JP2018048979A - Surface property inspection apparatus, surface property insection method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To inspect surface properties of a machined workpiece, while exposing a texture residual part and rust in the machined workpiece obtained by machining a material after hot-molding a billet or the like as an intermediate material.SOLUTION: A surface property inspection apparatus according to the present invention includes: a test object imaging device that applies linear laser light to a surface of a moving test object, with a machined workpiece defined as the test object, and captures an image of a surface to which the linear laser light is applied to generate a light sectioning image; and an arithmetic processing unit for performing image processing of the generated light sectioning image. The arithmetic processing unit includes: an image calculation section for calculating a depth image, a luminance image, and a linewidth image on the basis of a stripped image frame obtained from the light sectioning image; and a detection processing section for detecting surface properties of the test object on the basis of the calculated depth image, luminance image, and linewidth image. The detection processing section detects whether or not a texture residual part or rust is present on the surface of the test object on the basis of the linewidth image.SELECTED DRAWING: Figure 1

Description

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

  Does the machined steel manufactured by performing various types of machining after intermediate forming such as slabs and billets have appropriate surface properties at the time of shipment? An inspection (surface inspection) of whether or not is performed. Such surface inspection of machined steel is often performed as inspection by hammering sound or inspection by visual inspection, but in the case of these inspection methods, a large part depends on the skill of the inspector. In particular, visual inspection includes a plurality of inspection items such as magnetic particle inspection and appearance inspection, which complicates operations. In such a machined steel material, fine scratches associated with machining are generated on the surface, or the surface of the material after hot forming a billet that is an intermediate material of the base material remains on the surface of the machined steel material. Various surface property changes can occur, such as. Inspection of surface properties so that machined steel materials that have microscopic flaws on the surface and residual material surface (background) after hot forming of billets that are intermediate materials do not flow out as shameless flaws Requires accuracy.

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

  However, harmful scratches such as rust and other residual scratches on the surface of the material after hot forming a billet, which is an intermediate material, that can exist on the surface of machined steel, and unevenness are extremely low at 100 μm or less. Since it is small, it cannot be detected by the light cutting method proposed in Patent Document 1 below.

  Therefore, as a method for detecting minute unevenness, in Patent Document 2 below, the surface of a machined product is irradiated with slit laser light (linear light), and the irradiation light is focused on the concave portion and irradiated on the convex portion. A technique that pays attention to the change in the width of irradiation light caused by scattering of light has been proposed. This technique is a technique that utilizes the characteristic 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 is a recess.

Japanese Patent Laid-Open No. 2003-240521 JP 2002-346925 A

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

  As described above, when inspecting the surface properties of a machined product, the billet, 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. It is in the present situation that it is impossible to clearly reveal the portion where the background of the material after remaining, rust, etc. are clearly manifested. Although it is possible to image the surface of the machined product based on the luminance information of the illumination reflected light, it is affected by surrounding noise components (for example, machined skin and dust), and the defective part It is very difficult to distinguish between the normal part and the normal part.

  Therefore, the present invention has been made in view of the above-mentioned problems, and the object of the present invention is to provide a machined product obtained by machining an intermediate material with respect to the background remaining portion and rust of the intermediate material. An object of the present invention is to provide a surface property inspection apparatus, a surface property inspection method, and a program capable of inspecting the surface shape of a machined product while becoming apparent.

  In order to solve the above-described problems, according to one aspect of the present invention, there is provided a surface property inspection apparatus that uses a machined product made of an intermediate material as a material to be inspected. The laser beam is irradiated, and the surface to which the linear laser beam is irradiated is imaged, so that a light cut image, which is an image captured by the linear laser beam, is moved on the surface. A plurality of inspected object imaging devices that are generated along a direction, and an arithmetic process that performs image processing on the light cut image generated by the inspected object imaging device and determines a surface property of the surface of the inspected object An imaging device that irradiates the surface of the object to be inspected with the linear laser beam, and images the surface irradiated with the linear laser beam. An image processing device, and the arithmetic processing device The inspected object is based on a striped image frame in which light cutting lines, which are line segments corresponding to the irradiated portions of the linear laser light in each of the plurality of light cutting images, are arranged in order along the moving direction. A depth image representing an uneven state of the surface of the object, a luminance image representing a 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 inspected object based on the calculated depth image, the luminance image, and the line width image A detection processing unit that detects the surface properties of the surface, and the detection processing unit has, based on the line width image, a background remaining portion or rust made of the intermediate material as a material on the surface of the inspection object. Surface texture inspection to detect whether it exists Location is provided.

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

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

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

  The detection processing unit identifies a defective part based on whether or not the luminance values of the depth image and the luminance image are equal to or greater than a second threshold value for specifying a defective part, and the identified defective part It is preferable that feature amount information relating to the form and luminance value of the defect part is extracted, and a defect present on the surface of the object to be inspected is determined 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 inspection object imaging device includes at least two imaging devices that image the surface irradiated with the linear laser light from each of an upstream side in the moving direction and a downstream side in the moving direction. preferable.

  In order to solve the above-mentioned problem, according to another aspect of the present invention, there is provided a surface property inspection method using a machined product made of an intermediate material as a material to be inspected. Light that is a captured image of the linear laser light on the surface by irradiating the surface with linear laser light from an illuminating device and imaging the surface irradiated with the linear laser light with an imaging device A light section image generation step for generating a plurality of cut images along the moving direction of the object to be inspected, and a line segment corresponding to the irradiated portion of the linear laser light in each of the plurality of light section images by an arithmetic processing unit. A depth image representing a concavo-convex state of the surface of the object to be inspected, and the linear shape on the surface of the object to be inspected based on a striped image frame in which the light cutting lines are sequentially arranged along the moving direction. Luminance of laser light An image calculation step for calculating a luminance image representing the image and a 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 inspection object is associated with a luminance value; A detection processing step of detecting a surface property of the object to be inspected based on the depth image, the luminance image, and the line width image calculated by an apparatus, and in the detection processing step, the line width image In accordance with the present invention, there is provided a surface property inspection method in which it is detected whether a background remaining portion or rust made of the intermediate material is present on the surface of the object to be inspected.

  In order to solve the above-described problem, according to still another aspect of the present invention, a machined product made of an intermediate material is used as a test object, and a linear laser beam is formed on the surface of the moving test object. And imaging the surface irradiated with the linear laser light, a light cut image that is an image of the linear laser light on the surface along the moving direction of the object to be inspected A computer capable of mutual communication with a plurality of generated imaging devices to be inspected, and a light cutting line that is a line segment corresponding to a portion irradiated with the linear laser light in each of the plurality of generated light cutting images Based on the striped image frames arranged in order along the moving direction, the depth image representing the uneven state of the surface of the object to be inspected and the luminance distribution of the linear laser light on the surface of the object to be inspected Luminance image and the object to be inspected An image calculation function for calculating a line width image in which the distribution of the line width in the moving direction of the linear laser beam on the surface is associated with a luminance value, the calculated depth image, the luminance image, and the A detection processing function for detecting a surface property of the object to be inspected based on a line width image, and the detection processing function is based on the line width image, or the background remaining portion using the intermediate material as a material or A program for detecting whether rust is present on the surface of the object to be inspected is provided.

  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 billet or the like as an intermediate material is hot formed. The surface shape of the machined product can be inspected while the remaining surface of the surface of the material and the rust remaining on the surface and the rust appear.

It is the block diagram which showed typically the structure of the surface property inspection apparatus which concerns on embodiment of this invention. It is explanatory drawing which showed typically an example of the structure of the to-be-inspected object imaging device which concerns on the embodiment. It is explanatory drawing which showed typically an example of the structure of the to-be-inspected object imaging device which concerns on the embodiment. It is explanatory drawing for demonstrating the mode of reflection on the normal to-be-inspected 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 cutting image at the time of imaging the normal to-be-inspected object surface. It is explanatory drawing which showed typically the light cutting 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 cutting image at the time of imaging the to-be-inspected object surface containing a rough surface part. It is the block diagram which showed an example of the structure of the image process part with which the arithmetic processing apparatus which concerns on the same embodiment is provided. It is explanatory drawing which showed an example of the fringe image frame which concerns on the same embodiment. It is explanatory drawing for demonstrating the optical cutting process which concerns on the same embodiment. It is explanatory drawing for demonstrating the optical cutting process which concerns on the same embodiment. It is explanatory drawing which showed the two-dimensional arrangement | sequence of the optical cutting line displacement which concerns on the same embodiment. It is explanatory drawing which showed the two-dimensional arrangement | sequence of the sum total of the luminance which concerns on the same embodiment. It is explanatory drawing which showed the two-dimensional arrangement | sequence of the number of pixels of the bright line based on the embodiment. It is explanatory drawing which showed the relationship between the displacement of an optical cutting line, and the height of a defect. It is explanatory drawing for demonstrating the approximate correction process of the optical section line which concerns on the same embodiment. It is explanatory drawing for demonstrating the line | wire width of the optical cutting line in a normal part and a rough surface part. It is explanatory drawing for demonstrating the line | wire width of the optical cutting line in a normal part. It is explanatory drawing for demonstrating the line | wire width of the optical cutting line in a rough surface part. It is explanatory drawing for demonstrating the line | wire width image which concerns on the embodiment. It is explanatory drawing which showed typically an example of the logic table used by the surface property detection process which concerns on the same embodiment. It is the flowchart which showed an example of the flow of the surface property inspection method which concerns on the embodiment. It is the block diagram which showed an example of the hardware constitutions of the arithmetic processing unit which concerns on the same embodiment. It is explanatory drawing for demonstrating an Example. It is explanatory drawing for demonstrating an Example.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

(Embodiment)
<About the overall configuration of the surface texture inspection device>
First, the overall configuration of a surface texture inspection apparatus 10 according to an 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 apparatus 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 that is an intermediate material (hereinafter simply referred to as a “machined product using an intermediate material”). The inspection object 1 is a device for inspecting the surface properties of the inspection object 1 moving in a predetermined direction.

  Here, the intermediate material is a material before becoming a final product, such as a slab or billet. After such an intermediate material is hot-formed, machining such as polishing and cutting is performed, whereby a machined product focused on in this embodiment is manufactured. As such a machined product, for example, a disk-shaped manufactured by adjusting the shape of the material after hot forming a billet, which is a kind of intermediate material mainly composed of iron (Fe), by mechanical cutting Examples thereof include a processed product and a cylindrical processed product manufactured by adjusting the outer diameter of a material after hot forming a billet or the like by mechanical cutting or the like. Further, the intermediate material is not limited to a material mainly composed of iron, and may be a material mainly composed of a non-ferrous metal.

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

  The inspection object imaging device 100 is installed above the moving inspection object 1 as described in detail below. The inspection object imaging apparatus 100 is an apparatus that sequentially images the surface of the inspection 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. Imaging processing by the inspected object imaging device 100 is controlled by the arithmetic processing device 200. In general, for example, a PLG (Pulse Logic Generator: pulse type speed detector) or the like is provided in a conveyance line that conveys a machined product that is the object to be inspected 1 in order to detect the moving speed of the object 1 to be inspected. Yes. Therefore, the arithmetic processing device 200 periodically transmits a control signal to the inspecting object imaging device 100 based on one pulse of the PLG signal input from the PLG, and the inspecting object imaging device 100 is transmitted based on the control signal. Can function. Thus, the inspected object imaging apparatus 100 can image the surface of the inspected object 1 every time the inspected object 1 moves by a predetermined distance or a predetermined time.

  As described above, the arithmetic processing apparatus 200 controls the entire imaging process of the surface of the inspection object 1 in the inspection object imaging apparatus 100. In addition, the arithmetic processing device 200 generates a fringe image frame using the captured image generated by the inspected object imaging device 100, and performs image processing on the fringe image frame, so that the inspected object 1 is inspected. Various defects that may be present on the surface (for example, scratches with irregularities, pattern-type scratches, surface residual portions where the surface of the material after hot forming of the intermediate material remains (hereinafter, It is simply referred to as “background remaining portion using intermediate material”), and rust etc. are detected.

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

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

  2A is a schematic diagram when the inspection object imaging apparatus 100 is viewed from above the inspection object 1. The illustration shown in the lower part of FIG. 2A is the inspection object imaging apparatus 100. FIG. 2 is a schematic view when the device is viewed from the side of the device under test 1. Similarly, the diagram shown in the upper part of FIG. 2B is a schematic diagram when the object imaging device 100 is viewed from above the object 1 to be inspected, and the figure shown in the lower part of FIG. 1 is a schematic diagram when an imaging apparatus 100 is viewed from the side of an object to be inspected 1. FIG.

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

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

  The illumination 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 includes at least a laser light source that irradiates the surface of the inspection object 1 with a linear laser beam L.

  The illuminating device 101, for example, condenses light source units that emit laser light of a predetermined wavelength, such as a visible light band, and the line width direction while expanding the laser light emitted from the light source unit 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 along the y-axis direction of the linear laser light L at the laser irradiation position (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 device under test 1 can be, for example, about several hundred μm (for example, about 200 μm).

  In the portion irradiated with the linear laser beam L on the surface of the object 1 to be inspected, a linear bright portion is formed along the x-axis direction. A line segment corresponding to this linear bright part is called a light cutting line.

  An area camera 103, which is an example of an imaging apparatus, is an apparatus that captures an image of the entire surface of the inspection object 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 imaging device. The area camera 103 may be a monochrome camera or a color camera.

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

  The area camera 103 images the linear laser light L applied to the surface of the object 1 to be inspected, so that an optical cutting line that is a line segment corresponding to the irradiated portion of the linear laser light L is imaged. In addition, a so-called light cut image is generated. When the area camera 103 generates the light cut image, the area camera 103 outputs the generated light cut image to the arithmetic processing device 200.

  Here, the optical positional relationship between the illumination device 101 and the area camera 103 can be set as appropriate. For example, as illustrated in FIG. The linear laser beam L is provided above and irradiates the inspection target 1 with a linear laser beam L perpendicularly, and the area camera 103 is linear laser beam from the direction of the angle φ with respect to the vertical direction (z-axis direction). It can arrange | position so that the reflected light of L may be imaged.

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

  2A illustrates a case where the inspection object imaging apparatus 100 includes only one area camera which is an example of the imaging apparatus, but as illustrated in FIG. 2B, the inspection object imaging is performed. The apparatus 100 includes at least two area cameras 103 and 105 so that the surface of the inspection object 1 irradiated with the linear laser beam L can be imaged from each of the upstream side in the movement direction and the downstream side in the movement 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 equally arranged at an angle φ on the upstream side and the downstream side in the moving direction of the device under test 1.

  As will be described below with a specific example, there are cases where the background remaining portion, uneven scratches, and the like have directionality in the inclination of the surface along the moving direction. As shown in FIG. 2B, each area camera is provided on the upstream side and the downstream side in the moving direction, and by using the light cut image output from each area camera, the direction of the tilt is not affected. It becomes possible to inspect the surface property of the inspection object 1 more accurately.

  Hereinafter, specific configurations, setting values, and the like of each device included in the inspected object imaging device 100 according to the present embodiment are listed. Such a configuration, setting values, and the like are merely examples, and the inspected subject imaging apparatus 100 according to the present invention is not limited to the following specific examples.

○ Inspected object (machined product)
Width (length in the x-axis direction): about 600 mm to 1750 mm ○ Lighting device 101
Irradiates red laser light from a laser light source with an output of 100 mW. The line width of the linear laser beam L irradiated on the surface of the inspection object 1 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 field angle is 26 °. The pixel size of the image to be captured is 0.25 mm × 0.25 mm, and the line width of the linear laser beam L is captured with the width of the bright line of 2 to 4 pixels on the captured image. When the width of the object to be inspected is large, for example, it is possible to arrange a plurality of area cameras in the width direction as necessary for securing pixel resolution.
Image acquisition method When the object to be inspected 1 is moving, images are continuously acquired in synchronization with a signal output from the PLG. Specifically, imaging is performed every time the inspected object 1 moves forward in a time of 5 msec. At this time, two area cameras installed as shown in FIG. 2B are synchronized, and the same visual field is simultaneously imaged. The illumination device 101 is provided above the vertical direction, irradiates the linear laser beam L downward in the vertical direction, and the installation angle φ of the two area cameras is ± 45 degrees. Note that the imaging resolution is determined according to the size of the target scratch or the like, but the capture pitch is set to 0.25 mm to match the pixel size of the image sensor.

  Next, an optical section image captured by the inspection subject imaging apparatus 100 will be described in detail with reference to FIGS. 3A to 4C.

  Since the machined product focused on as the object to be inspected 1 in the present embodiment is subjected to machining such as polishing or grinding, the surface thereof has a substantially constant surface property and has regular reflectivity. strong. Therefore, the surface of a normal part (hereinafter, also simply referred to as “normal part”) that does not have scratches with unevenness, a background remaining part, rust, or the like has only extremely small unevenness of 10 μm or less. As a result, as shown schematically in FIG. 3A, the linear laser light L irradiated to the normal part shows substantially the same reflection characteristics 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 takes a substantially constant value as schematically shown in FIG. 4A. In addition, when there is a concave or convex portion on the surface of the machined product, as shown schematically in FIG. 4B, the light cutting image at the concave portion, the light cutting image shows a line of a substantially constant light cutting line. The optical cutting line is bent while maintaining the width.

  On the other hand, the background remaining portion and the surface of rust to which attention is paid in this embodiment have irregularities of about 100 μm, and are rougher than the normal portion. The background remaining portion and rust (hereinafter collectively referred to as “rough surface portion”) function as a diffusion surface because of the roughness of the surface, as schematically shown in FIG. 3B. Therefore, the linear laser beam L irradiated to the rough surface portion 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 irregular reflection as described above. Is expanded.

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

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

<About Overall Configuration of Arithmetic Processing Device 200>
Next, returning to FIG. 1 again, the overall configuration of the arithmetic processing apparatus 200 according to the present embodiment will be described.
For example, as illustrated in FIG. 1, the arithmetic processing device 200 according to the present embodiment mainly includes 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 performs imaging control of the inspection object 1 by the inspection object imaging apparatus 100 according to the present embodiment. More specifically, the imaging control unit 201 sends a control signal for starting oscillation of laser light to the illumination device 101 when imaging of the inspection object 1 is started.

  In addition, as previously mentioned, a PLG signal is periodically sent from the conveyance line of the inspection object 1 (for example, one pulse of the PLG signal 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 every time a 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 imaging data of the light section image acquired from the inspected object imaging device 100 (more specifically, the area cameras 103 and 105 of the inspected object imaging device 100) to form a fringe image frame to be described later. Is generated. Thereafter, the generated striped image frame is subjected to image processing as will be described below to inspect the surface properties of the machined product that is the inspected object 1, and various defects that may exist on the surface are detected. 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 in detail later again.

  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 property inspection result of the machined product that is the inspection object 1 transmitted from the image processing unit 203 to an output device such as a display provided in the arithmetic processing device 200 or the outside of the arithmetic processing device 200. Display control when displaying on the provided output device or the like is performed. Thereby, the user of the surface texture inspection apparatus 10 can grasp the inspection result regarding the surface texture of the machined product that is the inspection object 1 on the spot.

  The storage unit 207 is realized by, for example, a RAM or a storage device included in the arithmetic processing device 200 according to the present embodiment. The storage unit 207 stores various parameters, intermediate progress of processing, and various databases and programs that need to be saved when the arithmetic processing apparatus 200 according to the present embodiment performs some processing, as appropriate. To be recorded. The storage unit 207 allows the imaging control unit 201, the image processing unit 203, the display control unit 205, and the like to execute read / write processing.

<Regarding Image Processing Unit 203>
Next, the image processing unit 203 included in the arithmetic processing apparatus 200 according to the present embodiment will be described in detail with reference to FIG. FIG. 5 is a block diagram illustrating an example of a configuration of an image processing unit included in the arithmetic processing apparatus 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 striped 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 the image data (digital multi-valued image data) of the light section image output from the inspection subject imaging apparatus 100 (more specifically, the area cameras 103 and 105), and the storage unit 207 and the like. Are sequentially stored in the image memory provided. By using these digital multi-valued image data sequentially along the moving direction of the object 1 to be inspected, a fringe image frame as described later is generated.

  As described above, the light section image acquired by the data acquisition unit 211 is a linear laser beam irradiated on the surface of the inspection object 1 at a certain position along the moving direction of the surface of the inspection object 1. L is taken. The light-cut image is displayed by setting the area camera gain and the lens aperture appropriately in advance, for example, the portion irradiated with the linear laser light L is displayed in white, and the other portions are displayed in black and white. It can be an image. In addition, the irregularities superimposed on the light cutting line existing in the light cutting image and the line width of the light cutting line itself are various defects including the cross-sectional shape of the surface of the inspection object 1 and the rough surface portion existing on the surface. Contains information about etc.

  The fringe image frame generation unit 213 is realized by a CPU, a ROM, a RAM, and the like, for example. The fringe image frame generation unit 213 sequentially acquires the light section images stored along the moving direction of the device under test 1 from the image memory provided in the storage unit 207 or the like. Thereafter, the fringe image frame generation unit 213 uses an area including the optical cutting line among the obtained optical cutting images, and sequentially displays the image of the area including the optical cutting line along the moving direction of the inspection object 1. By arranging, a fringe image frame is generated.

  The number of light section images constituting one striped image frame may be set as appropriate. For example, one striped image frame may be composed of 256 light section images. Each light section image exists at every imaging interval (for example, 0.25 mm interval) of the light section image as described above. Therefore, one striped image frame composed of 256 light cut images based on the light cut images taken at intervals of 0.25 mm is 64 mm (= 256 × 0) along the moving direction on the surface of the inspection object 1. .25 mm) corresponding to the result of imaging.

  FIG. 6 shows an example of the stripe image frame generated by the stripe image frame generation unit 213. The striped image frame shown in FIG. 6 shows 16 light cut images out of 256 light cut 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 cut image, and the horizontal direction of the drawing corresponds to the x-axis direction in FIG. 2A and the like. 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 illustrated in FIG. 6, the stripe image frame generation unit 213 outputs the generated stripe image frame to the image calculation unit 215 described later. Further, the fringe image frame generation unit 213 may associate the time information related to the date and time when the fringe image frame is generated with the data corresponding to the generated fringe image frame and store the data in the storage unit 207 or the like as history information. .

  The image calculation unit 215 is realized by, for example, a CPU, a ROM, a RAM, and the like. Based on the fringe image frame generated by the fringe image frame generation unit 213, the image calculation unit 215 has a depth image representing an uneven state on the surface of the inspection object 1 and linear laser light on the surface of the inspection object 1. A luminance image representing the luminance distribution of L and a line width image in which the line width distribution in the moving direction of the linear laser beam L on the surface of the inspection object 1 is associated with the luminance 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, for each light section line included in the fringe image frame, a light section line feature amount including a displacement amount of the light section line (bending degree of the bright line). Hereinafter, the processing performed by the light section line processing unit 217 and the calculated light section line feature amount will be described in detail with reference to FIGS. 7A and 7B.
FIG. 7A is an explanatory diagram schematically showing a fringe image frame. FIG. 7B is an explanatory diagram for explaining the optical section line processing performed by the optical section 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 optical section image which includes a single optical cutting line, and a vertical y _n pixels × horizontal M pixels. Incidentally, if one vertical pixel number y size of _n in the light section image (in other words, including one optical cutting line, from one light section image, the number of vertical pixels to be cut out when fringe image frame is generated ₍ the size of yn) can be determined by roughly calculating in advance the range of the height of the concave portion or the convex portion that may exist in the inspection object 1 based on past operation data or the like. is there.

Here, for convenience of explanation, the X-axis is taken in the x-axis direction (lateral direction of the striped image frame in FIG. 7A) orthogonal to the moving direction of the inspection object 1, and the y-axis direction corresponding to the moving direction of the inspection object 1 The Y-axis is taken in the vertical direction of the striped image frame in FIG. 7A, and the pixel position in the striped image frame is expressed 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 fringe image frame (ie, represented by X _{j, m} ). The position).

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

Here, the reference position Y _s of the Y coordinate is a position in the y-axis direction that is designated in advance with respect to the j-th light section image of the striped 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 and the convex portion that may exist in the inspection object 1 is specified based on past operation data and the like, and the range of W before and after the reference position Y _s of the Y coordinate in the light section image is determined. What is necessary is just to determine suitably the magnitude | size of the parameter W previously calculated so that it may be settled in a light cutting image. If the value of the parameter W can be reduced, it is possible to reduce the processing load of the optical section line processing unit 217 described later.

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 illustrated in FIG. 7B, three pixels represented by Y _{j, k} , Y _{j, k + 1} , Y _{j, k + 2} have luminance values I _{j, k} , I _{j, k + 1} , I _j that are equal to or higher than the threshold Th, respectively. _{, K + 2} . Accordingly, the light section line processing unit 217 sets the number p _{j, m} = 3 obtained by adding pixels having luminance values equal to or greater than the predetermined threshold Th in the line width direction. The number p _{j, m} obtained by adding pixels having luminance values equal to or greater than the predetermined threshold Th in the line width direction is a value corresponding to the number of pixels of the bright line at the position (j, m). one of. Further, the light section 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)), further light section line feature quantities are calculated.

In addition, the light section line processing unit 217 calculates the total sum K _{j, m} of the luminances of the extracted pixels using the parameters p _{j, m} and the information (Y, I) regarding the extracted pixels. In the case of the example illustrated in FIG. 7B, the sum of the luminances calculated by the light section line processing unit 217 is K _{j, m} = I _{j, k} + I _{j, k + 1} + I _{j, k + 2} . This total luminance K _{j, m} is also one of the features of the light section line.

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, and the barycentric position Y _C (j, m) and a displacement amount Δd _{j, m} = Y _s −Y _C (j, m) of the center of gravity Y _C (j, m) from the reference position Y _s are calculated.

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

Here, the position in the Y-axis direction corresponding to the pixel is a value quantized with a take-in pitch (for example, 0.25 mm) in the inspected object imaging apparatus 100. 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. It can be smaller than the take-in pitch (so-called quantization unit). Therefore, the displacement amount Δd _{j, m} calculated using the center-of-gravity position Y _C (j, m) is also a value that can have a value smaller than the movement width. The displacement amount Δd _{j, m} calculated in this way is also one of the light section line feature amounts.

  The light section line processing unit 217 calculates the above three types of feature amounts with respect to 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 Δd of the light section line, the total luminance K, and the number of pixels p of the bright lines.

  The light section line processing unit 217 outputs a feature amount related 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, to the brightness image calculation unit 221, which will be described later, among the calculated light section line feature amounts, the brightness sum K and the feature amount related to the number of bright line pixels p. Further, the light section line processing unit 217 outputs the feature amount related to the number of pixels 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, a ROM, a RAM, and the like. The depth image calculation unit 219 is a depth image that represents the uneven state of the surface of the object 1 to be inspected based on the optical cutting line feature value (particularly, the feature value related to the displacement amount Δd) generated by the optical cutting line processing unit 217. Is calculated.

  Specifically, the depth image calculation unit 219 performs an angle (a two-dimensional arrangement) regarding the amount of displacement Δd as shown in FIG. 8A and the angle formed by the linear laser beam L and the optical axis of the area camera ( The depth image is calculated using the angle φ) in FIGS. 2A and 2B. This depth image is an image representing a two-dimensional uneven state distribution in which the one-dimensional distribution of the uneven state 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 present on the surface of the inspection object 1 and the displacement Δd of the light cutting line will be described with reference to FIG. FIG. 9 is an explanatory diagram showing the relationship between the displacement of the optical cutting line and the height of the defect.

  In FIG. 9, the case where the recessed part exists in the surface of the to-be-inspected object 1 is shown typically. Here, the difference between the height of the surface position and the height of the bottom of the recess when the recess is not present on the surface of the inspection object 1 is represented by Δh. When attention is paid to the case where the linearly incident linear laser beam L is surface-reflected, when there is no concave portion on the surface of the object 1 to be inspected, the reflected light propagates like the light ray A in FIG. When there is a recess on the surface of the inspection object 1, the reflected light propagates like a light beam B in FIG. The deviation between the light beam A and the light beam B is observed as the displacement Δd of the light cutting line in this embodiment. Here, as is apparent from the geometrical positional relationship, the relationship Δd = Δh · sinφ is established between the displacement Δd of the light cutting line and the depth Δh of the recess.

  In addition, although FIG. 9 demonstrated the case where a recessed part exists in the surface of the to-be-inspected object 1, even if it is a case where a convex part exists in the surface of the to-be-inspected object 1, the same relationship is materialized.

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

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

  Note that, as shown in FIG. 10, due to a change in the shape of the surface of the device under test 1, distortion such as bending may occur in the optical cutting line. On the other hand, in the surface property inspection method according to the present embodiment, the unevenness superimposed on the optical cutting line is information on the cross-sectional shape of the surface of the object 1 and surface defects existing on the surface. Therefore, when the depth image calculation unit 219 calculates the depth image based on the displacement amount Δd of the light cutting line, the depth image calculation unit 219 performs distortion correction processing for each light cutting line, and the unevenness superimposed on the light cutting line. Only the information regarding may be extracted. By performing such a distortion correction process, it is possible to obtain only information on the uneven ridges present on the surface of the inspected object 1 even when the optical cutting line has a distortion such as curvature. .

  As specific examples of such distortion correction processing, (i) a fitting process using a multidimensional function or various nonlinear functions, and a difference calculation between the obtained fitting curve and the observed light cutting line, ii) A process of applying a low-pass filter such as a floating filter or a median filter by using the fact that the information on the unevenness is a high-frequency component can be mentioned. By carrying out such a distortion correction process, it is possible to flatten the light section line while maintaining the information on the uneven ridges present on the surface of the device under test 1.

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

  The luminance image calculation unit 221 is realized by, for example, a CPU, a ROM, a RAM, and the like. The luminance image calculation unit 221 generates a line on the surface of the object 1 to be inspected based on the light cutting line feature amount generated by the light cutting line processing unit 217 (particularly, the feature amount related to the luminance sum K and the number of pixels p of the bright line). A luminance image representing the luminance distribution of the laser beam L is calculated.

Specifically, the luminance image calculation unit 221 performs a feature amount (two-dimensional array) related to the luminance sum K as shown in FIG. 8B and a feature amount related to the number of pixels p of bright lines as shown in FIG. 8C ( The average luminance K _AVE (j, m) = K _{j, m} / p _{j, m} (1 ≦ j ≦ N, 1 ≦ m ≦), which is the average value of the total luminance in the line width direction. M) is calculated. Thereafter, the luminance image calculation unit 221 sets the data array formed of the calculated average luminance K _AVE (j, m) as the luminance image of the object 1 to be inspected. Such a luminance image is an image representing a two-dimensional luminance distribution in which the one-dimensional luminance distribution of the linear laser beam L at each position in the Y-axis direction is sequentially arranged along the Y-axis direction.

  The luminance image calculation unit 221 outputs information on 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 is configured to generate a linear laser beam on the surface of the inspected 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 number of pixels p of the bright line). 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.

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

  As described earlier, in the rough surface portion and the rough surface portion such as rust focused on in the present embodiment, as a result of the rough surface portion functioning as a scattering surface, the linear laser light L irradiated to the rough surface portion is scattered by the rough surface portion. Is done. Therefore, as schematically shown in FIGS. 4C and 11, an increase in the line width of the light section line is recognized at the position of the light section image corresponding to the rough surface portion.

  If the optical cutting line as schematically shown in FIG. 11 is obtained, the position corresponding to the AA ′ cutting line corresponds to the normal part, and the position corresponding to the BB ′ cutting line is rough. It corresponds to the surface part. In this case, a pixel having a luminance value equal to or higher than a predetermined threshold Th for specifying a pixel corresponding to the light cutting line in the luminance distribution of the normal part along the AA ′ cutting line is schematically illustrated in FIG. 12A. Assume 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 higher than the threshold Th are 8 pixels as schematically illustrated in FIG. 12B.

  In the inspection object imaging device 100, for example, it is assumed that the line width of the linear laser light L is set to correspond to 2 to 4 pixels. Since the line width of the linear laser light L is recognized 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 are set values in the inspection object imaging apparatus 100. Exceeds value. 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 in advance a predetermined threshold Th2 for specifying a pixel corresponding to the rough surface portion. Become. For example, in the imaging device 100 to be inspected, it is assumed that the line width of the normal portion of the linear laser light L is set to 2 to 4 pixels. In this case, by setting the threshold Th2 as 5 pixels with a margin, a portion having a line width of 5 pixels or more can be distinguished as a rough surface portion.

  From the above viewpoint, the line width image calculation unit 223 corresponds to the rough surface portion by determining the threshold value of the feature amount related to the number of pixels p of the bright lines generated by the light cutting line processing unit 217 based on the threshold value Th2. It becomes possible to specify the pixel position.

Next, a specific calculation method of the line width image in the line width image calculation unit 223 will be described with reference to FIG.
By setting the threshold value Th2 as described above, the position of the rough surface portion can be specified, while the line width image generated by the line width image calculation unit 223 does not reveal the normal portion. It is important to determine the luminance value that constitutes. 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 and a predetermined threshold line at each position in the extending direction (Y-axis direction) of the light cutting line. A line width image is calculated by calculating a difference from the width and assigning a luminance value according to the calculated magnitude of the difference.

  More specifically, the line width image calculation unit 223 refers to the feature quantity related to the number of pixels p of the bright lines generated by the light section line processing unit 217, and determines the number of bright lines pixels p at each position and the threshold line width. The difference from the corresponding threshold value Th2 is calculated. Note that, if the difference from the threshold Th2 is calculated for the normal part, the difference may be a negative value. However, the difference value in this case is preferably set to zero instead of being a negative value. Thereafter, the line width image calculation unit 223 determines the luminance value at each pixel position so that the luminance value of the pixels constituting the line width image increases as the calculated difference value increases.

  For example, consider a case where the threshold Th2 is 5 pixels and a line width image is generated as an 8-bit image. In this case, when trying to use all the luminance value ranges (0 to 255) in the 8-bit image, the line width image calculation unit 223 determines the luminance value at each pixel position as follows, for example. That's fine. In addition, although the example shown below has shown about the case where 8 bit full scale is used, it is not necessary to use 8 bit full scale. However, the visibility of the generated line width image can be improved by setting the luminance value in the full scale range.

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

  Note that the method of assigning the luminance value according to the difference value is not limited to the above example, and any assignment method may be adopted as long as the luminance value increases as the difference value increases. It is possible. 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 is needless to say 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, for example, the light section 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 section line). Thus, a line width image as shown on the right side of FIG. 13 can be generated. In the example shown in FIG. 13, the line width image is black at the position where the luminance value = 0 (that is, the normal portion), and the luminance value becomes large (that is, the luminance value corresponds to the rough surface portion and The illustration is performed so that the surface becomes more white as the surface irregularities become larger). The line width image generated by such processing is a two-dimensional line width in which a one-dimensional distribution of the line width of the linear laser light L at each position in the Y-axis direction is sequentially arranged along the Y-axis direction. It is an image showing distribution.

  The line width image calculation unit 223 outputs 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. Based on the depth image, the luminance image, and the line width image respectively calculated by the depth image calculation unit 219, the luminance image calculation unit 221, and the line width image calculation unit 223, the detection processing unit 225 detects the surface of the inspection object 1 Detect properties.

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

○ Defect site identification function The detection processing unit 225 emphasizes the area of the rough surface portion by filtering processing that obtains a linear sum of luminance values with peripheral pixels as necessary for each pixel of the acquired line width image. Then, it is determined whether or not the obtained value is equal to or greater than the first threshold value for specifying the rough surface portion. By performing such a filtering process and a determination process based on the filtering process result, the detection processing unit 225 can generate a binarized image for specifying the portion 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 part (that is, pixel value of the binarized image = 0), and the calculated value is equal to or greater than the first threshold. A given 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 remaining surface portion or rust) by combining the portions of the rough surface portions that are continuously generated.

  Similarly, the detection processing unit 225 performs a filter process for obtaining a linear sum of pixel values (values representing depth or luminance values) with peripheral pixels for each pixel of the acquired depth image and luminance image. Regions such as vertical line wrinkles, horizontal line wrinkles, and fine wrinkles are emphasized, and it is determined whether or not the obtained value is equal to or greater than a second threshold value for specifying a defective part. By performing such a filtering process and a determination process based on the filtering process result, the detection processing unit 225 can generate a binarized image for specifying a defective part. In such a binarized image, a pixel whose calculated value is less than the second threshold corresponds to a normal location (that is, pixel value of the binarized image = 0), and the calculated value is equal to or greater than the second threshold. The pixel in question corresponds to a defective portion (that is, the pixel value of the binarized image = 1). Furthermore, the detection processing unit 225 identifies each defective portion by combining consecutively generated defect portions.

○ Feature Extraction Function When the detection processing unit 225 specifies a defective part (that is, a rough surface part) of the line width image by the defective part specifying function, a feature amount related to the form and luminance value of the defective part is determined for each specified defective part. Extract. Examples of the feature quantity related to the form of the defective part include the width of the defective part, the length of the defective part, the peripheral length of the defective part, the area of the defective part, and the area of the circumscribed rectangle of the defective part. In addition, examples of the feature amount related to the luminance value of the defective part include a maximum value, a minimum value, and an average value of the luminance of the defective part.

  In addition, when the defect processing unit 225 specifies the defective part of the depth image and the luminance image by the defective part specifying function, the detection processing unit 225 extracts a feature amount regarding the form and pixel value of the defective part for each specified defective part. Examples of the feature quantity related to the form of the defective part include the width of the defective part, the length of the defective part, the peripheral length of the defective part, the area of the defective part, and the area of the circumscribed rectangle of the defective part. In addition, as the feature amount related to the pixel value of the defective part, for the depth image, the maximum value, the minimum value, the average value, etc. of the depth of the defective part can be mentioned. Value, minimum value, average value, and the like.

Defect determination function When the detection processing unit 225 extracts the feature amount of each defective portion by the feature amount extraction function, the detection processing unit 225 determines the type of defect, the degree of harm, and the like for each defective portion based on the extracted feature amount. The determination processing such as the type of defect and the degree of harmfulness 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 vertical items in the logic table, and the types of features (feature amount B1) are displayed as horizontal items in the logic table. To feature quantity Bm). Also, in each cell of the table defined by the defect type and the feature amount, a discrimination conditional expression (conditional expression C11 to conditional expression Cnm) based on the size of the corresponding feature amount is described. Each row of such a logic table is a set, and becomes a determination condition for each type of defect. The determination process is performed in order from the type described in the top line, and ends when all the determination conditions described in any one line 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 specifying a defect type and a hazard level by an examiner based on the operation data are used as teacher data. It is possible to generate.

  The detection processing unit 225 specifies the defect type and the harmfulness for each defective part detected in this way, and outputs the obtained detection result to the display control unit 205. Thereby, the information regarding the defect which exists in the surface of the machined goods which are the to-be-inspected objects 1 will be output to a display part (not shown). In addition, the detection processing unit 225 may output the obtained detection result to an external device such as a manufacturing control process computer, or may create a product defect form using the obtained detection result. Good. Further, the detection processing unit 225 may store the information related to the detection result of the defective part as history information in the storage unit 207 or the like in association with time information related to the date and time when the information is calculated.

  In the above description, the case where the type of the defect and the harmfulness are determined using the logic table has been described. However, the method for determining the type of the defect and the harmfulness 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 learning processing using past operation data and a result of specifying a defect type and a hazard level by a tester based on the operation data as teacher data, Such a discriminator may be used for discriminating the type of defect and the degree of harm.

  As shown in the following examples, it is possible to find a portion that is a candidate for a rough surface portion by paying attention to a luminance image generated by a conventional light cutting method. However, since the rough surface portion is composed of minute irregularities, it is difficult to distinguish between the luminance image region and the rough surface portion caused by noise, dust, etc. It was impossible to determine which part of the region corresponding to the rough surface portion. On the other hand, as described above, the detection processing unit 225 according to the present embodiment performs defect detection processing based on a predetermined threshold determination using a line width image, so that it is difficult to distinguish by the conventional light cutting method. The portion of the rough surface portion (that is, the background remaining portion and rust) can be easily revealed.

  In addition, the detection processing unit 225 performs the above-described processing on a portion other than the portion where the rough surface portion (that is, the background remaining portion and rust) is detected based on the line width image during the defect detection processing based on the depth image and the luminance image. Such a defect site detection process may be performed. Thereby, it is possible to increase the speed of the defect detection process 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 a defect candidate portion in the luminance image. Therefore, the detection processing unit 225 confirms whether or not the rough surface portion specified based on the line width image is extracted as a defect candidate portion in the luminance image, and performs a double check of 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, when the depth image calculation unit 219 calculates the depth image, the case where the approximate correction process such as the difference calculation process or the low-pass filter process is performed has been described. However, the optical correction line processing unit 217 may execute the approximate correction process before the optical cutting line processing unit 217 calculates the optical cutting line feature amount.

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

  A computer program for realizing each function of the arithmetic processing apparatus according to the present embodiment as described above can be produced and installed in a personal computer or the like. In addition, a computer-readable recording medium storing such a computer program can be provided. 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 via a network, for example, without using a recording medium.

  The configuration of the surface property inspection apparatus 10 according to the present embodiment has been described in detail above. By using the surface texture inspection apparatus 10 according to the present embodiment, it is possible to detect the residual surface portion and rust remaining on the machined surface with the same apparatus configuration as the apparatus based on the conventional light cutting method. . In addition, since detection based on a conventional light cutting method such as an uneven surface or a surface pattern is also possible, a wide variety of defective parts can be inspected over the entire machined surface of a machined product.

  Furthermore, 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 of the defective portion is different from that of the normal portion. If it is such a product, the surface texture inspection apparatus 10 according to the present embodiment can be applied. In particular, the two-dimensional image of the distribution of the remaining surface and the rust portion having low visibility makes it easy to identify a defective part by image processing, and uses an image with good visibility even in visual inspection. It becomes possible.

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

  First, the inspected object imaging device 100 of the surface property inspection apparatus 10 uses a linear laser beam L under the control of the imaging control unit 201 of the arithmetic processing device 200 for the machined product that is the inspected object 1. The surface is imaged to generate a light section image (step S101). Thereafter, 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 data section 211 stores the acquired light section image along the moving direction of the object 1 to be inspected. Are sequentially stored in an image memory provided in the storage.

  Next, the fringe image frame generation unit 213 of the image processing unit 203 included in the arithmetic processing device 200 generates a fringe image frame by sequentially arranging the acquired light-cut images along the moving direction of the device under test 1 ( Step S103). The stripe image frame generation unit 213 outputs the generated stripe 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 luminance equal to or higher than a predetermined threshold Th, the sum of the brightness of the pixels, and the displacement of the light section line. The amount is calculated (step S105). These calculation results are used as the feature value of the light section line. 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 using the calculated light section line feature amount (particularly, a feature amount related to the displacement amount of the light section line) (step S107). Further, the luminance image calculation unit 221 calculates a luminance image by using the calculated light section line feature amount (particularly, the feature amount relating to the number of pixels of the bright line and the feature amount relating to the sum of luminance) (step S107). ). Further, the line width image calculation unit 223 calculates a line width image using the calculated light section line feature amount (particularly, the feature amount related to 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 the calculated images to the detection processing unit 225.

  Subsequently, the detection processing unit 225 performs a surface property detection process of the inspection object 1 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 for various types of defective parts existing on the surface of the inspection object 1. Through the flow as described above, various types of defects existing on the surface of the machined product that is the inspection object 1 are detected.

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

<Hardware Configuration of Arithmetic Processing Device 200>
Next, the hardware configuration of the arithmetic processing apparatus 200 according to the present embodiment will be described in detail with reference to FIG. FIG. 16 is a block diagram for explaining a 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. 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 device and control device, and controls all or a part of the operation in the arithmetic processing device 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 primarily stores programs used by the CPU 901, parameters that change as appropriate during execution of the programs, and the like. These are connected to each other by a bus 907 constituted by 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 the 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, remote control means (so-called remote control) using infrared rays or other radio waves, or may be an external connection device 923 such as a PDA corresponding to the operation of the arithmetic processing device 200. May be. Furthermore, the input device 909 includes, for example, an input control circuit that generates an input signal based on information input by a user using the operation unit and outputs the input signal to the CPU 901. By operating the input device 909, the user can input various data or instruct processing operations to the arithmetic processing device 200.

  The output device 911 is configured by a device capable of visually or audibly notifying acquired information to the user. 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 results obtained by various processes performed by the arithmetic processing device 200, for example. Specifically, the display device displays the results obtained by 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, acoustic data, and the like into an analog signal and outputs the analog signal.

  The storage device 913 is a data storage device 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 an HDD (Hard Disk Drive), a semiconductor storage device, an optical storage device, or a magneto-optical storage device. 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 recording medium reader / writer, and is built in or externally attached to the arithmetic processing unit 200. The drive 915 reads information recorded on a removable recording medium 921 such as a mounted magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, and outputs the information to the RAM 905. The drive 915 can also write a record on a removable recording medium 921 such as a magnetic disk, an optical disk, a magneto-optical disk, or a 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. Further, the removable recording medium 921 may be a compact flash (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) on which a non-contact type IC chip is mounted, 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 USB (Universal Serial Bus) port, an IEEE 1394 port, a SCSI (Small Computer System Interface) port, an RS-232C port, an HDMI (registered trademark) (High-Definition Multimedia Interface), and the like. By connecting the external connection device 923 to the connection port 917, the arithmetic processing apparatus 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 a communication interface configured with, for example, a communication device for connecting to the communication network 925. The communication device 919 is, for example, a communication card for wired or wireless LAN (Local Area Network), Bluetooth (registered trademark), or WUSB (Wireless USB). The communication device 919 may be a router for optical communication, a router for ADSL (Asymmetric Digital Subscriber Line), or a modem for various communication. The communication device 919 can transmit and receive signals and the like according to a predetermined protocol such as TCP / IP, for example, with the Internet and other communication devices. In addition, the communication network 925 connected to the communication device 919 is configured by a wired or wireless network, for example, the Internet, a home LAN, an in-house LAN, infrared communication, radio wave communication, satellite communication, or the like. May be.

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

  Hereinafter, the surface property inspection apparatus and the surface property inspection method according to the present invention will be specifically described with reference to examples. In addition, the Example shown below is only an example of the surface property inspection apparatus and surface property inspection method which concern on this invention, and the surface property inspection apparatus and surface property inspection method which concern on this invention are limited to the following example. It is not a thing.

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

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

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

  As the area cameras 103 and 105, a commercially available camera in which a CCD (pixel size: 5.5 μm × 5.5 μm) of 2048 pixels × 2048 pixels was mounted as an image sensor was 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 field angle is 26 °. The pixel size of the image to be captured is 0.25 mm × 0.25 mm, and the line width of the linear laser beam L is captured with the width of the bright line of 2 to 4 pixels on the captured image.

  When the disk-shaped workpiece is rotating in a direction orthogonal to the radial direction and parallel to the grinding surface, images are continuously captured by 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 was rotated for 5 msec. The illumination device 101 is provided above the vertical direction, irradiates the linear laser beam L downward in the vertical direction, and the installation angle φ of the two area cameras is ± 45 degrees. The image capture pitch was set to 0.25 mm to match the pixel size of the image sensor.

  The light cut image obtained by the inspection object imaging device 100 as described above was subjected to image processing by the arithmetic processing device 200 having the configuration as described above, and the surface property of the ground surface of the disk-like processed product was inspected. In calculating the line width image, the line width threshold Th2 is set to 5 pixels, and the luminance value is assigned using the 8-bit full scale as mentioned above.

  Among the obtained light cut images, the light cut image of the portion corresponding to the normal portion, the light cut image of the portion corresponding to the concave portion, and the light cut image of the portion corresponding to the remaining background portion are summarized in FIG. Indicated. As is clear from FIG. 17, in the light cut image corresponding to the normal portion, the straight line segment is imaged while the line width of the light cut line is substantially constant, and in the light cut image corresponding to the recess, It can be seen that the light cutting line is bent at a position corresponding to the recess without substantially changing the line width of the light cutting line. On the other hand, in the light cut image corresponding to the background remaining portion, it was confirmed that the line width of the light cut line was enlarged as is clear when compared with the light cut image corresponding to the normal portion.

  FIG. 18 shows a luminance image, a depth image, and a line width image calculated by the arithmetic processing device 200 using the light section images obtained from the respective area cameras. In FIG. 18, “area camera 1” is an area camera provided on the downstream side in the rotational direction of the disk-shaped workpiece, and “area camera 2” is provided on the upstream side in the rotational direction of the disk-shaped workpiece. Area camera.

  As apparent from the two types of luminance images shown in FIG. 18, in the luminance image, a portion that appears white as a defect candidate site is affected by the reflected light from surrounding noise caused by dust and minute unevenness. It can be seen that there are many. It can be seen that it is difficult to make the remaining surface of the background focused in the present invention obvious 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 as defect candidate sites. It can be seen that it is difficult to make the remaining surface portion 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 state of the image is clearly different between the remaining background portion and the other portions, and the remaining surface portion becomes obvious. It became clear that it was possible. As is clear from this figure, it was confirmed that the discrimination between the remaining portion of the background and the surrounding noise was high by using the line width image.

  Further, as a result of comparing the two types of line width images calculated from the two area cameras, the line width image based on the light cut image from the area camera 1 is the line width image based on the light cut image from the area camera 2. It is clear that it is clearer. This result suggests that the background portion of the disk-like processed product used as the object to be inspected 1 has surface directionality. 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 remaining portion of the background, and underestimate the remaining portion of the background and rust. It was confirmed that it was possible to avoid the possibility that

  The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to such 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.

DESCRIPTION OF SYMBOLS 10 Surface texture inspection apparatus 100 Test object imaging device 101 Illumination device 103,105 Area camera 200 Arithmetic processing device 201 Imaging control part 203 Image processing part 205 Display control part 207 Storage part 211 Data acquisition part 213 Stripe image frame generation part 215 Image Calculation unit 217 Optical 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 object to be inspected,
The image of the linear laser light on the surface is obtained by irradiating the surface of the moving object to be inspected with linear laser light and imaging the surface irradiated with the linear laser light. An inspected object imaging device for generating a plurality of light cut images along the moving direction of the inspected object;
An arithmetic processing unit that performs image processing on the light-cut image generated by the inspection object imaging device and determines a surface property of the surface of the inspection object;
With
The inspected object imaging device includes:
An illumination device that irradiates the surface of the object to be inspected with the linear laser beam;
An imaging device for imaging the surface irradiated with the linear laser beam;
Have
The arithmetic processing unit includes:
Based on a fringe image frame in which light cutting lines, which are line segments corresponding to the irradiated portions of the linear laser light in each of the plurality of light cutting images, are sequentially arranged along the moving direction, A depth image representing an uneven state of the surface, a luminance image representing a 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 is associated with the luminance value;
A detection processing unit that detects a surface property of the object to be inspected based on the calculated depth image, the luminance image, and the line width image;
Have
The said detection process part is a surface property inspection apparatus which detects whether the surface residual part or rust which used the said intermediate material as a raw material exists in the surface of the said to-be-inspected object based on the said line width image.   The said detection process part detects the said background residual part and the said rust based on whether the luminance value of the said line | wire width image is more than the 1st threshold value for the detection of the said background residual part and rust. The surface texture inspection apparatus according to 1.   The image calculation unit calculates and calculates a difference between the line width at each position in the extending direction of the light cutting line and a predetermined threshold line width for each light cutting line in the striped image frame. The surface property inspection apparatus according to claim 1, wherein the line width image is calculated by assigning a luminance value according to the magnitude of the difference.   The image calculation unit calculates a barycentric position in a line width direction of the light cutting line along the moving direction of the object to be inspected, and a reference position that is a position in a moving direction designated in advance with respect to the light cutting image; The surface property inspection apparatus according to claim 1, wherein the depth image is calculated based on a displacement amount with respect to the gravity center position. The detection processing unit
Identifying a defect site based on whether the brightness value of the depth image and the brightness image is greater than or equal to a second threshold for defect site identification;
For the identified defective part, extract feature quantity information regarding the form and luminance value of the defective part,
The surface property 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 the detection of the defective portion other than the portion where the background remaining portion or the rust is detected based on the line width image. The surface texture inspection apparatus described.   The inspection object imaging device includes at least two imaging devices that image 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. Item 7. The surface property inspection apparatus according to any one of Items 1 to 6. A surface property inspection method using a machined product made of an intermediate material as an inspection object,
The surface of the moving object to be inspected is irradiated with linear laser light from an illuminating device, and the surface of the surface irradiated with the linear laser light is imaged by an imaging device, whereby the linear laser on the surface is irradiated. A light section image generation 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 fringe image frame in which light cutting lines, which are line segments corresponding to the irradiated portions of the linear laser light in each of the plurality of light cutting images, are arranged in order along the moving direction by the arithmetic processing device, A depth image representing the uneven state of the surface of the inspection object, a luminance image representing a 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 for calculating a line width image in which a 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 property of the object to be inspected based on the calculated depth image, the luminance image and the line width image by an arithmetic processing unit;
Including
In the detection processing step, based on the line width image, it is detected whether a background remaining portion or rust made of the intermediate material is present on the surface of the object to be inspected. . A machined product made of an intermediate material is used as an inspection object, and the surface of the moving inspection object is irradiated with linear laser light, and the surface irradiated with the linear laser light is imaged. A computer capable of mutual communication with an inspection object imaging device that generates a plurality of light cut images that are captured images of the linear laser light on the surface along the moving direction of the inspection object;
Based on a fringe image frame in which light cutting lines, which are line segments corresponding to the irradiated portions of the linear laser light in each of the generated plurality of light cutting images, are sequentially arranged along the moving direction. A depth image representing an uneven state on the surface of the inspection object, a luminance image representing a luminance distribution of the linear laser light on the surface of the object to be inspected, 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 for detecting a surface property of the object to be inspected based on the calculated depth image, the luminance image, and the line width image;
Realized,
The detection processing function is a program for detecting, based on the line width image, whether a background remaining portion or rust made of the intermediate material is present on the surface of the object to be inspected.