 2} . The total sum K _{j, m of the} brightness is also one of the light section line feature amounts.

Further, the light section line processing unit 217 uses the information (Y, I) regarding the extracted pixel and the reference position Y _{s of the} Y coordinate to determine the barycentric position Y _C (j, j of the extracted pixel in the Y direction. m) and the displacement amount Δd _{j, m} = Y _s −Y _C (j, m) of the center of gravity position Y _C (j, m) from the reference position Y _s .

Here, the barycentric position Y _C (j, m) has a value represented by the following Expression 101, where the set of extracted pixels is represented as A. Therefore, in the case of the example shown in FIG. 7B, the center-of-gravity position Y _C (j, m) has a value represented by the following expression 101a.

Here, the position in the Y-axis direction corresponding to the pixel is, so to speak, a value quantized by the take-in pitch (for example, 0.25 mm) in the image pickup device 100 for inspection. On the other hand, the center-of-gravity position Y _C (j, m) calculated by the calculation shown in the above equation 101 is a value calculated by using a numerical calculation called division, so that The value can be smaller than the import pitch (so-called quantization unit). Therefore, the displacement amount Δd _{j, m} calculated by using the center-of-gravity position Y _C (j, m) also has a value that can be smaller than the movement width. The displacement amount Δd _{j, m} calculated in this way is also one of the optical cutting line feature amounts.

  The light section line processing unit 217 calculates the above-described three types of feature amounts for M elements included in each section line. As a result, as shown in FIGS. 8A to 8C, a two-dimensional array of M columns × N rows is generated with respect to the displacement amount Δd of the light cutting line, the total brightness K, and the number of pixels p of the bright line.

  The light section line processing unit 217 outputs the feature amount relating to the displacement amount Δd of the light section line among the calculated light section line feature amounts to the depth image calculation unit 219 described later. In addition, the light section line processing unit 217 outputs the total amount K of brightness and the feature value related to the number of pixels p of the bright line among the calculated light section line feature values to the brightness image calculation unit 221 described later. Further, the light-section line processing unit 217 outputs the feature amount related to the pixel number p of the bright line among the calculated light-section line feature amounts to the line width image calculation unit 223 described later.

  The depth image calculation unit 219 is realized by, for example, a CPU, ROM, RAM and the like. The depth image calculation unit 219, based on the light section line characteristic amount generated by the light section line processing unit 217 (particularly, the feature amount related to the displacement amount Δd), the depth image representing the unevenness state of the surface of the inspection object 1. To calculate.

  Specifically, the depth image calculation unit 219 forms a feature amount (two-dimensional array) relating to the displacement amount Δd as shown in FIG. 8A and an angle between the linear laser light L and the optical axis of the area camera ( 2A and 2B, the depth image is calculated. The depth image is an image showing a two-dimensional unevenness distribution in which the one-dimensional unevenness distribution at each position in the Y-axis direction is sequentially arranged along the Y-axis direction.

  First, the relationship between the height of the unevenness existing on the surface of the inspection object 1 and the displacement amount Δd of the light cutting line will be described with reference to FIG. 9. FIG. 9 is an explanatory diagram showing the relationship between the displacement of the light section line and the height of the defect.

  FIG. 9 schematically shows a case where a recess is present on the surface of the DUT 1. Here, the difference between the height of the surface position and the height of the bottom of the recess when there is no recess on the surface of the DUT 1 is represented by Δh. Focusing on the case where the vertically incident linear laser light L is surface-reflected, when there is no concave portion on the surface of the DUT 1, the reflected light propagates like the light ray A in FIG. When a concave portion is present on the surface of the inspection body 1, reflected light propagates like the light ray B in FIG. The deviation between the light ray A and the light ray B will be observed as the displacement amount Δd of the light cutting line in the present embodiment. Here, as is apparent from the geometrical positional relationship, the displacement Δd of the light cutting line and the depth Δh of the recess have a relationship of Δd = Δh · sin φ.

  Although the case where the concave portion is present on the surface of the inspection object 1 has been described with reference to FIG. 9, the same relationship is established even when the convex portion is present on the surface of the inspection object 1.

  The depth image calculation unit 219 uses the relationship as described above, and relates to the unevenness of the surface of the inspection object 1 based on the feature amount regarding the displacement amount Δd of the light cutting line calculated by the light cutting line processing unit 217. The amount Δh is calculated.

  Here, the displacement amount Δd of the light cutting line used for calculating the depth image is calculated based on the center of gravity position of the light cutting line as described above, and has a value smaller than the take-in pitch. It is a good value. Therefore, the depth image calculated by the depth image calculation unit 219 is an image in which the unevenness is reproduced with a resolution smaller than the pixel size of the image sensor.

  It should be noted that, as shown in FIG. 10, there are cases where distortion such as bending occurs in the optical cutting line due to a change in the shape of the surface of the DUT 1. On the other hand, in the surface texture inspection method according to the present embodiment, the unevenness superimposed on the light cutting line serves as information regarding the cross-sectional shape of the surface of the inspection object 1 and surface defects existing on the surface. Therefore, when calculating the depth image based on the displacement amount Δd of the light section line, the depth image calculation unit 219 performs distortion correction processing for each light section line, and the unevenness superimposed on the light section line. You may extract only the information regarding. By performing such a distortion correction process, it is possible to obtain only the information of the unevenness flaws existing on the surface of the inspection object 1 even when the light cutting line is distorted such as curved. .

  As a specific example of the distortion correction process, (i) a process of performing a fitting process using a multidimensional function or various nonlinear functions, and a process of calculating a difference between the obtained fitting curve and the observed light section line, ( ii) A process of applying a low-pass filter such as a floating filter or a median filter by utilizing the fact that the information on the unevenness is a high-frequency component can be mentioned. By performing such distortion correction processing, it becomes possible to flatten the optical cutting line while retaining the information on the unevenness flaws existing on the surface of the inspection object 1.

  The depth image calculation unit 219 outputs the information regarding the depth image calculated as described above to the detection processing unit 225 described later.

  The brightness image calculation unit 221 is realized by, for example, a CPU, a ROM, a RAM, and the like. The luminance image calculation unit 221 calculates the line on the surface of the inspection object 1 based on the light-section line feature amount generated by the light-section line processing unit 217 (particularly, the feature amount regarding the total brightness K and the number p of pixels of the bright line). A luminance image representing the luminance distribution of the laser light L in the shape of a circle is calculated.

Specifically, the luminance image calculation unit 221 has a feature amount (two-dimensional array) relating to the total luminance K as shown in FIG. 8B and a feature amount relating to the pixel number p of the bright line as shown in FIG. 8C ( (Two-dimensional array), average brightness K _AVE (j, m) = K _{j, m} / p _{j, m} (1 ≦ j ≦ N, 1 ≦ m ≦), which is the average value of the total brightness in the line width direction. Calculate M). After that, the luminance image calculation unit 221 sets the data array including the calculated average luminance K _AVE (j, m) as the luminance image of the inspection object 1 of interest. The luminance image is an image showing a two-dimensional luminance distribution in which the one-dimensional luminance distribution of the linear laser light L at each position in the Y-axis direction is sequentially arranged along the Y-axis direction.

  The luminance image calculation unit 221 outputs the information regarding the luminance image calculated as described above to the detection processing unit 225 described later.

  The line width image calculation unit 223 is realized by, for example, a CPU, a ROM, a RAM, and the like. The line width image calculation unit 223, based on the light section line feature amount generated by the light section line processing unit 217 (particularly, the feature amount relating to the pixel number p of the bright line), forms a linear laser beam on the surface of the inspection object 1. A line width image in which the distribution of the line width in the moving direction of L is associated with the luminance value is calculated.

  Hereinafter, the line width image calculation processing in the line width image calculation unit 223 will be described with reference to FIGS. 11 to 13. FIG. 11 is an explanatory diagram for explaining the line width of the light cutting line in the normal portion and the rough surface portion. FIG. 12A is an explanatory diagram for explaining the line width of the light cutting line in the normal portion, and FIG. 12B is an explanatory diagram for explaining the line width of the light cutting line in the rough surface portion. FIG. 13 is an explanatory diagram for describing the line width image according to the present embodiment.

  As described above, in the rough surface portion such as the residual surface portion and rust that is focused on in the present embodiment, the rough surface portion functions as a scattering surface, and as a result, the linear laser light L irradiated on the rough surface portion is scattered by the rough surface portion. To be done. Therefore, as schematically shown in FIG. 4C and FIG. 11, the line width of the light cutting line is enlarged at the position of the light cutting image corresponding to the rough surface portion.

  Assuming that an optical cutting line as schematically shown in FIG. 11 is obtained, the position corresponding to the AA ′ cutting line corresponds to the normal portion, and the position corresponding to the BB ′ cutting line corresponds to the rough portion. It corresponds to the face part. In this case, in the luminance distribution of the normal portion along the AA ′ cutting line, a pixel having a luminance value equal to or higher than a predetermined threshold Th for identifying the pixel corresponding to the light cutting line is schematically shown in FIG. 12A. It is assumed that there are 3 pixels as shown. Similarly, in the luminance distribution of the rough surface portion along the B-B ′ cutting line, it is assumed that the pixels having the luminance value equal to or greater than the threshold Th are 8 pixels as schematically shown in FIG. 12B.

  It is assumed that, in the inspected object imaging apparatus 100, for example, the line width of the linear laser beam L is set to correspond to 2 to 4 pixels. Since the line width of the linear laser light L is recognized to increase in the rough surface portion, the line width of the linear laser light L in the rough surface portion is set to 4 pixels which is the set value in the inspection object imaging device 100. The value will exceed. Therefore, regarding the line width of the linear laser beam L, it is possible to distinguish between the normal portion and the rough surface portion by setting a predetermined threshold value Th2 for specifying the pixel corresponding to the rough surface portion in advance. Become. For example, it is assumed that the line width of the linear laser beam L in the normal portion is set to 2 to 4 pixels in the inspected object imaging apparatus 100. In this case, by setting the threshold value Th2 to 5 pixels in consideration of the margin, it is possible to distinguish a portion having a line width of 5 pixels or more as a rough surface portion.

  From the above viewpoints, the line width image calculation unit 223 handles the rough surface portion by performing the threshold value determination of the feature amount related to the pixel number p of the bright line generated by the light section line processing unit 217 based on the threshold value Th2. It is possible to specify the pixel position.

Next, with reference to FIG. 13, a specific method of calculating the line width image in the line width image calculation unit 223 will be described.
By setting the threshold value Th2 as described above, it is possible to specify the position of the rough surface portion, while the line width image generated by the line width image calculation unit 223 prevents the normal portion from being revealed. It is important to determine the brightness values that make up Therefore, in the line width image calculation unit 223 according to the present embodiment, for each light cutting line in the striped image frame, the line width at each position in the extending direction (Y-axis direction) of the light cutting line and a predetermined threshold line. The line width image is calculated by calculating the difference from the width and assigning the brightness value according to the magnitude of the calculated difference.

  More specifically, the line width image calculation unit 223 refers to the feature amount regarding the pixel number p of the bright line generated by the light section line processing unit 217, and determines the pixel number p of the bright line at each position and the threshold line width. The difference from the corresponding threshold Th2 is calculated. It is possible that the difference between the normal portion and the threshold Th2 may be a negative value, but the difference value in this case is preferably set to zero instead of being a negative value. After that, the line width image calculation unit 223 determines the brightness value at each pixel position such that the brightness value of the pixels forming the line width image increases as the calculated difference value increases.

  For example, consider a case where the threshold Th2 is 5 pixels and the line width image is generated as an 8-bit image. In this case, if the range of all brightness values (0 to 255) is to be used in the 8-bit image, the line width image calculation unit 223 should determine the brightness value at each pixel position as follows, for example. Good. In addition, in the example shown below, the case where the 8-bit full scale is used is shown, but the 8-bit full scale may not be used. However, the visibility of the generated line width image can be improved by setting the brightness value within the full scale range.

Difference value = 0 (or 0 or less): luminance value 0
Difference value = 1: brightness value 95
Thereafter, the brightness value 32 is added every time the difference value becomes +1. (For example, when the difference value = 2, the brightness value = 95 + 32 = 127)
When the difference value = 5 or more, the fixed value is 255 (full scale).

  It should be noted that the method of assigning the brightness value according to the difference value is not limited to the above example, and an arbitrary assignment method is adopted as long as the brightness value increases as the difference value increases. It is possible. Further, in the above example, the case where the line width image is generated as an image having a luminance value of 8 bits has been described, but it goes without saying that the line width image may be generated as an image having a luminance value exceeding 8 bits. .

  By performing such processing, the line width image calculation unit 223 causes, for example, the light cutting line as shown on the left side of FIG. 13 (and the feature amount regarding the pixel number p of the bright line generated from the light cutting line). From this, a line width image as shown on the right side of FIG. 13 can be generated. Note that in the example shown in FIG. 13, the line width image becomes black at a position where the luminance value = 0 (that is, a normal portion), and the luminance value becomes large (that is, corresponding to the rough surface portion and at the rough surface portion). The larger the surface irregularities, the whiter the image is. The line width image generated by such processing is a two-dimensional line width in which the one-dimensional distribution of the line width of the linear laser light L at each position in the Y-axis direction is arranged in order along the Y-axis direction. It is an image showing distribution.

  The line width image calculation unit 223 outputs the information regarding the line width image calculated as described above to the detection processing unit 225 described later.

Returning to FIG. 5 again, the detection processing unit 225 will be described.
The detection processing unit 225 is realized by, for example, a CPU, a ROM, a RAM, and the like. The detection processing unit 225 uses the depth image calculation unit 219, the brightness image calculation unit 221, and the line width image calculation unit 223 to calculate the depth image, the brightness image, and the line width image, respectively. Detect properties.

  The detection processing unit 225 has a defect part specifying function for specifying a defect part based on a depth image, a brightness image, and a line width image, and a feature amount extracting function for extracting a feature amount regarding the form and pixel value of the specified defect part. And a defect discriminating function for discriminating a defect type, a degree of harmfulness, and the like based on the extracted feature amount. Hereinafter, these functions will be briefly described.

Defect portion specifying function The detection processing unit 225 emphasizes the area of the rough surface portion for each pixel of the acquired line width image by filter processing that obtains a linear sum of luminance values with surrounding pixels, if necessary. Then, it is determined whether or not the obtained value is equal to or larger than the first threshold value for specifying the rough surface portion. By performing such a filter process and the determination process based on the filter process result, the detection processing unit 225 can generate a binarized image for specifying the site of the rough surface portion. In such a binarized image, a pixel whose calculated value is less than the first threshold corresponds to a normal portion (that is, pixel value of binary image = 0), and the calculated value is equal to or larger than the first threshold. The existing pixel corresponds to the rough surface portion (that is, the pixel value of the binarized image = 1). Furthermore, the detection processing unit 225 identifies the position of each rough surface portion (that is, the background residual portion and rust) by combining the portions of the rough surface portion that are continuously generated.

  Similarly, the detection processing unit 225 performs filter processing to obtain a linear sum of pixel values (values representing depth or brightness values) with surrounding pixels for each pixel of the acquired depth image and brightness image. The areas such as the vertical line flaws, the horizontal line flaws, and the minute flaws are emphasized, and it is determined whether or not the obtained value is equal to or more than the second threshold value for identifying the defective portion. By performing such filter processing and determination processing based on the filter processing result, the detection processing unit 225 can generate a binarized image for identifying a defective portion. In such a binarized image, a pixel whose calculated value is less than the second threshold corresponds to a normal location (that is, the pixel value of the binarized image = 0), and the calculated value is equal to or greater than the second threshold. The existing pixel corresponds to the defective portion (that is, the pixel value of the binarized image = 1). Furthermore, the detection processing unit 225 identifies each defective portion by combining defective portions that are continuously generated.

○ Feature Extraction Function When the detection processing unit 225 specifies a defect portion (that is, a rough surface portion) of a line width image by the defect portion specifying function, the detection processing unit 225 obtains the feature amount regarding the form and the brightness value of the defect portion for each identified defect portion. Extract. Examples of the feature amount related to the form of the defective portion include the width of the defective portion, the length of the defective portion, the perimeter of the defective portion, the area of the defective portion, and the area of the circumscribed rectangle of the defective portion. Further, as the feature amount relating to the brightness value of the defective portion, the maximum value, the minimum value and the average value of the brightness of the defective portion can be mentioned.

  Further, when the detection processing unit 225 specifies the defective portion of the depth image and the luminance image by the defective portion specifying function, the detection processing unit 225 extracts the feature amount related to the form and pixel value of the defective portion for each specified defective portion. Examples of the feature amount related to the form of the defective portion include the width of the defective portion, the length of the defective portion, the perimeter of the defective portion, the area of the defective portion, and the area of the circumscribed rectangle of the defective portion. Further, as the feature amount regarding the pixel value of the defective portion, the maximum value, the minimum value, and the average value of the depth of the defective portion can be cited for the depth image, and the maximum value of the luminance of the defective portion for the luminance image. A value, a minimum value, an average value, etc. can be mentioned.

Defect Discrimination Function The detection processing unit 225 discriminates the defect type, the degree of harm, and the like for each defect site based on the extracted feature quantity when the feature quantity of each defective site is extracted by the feature quantity extraction function. The determination process of the type of defect, the degree of harmfulness, and the like based on the feature amount is performed using a logic table as shown in FIG. 14, for example. That is, the detection processing unit 225 determines the type of defect and the degree of harmfulness based on the determination condition represented by the logic table illustrated in FIG.

  As illustrated in FIG. 14, the types of defects (defects A1 to An) are described as items in the vertical direction of the logic table, and the types of feature amounts (feature amount B1 as items in the horizontal direction of the logic table. -Characteristic amount Bm) is described. Further, in each cell of the table defined by the type of defect and the feature amount, a discriminating conditional expression (conditional expression C11 to conditional expression Cnm) depending on the size of the corresponding characteristic quantity is described. Each row of such a logic table forms a set, which serves as a determination condition for each defect type. The determination processing is performed in order from the type described in the top row, and ends when all the determination conditions described in any one row are satisfied.

  Such a logic table is obtained by a known method using a database constructed by a learning process in which past operation data and a result of identification of a defect type and a harmful degree by an inspector based on the operation data are used as teacher data. It is possible to generate.

  The detection processing unit 225 identifies the defect type and the degree of harmfulness for each defect site detected in this way, and outputs the obtained detection result to the display control unit 205. As a result, the information regarding the defects existing on the surface of the machined product which is the inspection object 1 is output to the display unit (not shown). Further, the detection processing unit 225 may output the obtained detection result to an external device such as a manufacturing control process computer or the like, and use the obtained detection result to create a defect report of the product. Good. Further, the detection processing unit 225 may store the information regarding the detection result of the defective portion in the storage unit 207 or the like as history information in association with the time information regarding the date and time when the information is calculated.

  In the above description, the case of determining the defect type and the degree of harm using the logic table has been described, but the method of determining the defect type and the degree of harm is not limited to the above example. For example, a discriminator such as a neural network or a support vector machine (SVM) is generated by a learning process in which past operation data and a result of identification of a defect type and a harmfulness degree by an inspector based on the operation data are used as teacher data, Such a discriminator may be used for discriminating the type of defect and the degree of harmfulness.

  As shown in the following examples, it is possible to find a candidate site for the rough surface portion by focusing on the luminance image generated by the conventional light cutting method. However, since the rough surface portion is composed of minute irregularities, even if attention is paid to such a luminance image, it is difficult to distinguish the area of the luminance image due to noise or dust from the rough surface portion, It was not possible to discriminate which part corresponds to the rough surface part. On the other hand, as described above, the detection processing unit 225 according to the present embodiment performs the defect detection processing based on the predetermined threshold value determination using the line width image, so that it is difficult to distinguish by the conventional optical cutting method. The rough surface portion (that is, the surface remaining portion and rust) can be easily made visible.

  Also, the detection processing unit 225 performs the defect detection processing based on the depth image and the luminance image, with respect to a portion other than the portion where the rough surface portion (that is, the background residual portion and rust) is detected based on the line width image. You may implement the detection process of a defective part like this. This makes it possible to speed up defect detection processing based on the depth image and the luminance image.

  Further, as described above, the portion corresponding to the rough surface portion is also extracted as the defect candidate portion in the brightness image. Therefore, the detection processing unit 225 confirms whether or not the site of the rough surface portion specified based on the line width image is extracted as the defect candidate site also in the luminance image, and double-checks the detection result. May be.

  The configuration of the image processing unit 203 included in the arithmetic processing device 200 according to the present embodiment has been described above in detail.

  In the above description, the case where the depth image calculation unit 219 performs an approximate correction process such as a difference calculation process or a low pass filter process when calculating the depth image has been described. However, the approximation correction processing may be performed by the light section line processing unit 217 before the light section line processing unit 217 calculates the light section line feature amount.

  Heretofore, an example of the functions of the arithmetic processing device 200 according to the present embodiment has been shown. Each component described above may be configured by using a general-purpose member or circuit, or may be configured by hardware specialized for the function of each component. Further, the function of each component may be performed by the CPU or the like. Therefore, it is possible to appropriately change the configuration to be used according to the technical level at the time of implementing the present embodiment.

  Note that it is possible to create a computer program for realizing each function of the arithmetic processing device according to the present embodiment as described above, and install the computer program in a personal computer or the like. It is also possible to provide a computer-readable recording medium in which such a computer program is stored. The recording medium is, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, or the like. Further, the above computer program may be distributed, for example, via a network without using a recording medium.

  The configuration of the surface texture inspection device 10 according to this embodiment has been described above in detail. By using the surface texture inspection device 10 according to the present embodiment, it is possible to detect the background residual portion and rust remaining on the machined surface with the same device configuration as the device based on the conventional optical cutting method. . In addition, since it is possible to detect irregularities, surface patterns, etc. based on the conventional light cutting method, it is possible to inspect a wide variety of defective portions over the entire machined surface of the machined product.

  Further, the application destination of the surface texture inspection apparatus 10 according to the present embodiment is not limited to the specific machined product as described above, and the roughness in the defective portion is different from that in the normal portion. If it is such a product, the surface texture inspection device 10 according to the present embodiment can be applied. In particular, by making a two-dimensional image of the distribution state of the background remaining portion and the rust portion, which has low visibility, it becomes easy to identify the defective portion by image processing, and an image with good visibility is used even in visual inspection. It becomes possible.

<About surface property inspection method>
Subsequently, the flow of the surface texture inspection method according to the present embodiment will be briefly described with reference to FIG. FIG. 15 is a flow chart showing an example of the flow of the surface texture inspection method according to this embodiment.

  First, the inspected object imaging apparatus 100 of the surface texture inspection apparatus 10 uses a linear laser beam L under the control of the imaging control unit 201 of the arithmetic processing device 200 to process a machined article which is the inspected object 1. The surface is imaged to generate a light section image (step S101). After that, the inspection object imaging device 100 outputs the generated light-section image to the arithmetic processing device 200. When the data acquisition unit 211 of the image processing unit 203 included in the arithmetic processing device 200 acquires the image data of the light-section image, the acquired light-section image is stored in the storage unit 207 or the like along the moving direction of the DUT 1. The images are sequentially stored in the image memory provided in.

  Next, the striped image frame generation unit 213 of the image processing unit 203 included in the arithmetic processing device 200 sequentially arranges the acquired light-section images along the moving direction of the DUT 1 to generate a striped image frame ( Step S103). The striped image frame generation unit 213 outputs the generated striped image frame to the light section line processing unit 217.

  The light section line processing unit 217 uses the generated striped image frame and, for each light section line, the number of pixels having a brightness equal to or higher than a predetermined threshold Th, the sum of the brightness of the pixel, and the displacement of the light section line. The amount is calculated (step S105). These calculation results are used as the light section line feature amount. The calculated light section line feature amount is output to the depth image calculation unit 219, the luminance image calculation unit 221, and the line width image calculation unit 223, respectively.

  The depth image calculation unit 219 calculates a depth image by using the calculated light cutting line feature amount (particularly, the feature amount relating to the displacement amount of the light cutting line) (step S107). In addition, the brightness image calculation unit 221 calculates the brightness image by using the calculated light-section line feature amount (particularly, the feature amount related to the number of pixels of the bright line and the feature amount related to the total brightness) (step S107). ). Further, the line width image calculation unit 223 calculates the line width image by using the calculated light section line feature amount (particularly, the feature amount regarding the number of pixels of the bright line) (step S107). The depth image calculation unit 219, the luminance image calculation unit 221, and the line width image calculation unit 223 output each calculated image to the detection processing unit 225.

  Subsequently, the detection processing unit 225 performs the detection processing of the surface texture of the inspection object 1 by using the calculated depth image, luminance image, and line width image (step S109). As a result, the detection processing unit 225 can specify the type of defect and the degree of harmfulness of various defective portions existing on the surface of the inspection object 1. Through the above flow, various defects existing on the surface of the machined product which is the inspection object 1 will be detected.

  Heretofore, an example of the flow of the inspection object inspection method according to the present embodiment has been briefly described.

<About the hardware configuration of the arithmetic processing device 200>
Next, the hardware configuration of the arithmetic processing device 200 according to the present embodiment will be described in detail with reference to FIG. FIG. 16 is a block diagram for explaining the hardware configuration of the arithmetic processing device 200 according to the embodiment of the present invention.

  The arithmetic processing device 200 mainly includes a CPU 901, a ROM 903, and a RAM 905. Further, the arithmetic processing device 200 further includes a bus 907, an input device 909, an output device 911, a storage device 913, a drive 915, a connection port 917, and a communication device 919.

  The CPU 901 functions as a central processing unit and a control unit, and controls the whole operation or a part thereof in the arithmetic processing unit 200 according to various programs recorded in the ROM 903, the RAM 905, the storage device 913, or the removable recording medium 921. To do. The ROM 903 stores programs used by the CPU 901, calculation parameters, and the like. The RAM 905 temporarily stores programs used by the CPU 901, parameters that change appropriately during execution of the programs, and the like. These are connected to each other by a bus 907 composed of an internal bus such as a CPU bus.

  The bus 907 is connected to an external bus such as a PCI (Peripheral Component Interconnect / Interface) bus via a bridge.

  The input device 909 is an operation unit operated by a user, such as a mouse, a keyboard, a touch panel, a button, a switch, and a lever. The input device 909 may be, for example, a remote control unit (so-called remote controller) that uses infrared rays or other radio waves, or is an external connection device 923 such as a PDA corresponding to the operation of the arithmetic processing device 200. May be. Further, the input device 909 is composed of, for example, an input control circuit that generates an input signal based on the information input by the user using the above-described operation unit and outputs the input signal to the CPU 901. By operating the input device 909, the user can input various data to the arithmetic processing device 200 and instruct a processing operation.

  The output device 911 is configured by a device capable of visually or auditorily notifying the user of the acquired information. Such devices include display devices such as CRT display devices, liquid crystal display devices, plasma display devices, EL display devices and lamps, audio output devices such as speakers and headphones, printer devices, mobile phones, and facsimiles. The output device 911 outputs, for example, the results obtained by various processes performed by the arithmetic processing device 200. Specifically, the display device displays the results obtained by the various processes performed by the arithmetic processing device 200 as text or images. On the other hand, the audio output device converts an audio signal composed of reproduced audio data and acoustic data into an analog signal and outputs the analog signal.

  The storage device 913 is a device for storing data configured as an example of a storage unit of the arithmetic processing device 200. The storage device 913 includes, for example, a magnetic storage device such as a HDD (Hard Disk Drive), a semiconductor storage device, an optical storage device, a magneto-optical storage device, or the like. The storage device 913 stores programs executed by the CPU 901, various data, various data acquired from the outside, and the like.

  The drive 915 is a reader / writer for a recording medium, and is built in or externally attached to the arithmetic processing device 200. The drive 915 reads the information recorded on the removable recording medium 921 such as a mounted magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, and outputs it to the RAM 905. The drive 915 can also write a record on a removable recording medium 921 such as a mounted magnetic disk, optical disk, magneto-optical disk, or semiconductor memory. The removable recording medium 921 is, for example, a CD medium, a DVD medium, a Blu-ray (registered trademark) medium, or the like. The removable recording medium 921 may be a CompactFlash (registered trademark) (CompactFlash: CF), a flash memory, an SD memory card (Secure Digital memory card), or the like. Further, the removable recording medium 921 may be, for example, an IC card (Integrated Circuit card) equipped with a non-contact type IC chip, an electronic device, or the like.

  The connection port 917 is a port for directly connecting a device to the arithmetic processing device 200. Examples of the connection port 917 include a Universal Serial Bus (USB) port, an IEEE 1394 port, a SCSI (Small Computer System Interface) port, an RS-232C port, and an HDMI (registered trademark) (High-Definition Multimedia) port. By connecting the external connection device 923 to the connection port 917, the arithmetic processing device 200 acquires various data directly from the external connection device 923 or provides various data to the external connection device 923.

  The communication device 919 is, for example, a communication interface including a communication device or the like for connecting to the communication network 925. The communication device 919 is, for example, a wired or wireless LAN (Local Area Network), Bluetooth (registered trademark), or a communication card for WUSB (Wireless USB). The communication device 919 may be a router for optical communication, a router for ADSL (Asymmetrical Digital Subscriber Line), or a modem for various kinds of communication. The communication device 919 can send and receive signals and the like to and from the Internet and other communication devices, for example, according to a predetermined protocol such as TCP / IP. The communication network 925 connected to the communication device 919 is configured by a network connected by wire or wirelessly, and is, for example, the Internet, a home LAN, an in-house LAN, infrared communication, radio wave communication or satellite communication. May be.

  The example of the hardware configuration capable of realizing the functions of the arithmetic processing device 200 according to the embodiment of the present invention has been described above. Each component described above may be configured by using a general-purpose member, or may be configured by hardware specialized for the function of each component. Therefore, it is possible to appropriately change the hardware configuration to be used according to the technical level at the time of implementing the present embodiment.

  Hereinafter, the surface texture inspection apparatus and the surface texture inspection method according to the present invention will be specifically described with reference to Examples. The following examples are merely examples of the surface texture inspection device and the surface texture inspection method according to the present invention, and the surface texture inspection device and the surface texture inspection method according to the invention are limited to the following examples. Not a thing.

  In the examples described below, the surface texture inspection apparatus 10 having the inspection object imaging apparatus 100 having the configuration shown in FIG. 2B was used to inspect the surface texture of the inspection object.

  In this embodiment, as the inspected object 1, a disk-shaped processed product manufactured by grinding a material after hot forming a billet, which is an intermediate material containing Fe as a main component, is used. The surface to be inspected (surface extending in the radial direction of the disk) was used as the inspection surface. The diameter of such a disk-shaped processed product is 860 mm.

  A red LD module that emits a red laser beam is used as an illumination device of the imaging device 100 for an object to be inspected, and a point laser beam (output: 100 mW) emitted from such a module is incident on a cylindrical lens, whereby a linear shape is obtained. The laser light L of was obtained. The linear laser light L is controlled so as to have a length (length in the x-axis direction in FIG. 2B) corresponding to the radius (430 mm) of the disk-shaped processed product, and is rotating in the disk shape. The ground surface of the processed product was irradiated. The line width of the linear laser beam L with which the surface of the inspection object 1 is irradiated is set to 0.25 mm (250 μm).

  As the area cameras 103 and 105, commercially available cameras each having a CCD of 2048 pixels × 2048 pixels (pixel size: 5.5 μm × 5.5 μm) mounted as an image pickup element were used. The frame rate of such an image sensor is 200 fps. The focal length of the lens mounted on the camera is 24 mm and the angle of view is 26 °. The pixel size of the imaged image is 0.25 mm × 0.25 mm, and the line width of the linear laser light L is captured with the width of the bright line of 2 to 4 pixels on the imaged image.

  When the disk-shaped processed product is rotating in the direction perpendicular to the radial direction and parallel to the grinding surface, the images are continuously displayed by the two area cameras in synchronization with the signal output from the PLG. I got it. Specifically, imaging was performed every time the disk-shaped processed product rotated for 5 msec. The illuminating device 101 is provided vertically upward, irradiates the linear laser light L vertically downward, and the installation angle φ of the two area cameras is ± 45 degrees. The image pickup pitch was set to 0.25 mm to match the pixel size of the image sensor.

  The light-section image obtained by the above-described device to be inspected 100 is subjected to image processing by the arithmetic processing device 200 having the configuration described above, and the surface texture of the ground surface of the disk-shaped processed product is inspected. In calculating the line width image, the line width threshold Th2 was set to 5 pixels, and the brightness value was assigned using the 8-bit full scale as previously mentioned.

  Of the obtained light-section images, the light-section image of the portion corresponding to the normal portion, the light-section image of the portion corresponding to the concave portion, and the light-section image of the portion corresponding to the background remaining portion are summarized in FIG. Indicated. As is clear from FIG. 17, in the light-section image corresponding to the normal part, a substantially straight line segment is imaged while the line width of the light-section line remains substantially constant, and in the light-section image corresponding to the recess, It can be seen that the line width of the light cutting line remains almost unchanged, and the light cutting line is bent at a position corresponding to the recess. On the other hand, in the light section image corresponding to the background remaining portion, it was confirmed that the line width of the light section line was enlarged, as is clear when compared with the light section image corresponding to the normal portion.

  The light intensity image, the depth image, and the line width image calculated by the arithmetic processing device 200 using the light section images obtained from the respective area cameras are collectively shown in FIG. In FIG. 18, “area camera 1” is an area camera provided on the downstream side in the rotation direction of the disk-shaped processed product, and “area camera 2” is provided on the upstream side in the rotation direction of the disk-shaped processed product. Area camera.

  As is clear from the attention to the two types of luminance images shown in FIG. 18, in the luminance image, a white-looking portion, which is a defect candidate portion, is affected by reflected light from surrounding noise caused by dust or minute unevenness. It turns out that there are many. It can be seen that it is difficult to reveal the background residual portion which is the focus of the present invention only by referring to such a luminance image.

  Similarly, when attention is paid to the two types of depth images shown in FIG. 18, in the depth image, there are a large number of gray portions that are defect candidate portions, and the present invention can be performed only by referring to such depth images. It can be seen that it is difficult to make the remaining surface of the surface of interest noticeable.

  On the other hand, in the two types of line width images shown in FIG. 18, although there is an influence of peripheral noise, the image state is clearly different between the background residual portion and other portions, and the background residual portion is made visible. It became clear that it is possible. As is clear from this figure, it was confirmed that by using the line width image, the distinguishability between the background residual part and the ambient noise is high.

  Further, as a result of comparing two types of line width images calculated from two area cameras, the line width image based on the light section image from the area camera 1 is the line width image based on the light section image from the area camera 2. It turns out that it is clearer than. These results suggest that the surface-remaining portion of the disc-shaped processed product used as the inspection object 1 has surface orientation. Even in such a case, by capturing the linear laser beam L from a plurality of directions, it is possible to more surely reveal the background residual portion and to underestimate the background residual portion and rust. It was confirmed that the possibility of being lost can be avoided.

  The preferred embodiments of the present invention have been described above in detail with reference to the accompanying drawings, but the present invention is not limited to these examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention pertains can come up with various changes or modifications within the scope of the technical idea described in the claims. Of course, it is understood that these also belong to the technical scope of the present invention.

10 surface texture inspection device 100 inspected object imaging device 101 illumination device 103, 105 area camera 200 arithmetic processing device 201 imaging control unit 203 image processing unit 205 display control unit 207 storage unit 211 data acquisition unit 213 striped image frame generation unit 215 image Calculation unit 217 Light section line processing unit 219 Depth image calculation unit 221 Luminance image calculation unit 223 Line width image calculation unit 225 Detection processing unit

Claims (9)

A surface texture inspection device that uses a machined product made of an intermediate material as an inspection object,
By irradiating the surface of the moving object to be inspected with a linear laser beam and by imaging the surface irradiated with the linear laser beam, it is a captured image of the linear laser beam on the surface. An object-to-be-inspected imaging device that generates a plurality of light-section images along the moving direction of the object to be inspected;
An arithmetic processing device that performs image processing on the light-section image generated by the inspection object imaging device to determine the surface texture of the surface of the inspection object,
Equipped with
The inspected device imaging device,
An illumination device that irradiates the surface of the inspected object with the linear laser beam,
An imaging device for imaging the surface irradiated with the linear laser light,
Have
The arithmetic processing unit,
Based on a striped image frame in which light cutting lines, which are line segments corresponding to the irradiation portion of the linear laser light in each of the plurality of light cutting images, are arranged in order along the moving direction, Depth image showing the unevenness of the surface, a luminance image showing the luminance distribution of the linear laser light on the surface of the inspection object, and the moving direction of the linear laser light on the surface of the inspection object An image calculation unit that calculates a line width image in which the distribution of the line width of is associated with a luminance value,
Based on the calculated depth image, the brightness image and the line width image, a detection processing unit for detecting the surface texture of the inspection object,
Have
The surface texture inspection device, wherein the detection processing unit detects, based on the line width image, whether or not a background residual portion or rust made of the intermediate material is present on the surface of the inspection object.   The detection processing unit detects the background residual portion and the rust based on whether or not the luminance value of the line width image is equal to or higher than a first threshold value for detecting the background residual portion and rust, 1. The surface texture inspection device according to 1.   The image calculation unit calculates, for each light cutting line in the striped image frame, a difference between the line width and a predetermined threshold line width at each position in the extending direction of the light cutting line, and is calculated. The surface texture inspection apparatus according to claim 1, wherein the line width image is calculated by assigning a brightness value according to the magnitude of the difference.   The image calculation unit calculates the barycentric position in the line width direction of the light cutting line along the moving direction of the inspection object, and a reference position that is a position in the moving direction designated in advance with respect to the light cutting image. The surface texture inspection device according to claim 1, wherein the depth image is calculated based on the amount of displacement from the position of the center of gravity. The detection processing unit,
The depth value and the brightness value of the brightness image specify a defective portion based on whether or not a second threshold value for specifying the defective portion,
For the identified defective portion, the feature amount information regarding the form and the brightness value of the defective portion is extracted,
The surface texture inspection apparatus according to claim 1, wherein a defect existing on the surface of the inspection object is determined based on the extracted feature amount information.   In the depth image and the luminance image, the detection processing unit performs detection of the defective portion other than the portion where the background residual portion or the rust is detected based on the line width image, The surface texture inspection device described.   The imaging device for an object to be inspected has at least two imaging devices for imaging the surface irradiated with the linear laser beam from an upstream side in the moving direction and a downstream side in the moving direction, respectively. Item 7. The surface texture inspection device according to any one of items 1 to 6. A method for inspecting a surface property of a machined product made of an intermediate material as an inspected object,
By irradiating the surface of the moving object to be inspected with linear laser light from an illuminating device, and by imaging the surface irradiated with the linear laser light with an imaging device, the linear laser on the surface is obtained. A light-section image generating step of generating a plurality of light-section images that are captured images of light along the moving direction of the object to be inspected;
Based on a striped image frame in which the optical processing line is arranged in order along the moving direction, which is a line segment corresponding to the irradiation portion of the linear laser light in each of the plurality of light cutting images, by the processing device. A depth image showing the concavo-convex state of the surface of the inspection object, a luminance image showing the luminance distribution of the linear laser light on the surface of the inspection object, and the linear laser on the surface of the inspection object An image calculation step of calculating a line width image in which the distribution of the line width in the moving direction of light is associated with a luminance value,
A detection processing step of detecting a surface texture of the inspected object based on the calculated depth image, the brightness image, and the line width image by an arithmetic processing device,
Including,
In the detection processing step, based on the line width image, it is detected whether or not a background residual portion or rust made of the intermediate material is present on the surface of the inspection object, a surface texture inspection method. . By using a machined product made of an intermediate material as the inspection object, irradiating the surface of the moving inspection object with a linear laser beam, and imaging the surface irradiated with the linear laser beam. A computer capable of mutually communicating with a device under test imaging device that generates a plurality of light-section images that are captured images of the linear laser light on the surface along the moving direction of the device under test,
Based on a striped image frame in which light cutting lines, which are line segments corresponding to the irradiation portion of the linear laser light in each of the plurality of generated light cutting images, are sequentially arranged along the moving direction, Depth image showing the concavo-convex state of the surface of the inspection object, a luminance image showing the luminance distribution of the linear laser light on the surface of the inspection object, and the linear laser light on the surface of the inspection object An image calculation function for calculating a line width image in which the distribution of the line width in the moving direction is associated with a luminance value,
A detection processing function of detecting the surface texture of the inspected object based on the calculated depth image, the luminance image, and the line width image,
And realize
The detection processing function is a program for detecting, based on the line width image, whether or not a background residual portion or rust made of the intermediate material is present on the surface of the inspection object.