WO2011070750A1 - Dispositif et procede d'inspection la forme d'un pneu - Google Patents

Dispositif et procede d'inspection la forme d'un pneu Download PDF

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Publication number
WO2011070750A1
WO2011070750A1 PCT/JP2010/007038 JP2010007038W WO2011070750A1 WO 2011070750 A1 WO2011070750 A1 WO 2011070750A1 JP 2010007038 W JP2010007038 W JP 2010007038W WO 2011070750 A1 WO2011070750 A1 WO 2011070750A1
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WIPO (PCT)
Prior art keywords
image
height
tire
mask
inspection
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PCT/JP2010/007038
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English (en)
Japanese (ja)
Inventor
英二 高橋
尚和 迫田
敏之 辻
玄 武田
将雄 村上
Original Assignee
株式会社神戸製鋼所
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Application filed by 株式会社神戸製鋼所 filed Critical 株式会社神戸製鋼所
Priority to EP10835677.5A priority Critical patent/EP2500686B1/fr
Priority to CN201080055305.2A priority patent/CN103038601B/zh
Priority to US13/514,285 priority patent/US9097514B2/en
Publication of WO2011070750A1 publication Critical patent/WO2011070750A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
    • G01B11/0608—Height gauges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00—Testing of vehicles
    • G01M17/007—Wheeled or endless-tracked vehicles
    • G01M17/02—Tyres
    • G01M17/027—Tyres using light, e.g. infrared, ultraviolet or holographic techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30164—Workpiece; Machine component

Definitions

  • the present invention relates to a tire inspection technique, and more particularly, to a tire shape inspection method and a tire shape inspection apparatus for inspecting a shape defect of a sidewall surface on which uneven marks are formed using an image processing technique.
  • the tire has a structure in which various materials such as rubber, chemical fiber and steel cord are laminated.
  • a bulge convex part
  • a dent Dent
  • a depression concave
  • Tires in which such shape defects as bulges and dents are generated need to be inspected and excluded from shipment due to safety problems or appearance problems.
  • a display mark (a mark that is normal unevenness) is formed on the sidewall surface of the tire to display the product type and size, the manufacturer's logo, and the like. Therefore, in the shape defect inspection process on the sidewall surface, it is necessary not to erroneously detect this display mark as a shape defect.
  • the surface shape of the tire is detected by capturing an image of line light irradiated on the surface of a relatively rotating tire and performing shape detection by a light cutting method based on the captured image.
  • a tire shape detecting device is disclosed.
  • This apparatus has a line light irradiation means for continuously irradiating a plurality of line lights from a direction different from the detection height direction in the light cutting line so that one light cutting line is formed on the surface of the tire, Imaging means for imaging in the direction in which the principal rays of the plurality of line lights irradiated on the surface of the tire are regularly reflected with respect to the surface of the tire.
  • This tire shape detection device detects a tire surface shape by irradiating a plurality of line lights continuously on the tire surface and capturing images of the irradiated line lights.
  • Patent Document 2 discloses a method for inspecting the three-dimensional shape of one or more figures formed by unevenness on the tire surface.
  • This method includes a step of measuring unevenness height for each area element in a predetermined tire surface area including these figures to obtain unevenness distribution data, and a figure template for each figure in advance.
  • a step of identifying a tire surface portion corresponding to the graphic model in the tire surface area from the three-dimensional shape data of the prepared graphic model and the acquired uneven distribution data, and specifying for each graphic Determining the degree of coincidence between the uneven distribution data of the tire surface portion and the three-dimensional data of the graphic model, and determining the pass / fail of the three-dimensional shape of the graphic based on the degree of coincidence.
  • This method for inspecting tire irregularities particularly calculates the degree of coincidence between the three-dimensional irregularity distribution data obtained by irradiating the tire surface with sheet light and the three-dimensional shape data of the graphic model created from the CAD data.
  • This is a technique for inspecting the presence or absence of defects.
  • a graphic model prepared in advance as a normal concavo-convex figure is used as teaching data.
  • the model is created from tire CAD data and mold CAD data.
  • Patent Document 2 if teaching data (reference data) is created using tire CAD data or mold CAD data, numerical values that are not affected by tire deformation or defects can be obtained.
  • the difficulty of the technique of Patent Document 1 may be avoided.
  • the tire is a rubber product and the tire shape inspection which is the subject of the invention of Patent Document 1 inspects a tire containing air, the amount of deformation of the tire from CAD data is large. Therefore, even if the coordinates of the CAD data and the coordinates of the tire corresponding thereto are matched, the amount of calculation and calculation becomes enormous, so that the method of Patent Document 2 is difficult to apply in practice.
  • An object of the present invention is to provide a tire shape inspection method and a tire shape inspection device.
  • the tire shape inspection method inspects a shape defect of a sidewall surface of an inspection tire using an image of the sidewall surface of a sample tire having a sidewall surface on which concave and convex marks are formed.
  • the tire shape inspection method includes a teaching work process and an inspection work process.
  • the teaching work step in a sample original image that is a two-dimensional image of a sidewall surface of the sample tire, a boundary line that is an outline of the uneven mark is detected, and a mask image that indicates a position of the boundary line is generated
  • the image generation step in the sample original image, the height of the remaining area excluding the area corresponding to the position of the boundary line indicated in the mask image is classified using a plurality of discrete height thresholds.
  • the inspection operation step includes a difference processing step of generating an unevenness removal image by removing the unevenness mark by subtracting the height offset image from an inspection image that is a two-dimensional image of a sidewall surface of the inspection tire; A shape defect inspection step of inspecting a shape defect on the sidewall surface of the inspection tire based on the unevenness removal image obtained as a result of the difference processing step.
  • FIG. 1 is the schematic showing the structure of the tire shape inspection apparatus by embodiment of this invention
  • (b) represents the three-dimensional arrangement
  • FIG. It is a schematic diagram showing the sidewall surface of a tire. It is a flowchart which shows the processing content of the tire shape inspection method by embodiment of this invention.
  • (A) is a flowchart which shows the mask image generation process in the tire shape inspection method by embodiment of this invention
  • (b) is a flowchart which shows the offset image generation process in the tire shape inspection method by embodiment of this invention. is there.
  • (A)-(d) is a schematic diagram which shows the process of the image processing in the tire shape inspection method by embodiment of this invention.
  • (A), (b) is a figure which shows the relationship between a height pixel profile and a label area
  • (A)-(c) is the schematic which shows the method of calculating
  • (A)-(e) is a figure which shows the interpolation method of the height pixel value to the position corresponding to a mask range in the tire shape inspection method by embodiment of this invention.
  • the tire shape inspection apparatus 1 captures an image of line light irradiated on the surface of a rotating tire T with a camera, and performs shape detection by a light cutting method based on the captured image. Measure the height of each part of T. Next, the tire shape inspection apparatus 1 replaces the measured height of each part of the tire T with a corresponding luminance value, and obtains a two-dimensional image (inspection image) of the surface of the tire T.
  • the tire shape inspection apparatus 1 uses the “inspection image” of the tire T and the “mask image” and “height offset image” of the sample tire (defect-free tire) to determine the sidewalls of the tire T.
  • the display mark formed on the surface is removed, and then a defect present on the surface of the tire T is inspected.
  • the “mask image” and “height offset image” are created using a “sample original image” obtained by imaging a sample tire. Details of the “sample original image”, “mask image”, and “height offset image” will be described later.
  • the tread surface and the sidewall surface of the tire T can be the measurement object, but in the present embodiment, the sidewall surface is the measurement object.
  • the sidewall surface of the tire T is a portion between a tread surface in contact with the road surface and a bead portion sandwiched between rims.
  • white portions are display marks (normal figures such as characters, logos, patterns, etc.) formed on the sidewall surface and can be considered as “normal uneven marks”.
  • corrugated mark is comprised by the unevenness
  • the tire shape inspection apparatus 1 includes a tire rotating machine 2, sensor units (imaging units) 3 (3a, 3b), an encoder 4, an image processing device 5, and the like.
  • the tire rotating machine 2 is a rotating device provided with a motor or the like that rotates the tire T that is the object of shape inspection around the rotation axis.
  • the tire rotating machine 2 rotates the tire T at a rotation speed of 60 rpm, for example. During this rotation, the surface shape in a range over the entire circumference of the sidewall surface is detected by the sensor unit 3 described later.
  • the tire shape inspection apparatus 1 includes two sensor units 3 (3a, 3b) used for measuring the shapes of the two sidewall surfaces of the tire T.
  • Each of the sensor units 3a and 3b incorporates a line light irradiation unit that irradiates the surface of the rotating tire T with line light (light cutting line), an imaging camera 6 that captures an image of the line light reflected from the surface of the tire T, and the like. Unit.
  • FIG. 1 (b) is a diagram schematically showing the arrangement of devices provided in the sensor unit 3.
  • the Y axis represents the radial direction of the circular tire T at the shape detection position of the tire T.
  • the Z axis represents the detected height direction from the sidewall surface at the shape detection position of the tire T (the direction of the detected surface height).
  • the X axis represents a direction orthogonal to the Y axis and the Z axis. That is, in the sensor unit 3 used for detecting the shape of the sidewall surface of the tire T, the Z axis is a coordinate axis parallel to the rotation axis of the tire T, and the Y axis is the direction of the normal to the rotation axis of the tire T. Is a coordinate axis representing. Note that the correspondence relationship between the tire T and the coordinate axis may vary depending on the manner of support of the camera 6.
  • the line light irradiation section includes a plurality (three in FIG. 1B) of line light sources 7a, 7b, and 7c.
  • the line light irradiation unit irradiates a plurality of line lights so that one light cutting line is formed on one line Ls on the surface of the tire T by the line light sources 7a, 7b, and 7c. It is.
  • the plurality of line lights are irradiated from a direction different from the detection height direction (Z-axis direction) in the one line Ls (light cutting line).
  • the plurality of line lights are irradiated so as to be continuous on the one line Ls.
  • the imaging camera 6 includes a camera lens 8 and an imaging element 9, and displays a plurality of line light images v1 (images of light cutting lines on one line Ls) irradiated continuously to the sidewall surface of the tire T. Take an image.
  • the tire rotating machine 2 is provided with an encoder 4.
  • the encoder 4 is a sensor that detects the rotation angle of the rotation shaft of the tire rotating machine 2, that is, the rotation angle of the tire T, and outputs the detected rotation angle as a detection signal.
  • the detection signal is used for controlling the imaging timing of the imaging camera 6 provided in the sensor units 3a and 3b.
  • the image processing device 5 receives a detection signal output from the encoder 4 every time the tire T rotating at a speed of 60 rpm rotates by a predetermined angle, and the sensor units 3a and 3b receive the detection signal in accordance with the reception timing of the detection signal. 1 is controlled so that the shutter of the imaging camera 6 is released. Thereby, imaging is performed at a predetermined imaging rate that matches the reception timing of the detection signal.
  • the image processing device 5 may be incorporated in the sensor units 3a and 3b.
  • the control signal from the unit driving device and the rotation speed pulse signal from the encoder 4 are inputted into each sensor unit 3a, 3b, and the final result is sent from each sensor unit 3a, 3b to the host computer. Output each.
  • the unit driving device may not have a role of issuing an instruction to release the shutter.
  • the unit driving device may issue a command such as a laser lighting instruction or a measurement start instruction to the sensor units 3a and 3b. You may have.
  • the instruction to release the shutter is in a form that is controlled by the image processing device 5 incorporated in each of the sensor units 3a and 3b in synchronization with the pulse signal from the encoder 4 in accordance with the amount of movement by the rotation of the tire T. May be.
  • Signals (1-line images) from the sensor units 3a and 3b are input to the image processing device 5.
  • the image processing device 5 applies the principle of the triangulation method to the input one-line image, thereby obtaining the height distribution information of the portion irradiated with the optical cutting line (one line portion on the sidewall surface). obtain.
  • the image processing device 5 replaces the measured height of each part on the surface of the tire T with a corresponding luminance value, and stores each luminance value in a built-in frame memory (imaging memory). A two-dimensional image (inspection image) of the surface of T is obtained.
  • the surface height measurement value (luminance value) of each part in the entire circumferential range (360 ° range) of the sidewall surface represents the radial direction of the tire T.
  • Y This is information arranged in a two-dimensional coordinate system including an axis and an X axis (frame) representing the circumferential direction of the tire T.
  • the height distribution information corresponds to the graph illustrated in FIG. 7B
  • the inspection image and the sample original image correspond to the image illustrated in FIG. 7A.
  • the value on the vertical axis (height pixel value) in the height distribution information and the luminance value of the inspection image have a one-to-one correspondence and are used synonymously in the following description.
  • the image processing apparatus 5 of the present embodiment removes only the normal concavo-convex mark from the inspection image based on the obtained inspection image and the height distribution information corresponding to one line in the inspection image, and after the removal.
  • the image processing device 5 is realized by hardware configured by, for example, a personal computer.
  • FIG. 3 is a flowchart showing the processing contents executed by the image processing apparatus 5.
  • the processing performed by the image processing device 5 includes an “inspection work process” for inspecting irregularities present on the sidewall surface of the tire online. Furthermore, this process has a “teaching work process” as a previous process prior to the inspection work process.
  • the inspection work process includes a “difference processing process (S6)” and a “shape defect inspection process (S7)”.
  • difference processing step (S6) the height offset image is subtracted from the inspection image that is a two-dimensional image of the sidewall surface of the inspection tire, and the boundary region represented by the mask image is removed.
  • shape defect inspection step (S7) each step S6, S7 for inspecting the shape defect of the sidewall surface of the inspection tire based on the normal uneven mark removal image obtained as a result of the difference processing step (S6), This is performed by a difference processing unit and a shape defect inspection unit provided in the image processing apparatus 5.
  • the teaching work process includes a “mask image generation process (S2)” and a “height offset image generation process (S3)”.
  • the mask image generation step (S2) in the sample original image that is a two-dimensional image of the sidewall surface of the sample tire, a boundary line that is an outline of the normal uneven mark is detected, and a mask image indicating the position of the boundary line is generated.
  • the height offset image generation step (S3) in the sample original image, the height of the remaining area excluding the area corresponding to the position of the boundary line shown in the mask image is determined using a plurality of discrete height thresholds.
  • Each of the steps S2 and S3 is performed by a mask image generation unit and a height offset image generation unit provided in the image processing apparatus 5.
  • a setup operation is performed as a registration operation before online inspection for each tire type (TireID).
  • This setup operation is an operation for registering design information related to the tire shape, such as the tire diameter and the width of the contact surface (tread surface) that is different for each TireID, and is indispensable when there are multiple types of tires. is there.
  • the above-described setup work is performed prior to the inspection work process.
  • the height image (raw data) obtained here may have “undetected points”.
  • the undetected point is a point where the height coordinate cannot be obtained because the sheet light does not return to the camera due to the step difference of the normal concave / convex mark and the received light intensity is below a specified value.
  • height coordinate 0 black point
  • a linear interpolation value is calculated using the height coordinates of two pixels that have already been detected in the vicinity of the undetected point and are arranged in the tire circumferential direction with the undetected point in between.
  • the interpolation value is embedded as the coordinates of the undetected point.
  • the method for determining the coordinates of undetected points is not limited to this.
  • the height in the vicinity of the undetected point is copied as it is (zero-order approximation), and a plane is formed by four points surrounding the undetected point (two points in the circumferential direction and two points in the radial direction) to perform plane interpolation.
  • the coordinates of the undetected point can be determined by such a method. If the height coordinates of undetected points are left undefined, an unexpectedly large differential value will appear in the next smooth differential process, which will eventually detect the position (boundary line) of the normal concavo-convex mark. Care must be taken because it may have adverse effects.
  • the height image after the linear interpolation includes low-order curve components in the tire radial direction and the tire circumferential direction. . If the next smooth differentiation process is performed with the curved component left, the differential value increases due to the curved component. In some cases, it is difficult to distinguish the differential value resulting from the curved component from the differential value of the boundary line of the normal uneven mark that is originally desired to be detected. For this reason, it is preferable to perform a planarization process for removing the curved component from the height image after linear interpolation.
  • This low-order bending component which is expected to reflect tire design CAD data and mold CAD data, can be corrected using a shape model from these CAD data.
  • cooperation with CAD data is difficult in terms of system, and in this embodiment, an ideal curved component is acquired from the acquired height image itself.
  • the curved component is mathematically modeled by least square fitting with a quadratic curve of the cross-sectional profile shape, and the curved component that has been mathematically modeled is removed from the height image after the linear interpolation.
  • This mask image generation step (S2) in FIG. 3 will be described.
  • This mask image generation step (S2) is shown as a flowchart of mask image generation in FIG.
  • a differential filter two-dimensional smooth differential filter
  • a Sobel filter or a Laplacian filter is applied to the planarized height image (hereinafter referred to as a sample original image) obtained in the above process (S21).
  • a processed differential image is obtained (S22).
  • the average value (Ave) and variance (1 ⁇ ) are obtained for each line of the differential value image thus obtained.
  • a binarization threshold that can separate the boundary line of the normal uneven mark from the differential value like background noise is determined.
  • the image of the differential value is binarized based on this binarization threshold. Thereby, a binarized image showing the boundary line of the normal uneven mark is obtained (S23).
  • the isolated pixel points in the obtained binarized image are removed by the isolated point removal filter, and further, the boundary portion of the normal concavo-convex mark in the image obtained by removing the isolated pixel points It is preferable to perform a process of expanding with an expansion filter.
  • the image obtained through the above processing is a mask image in which the value of the binary pixel point in the boundary line portion is 1 and the value of the binary pixel point in the portion other than the boundary line is 0, and FIG. As shown in This mask image is stored in a memory in the image processing apparatus 5 (S24).
  • This height offset image generation step (S3) in FIG. 3 will be described with reference to FIG. 4, FIG. 6, and FIG.
  • This height offset image generation step (S3) is shown in FIG. 4B as a flowchart of offset image generation.
  • a sample original image that has undergone linear interpolation and planarization is used (S31).
  • a portion indicated by a solid line is a part of the one-line phase adjustment line and indicates a normal uneven mark portion.
  • the graph of FIG. 7B shows a height pixel profile (cross-sectional shape) of the one-phase phase adjustment line schematically shown in FIG. 7A, for example.
  • the low-frequency height pixel change (low-frequency component), which is the undulation of the sidewall surface, exists as a whole, and the height pixel value changes abruptly at the normal uneven mark portion.
  • the low-frequency height pixel change is, for example, a change indicated by a low frequency of about 20th to 70th order (about 20th to 70th order after discrete Fourier transform).
  • the phase adjustment line will be described.
  • the final setup data (teaching data) is acquired from the height image (raw data) of the sidewall surface of the sample tire, which is a tire with no defects, by the image processing shown in this embodiment. And register with the device.
  • the phase difference is calculated from the shape difference between the two images in the “phase adjustment line”.
  • An arbitrary line for that purpose (for example, designated in the setup) is set as a phase adjustment line.
  • each normal uneven mark shown here is substantially the same height, but is on (formed) the low frequency height pixel change (Runout component) described above, so the low frequency The height is different according to the change in the pixel height. This will be described in more detail with reference to the graph of FIG.
  • a thick solid line P1 indicates a low-frequency height pixel change (Runout component) in the surface portion of each normal concavo-convex mark.
  • the thick solid line P1 is a portion other than the normal uneven mark of the original height pixel profile near the height pixel value 0. Substantially continuous with the runout component (base runout component) in the portion.
  • the low-frequency height pixel change (Runout component) in the surface portion of the normal concavo-convex mark is substantially the same as the base Runout component. It turns out that it is continuous.
  • the difference (P1 ⁇ P2) between the thick solid line P1 and the thick solid line P2 at this time becomes a fixed height value (height threshold) Pth.
  • a thick solid line Q1 indicating a low-frequency height pixel change (Runout component) on the surface portion of the normal uneven mark on the right is offset to the position of the thick solid line Q2, and the thick solid line R1 is the thick solid line R2. Is offset to the position of.
  • the thick solid line Q2 and the thick solid line R2 after the offset are not continuous with the base runout component. Therefore, another height fixed value is obtained by changing the offset amount of the height profile so that the thick solid line R2 is continuous with the base runout component.
  • the offset amount of the height profile is changed so that the thick solid line Q2 is continuous with the base runout component to obtain another height fixed value. In this way, a plurality of discrete height thresholds are obtained (S32).
  • Such a plurality of discrete fixed height values may be determined for each of the divided regions by dividing the sidewall surface into a plurality of regions, in addition to determining them in common over the entire sidewall.
  • a height image is displayed by a display means, and a GUI (mouse operation, etc.) is used while taking into account the meaning of characters and the layout of figures by human and visual inspection.
  • a rectangular area or the like is set as an area to be divided.
  • FIG. 6A is a graph obtained by enlarging several hundred points along the X coordinate in the circumferential direction of the tire in one line of the height profile in the circumferential direction of the sidewall in the sample original image.
  • the rectangular wave in the graph is obtained by superimposing and displaying in the graph the image at the same position as the height profile among the inverted mask images generated by inverting the previously obtained mask image.
  • the inverted mask image is a rectangular wave that oscillates between height pixel values 0 and 1 in the same manner as the mask image before inversion. However, in order to make the graph easier to see, the inverted mask image is moved in the positive direction of the height pixel value (Y The axis is moved upward).
  • the value of the binary pixel point in the boundary line portion is 0, and the value of the binary pixel point in the portion other than the boundary line is 1, so in FIGS.
  • a region corresponding to a height pixel value of 0 in the mask image indicates the boundary line portion of the normal uneven mark.
  • a label number is assigned to each area corresponding to the height pixel value 1 divided by the boundary line portion, and these areas are determined as label areas.
  • the longest label area (in the case of FIG. 6B, the leftmost label area of the graph) W1 is registered as the start area of the height offset calculation. Thereafter, an average height pixel value in the vicinity including the end point in contact with the boundary line of the normal concavo-convex mark is obtained from the height profile of FIG. Next, an average height pixel value in the adjacent label region W2 is determined with the boundary line interposed therebetween (via the boundary line). After that, the height difference between the area pair composed of the label area W1 and the label area W2 is calculated. This height difference is a difference between the two height pixel values obtained as described above. The height offset value of the average height pixel value in the longest label area (calculation start area) W1 is set to zero.
  • the difference between the height difference between the pair of regions consisting of the label region W1 and the label region W2 is compared with the plurality of discrete fixed height values acquired earlier, and the difference between the height difference is the smallest (
  • a substantially fixed height value is assigned as the height offset value of the label area W2 adjacent to the longest label area W1.
  • the fixed height value having the smallest difference is assigned as the height offset value of the region W2 in the rearrangement order among the pair of label regions constituting the region pair.
  • the assigned height offset value is recorded in the offset image memory area.
  • the same method is used to assign height offset values to all the remaining label areas W3, W4,. That is, for the remaining plurality of region pairs other than the region pair of region W1 and region W2 (for example, a region pair composed of region W2 and region W3, a region pair composed of region W3 and region W4, etc.)
  • the height fixed value having the smallest difference from the height difference of each area pair is assigned as the height offset value of the label area whose arrangement order in each area pair is later (S33).
  • the height offset image shown in FIG. 5B is obtained by assigning the height offset values to the lines of the entire range of the sample original image (S34).
  • the “discrete multiple fixed height values” as described above If the height image acquired during teaching has no low-frequency runout component and the normal unevenness mark has the same value as the tire design CAD data itself, the “discrete multiple fixed height values” as described above.
  • the obtained sample original image (height image) itself is registered as a height offset image without using, or the obtained height difference itself without using "discrete multiple fixed height values” (The height difference itself between adjacent regions) may be set as a relative offset value.
  • the mask image and the offset image are registered in the image processing apparatus 5, and the teaching work step is completed.
  • the teaching work step is completed.
  • an inspection work process for inspecting irregularities (Bulge / Dent) on the sidewall surface of the tire to be inspected is performed.
  • the inspection operation process will be described below with reference to FIGS. 3 and 5.
  • image matching is performed so that normal uneven marks (for example, logos) existing on the sidewall surface are matched, and the phase difference is corrected.
  • the height offset image registered at the time of teaching is subtracted from the inspection image. Thereby, the height image of the sidewall surface from which the height of the normal unevenness mark is subtracted is obtained.
  • the boundary line portion is determined based on the mask image. Interpolate. The interpolation process will be described below.
  • the average height coordinates of two positions sandwiching the mask range of the mask image that is, both ends of the normal uneven mark
  • the average height coordinate value is obtained, and the average height coordinate is adopted as the height coordinate value of the mask range to perform linear interpolation.
  • the maximum in a partial range not more than the mask range length with respect to the height pixel value in the mask range of the mask image By selecting a value or a minimum value and adopting the selected height coordinate value as the height coordinate of the mask range, all the height coordinates in the mask range are interpolated.
  • the shape defect inspection step (S7) of FIG. 3 is performed using the image after the character unevenness removal.
  • the image after the character unevenness removal shown in FIG. 5 (d) only the height change of the normal unevenness mark is removed, and the height of the convex defect portion shown in white and oval on the left side of the image is as shown in FIG. 5 (a). It remains unchanged compared to the original image (inspection image).
  • the shape defect inspection step (S7) the convex defect portion or the concave defect portion remaining in the image after the character unevenness removal is thus detected.
  • shape defect inspection step (S7) an existing image processing method can be employed. Defect extraction by binarization and defect extraction by pattern matching may be employed.
  • the tire shape inspection the tire shape can be inspected without being affected by the deformation unique to the rubber product or the deformation caused by inflating the tire.
  • each process such as the mask image generation process (S2) and the height offset image generation process (S3) may be automatically performed, or may be performed manually by the operator with reference to the image. Moreover, you may repeat each process in multiple times.
  • an inspection image, a mask image, a height offset image, an image after removing the normal concave / convex mark, and the like are displayed in parallel or by switching, and the operator confirms each image and originally connects it. It may be possible to confirm whether the boundary line to be made is not cut and whether an inappropriate part is recognized as the boundary line.
  • the set height offset image is confirmed, and it is confirmed whether or not one type of fixed height value set for each label is abnormal. If there is a defective part, it is preferable to change the height offset value by specifying the correction area (increase or decrease by ⁇ 1), and when corrected, recalculate the height offset image.
  • the image after removing the normal irregularity mark shows the flattened state when actually inspecting online based on the teaching information set this time, and after checking the height image after processing, if there is a defective part, It is desirable to return to the confirmation and correction work of the mask image or the height offset image and perform correction and recalculation, respectively.
  • the mask image generated in the present embodiment may have a mask range (mask area) larger than the concavo-convex defect (Bulge / Dent) to be detected.
  • the concavo-convex defect to be detected may be missed because it is masked. Therefore, it is preferable to provide a process for interpolating the height coordinate value. More preferably, the interpolation processing of the mask range is changed depending on the size (length) of the mask range.
  • the X-axis indicates the tire rotation direction (circumferential direction), and the Y-axis indicates the amount of change in the height of the tire surface.
  • a height image of the tire sidewall surface is obtained by subtracting the height offset image registered during teaching from the inspection image.
  • FIG. 8A shows a part of one line of the obtained height image.
  • FIG. 8B shows a portion corresponding to the height image of FIG. 8A in the obtained reverse mask image.
  • the value of the binary pixel point in the mask range corresponding to the normal uneven mark in the height image is 0.
  • the height coordinate value of the position corresponding to the mask range is all 0, so the height coordinate value must be interpolated at the masked position.
  • a method of interpolating the height coordinate value three interpolation processes of linear interpolation, average interpolation, and envelope interpolation are conceivable.
  • the height coordinate value is interpolated by linear interpolation or average interpolation.
  • the position corresponding to the mask range of the post-mask height image has a length exceeding several pixels (for example, 10 pixels or more), the height coordinate value is interpolated by envelope interpolation.
  • the linear interpolation is the height coordinate value of two positions sandwiching the position (region) corresponding to the mask range of the mask image, that is, the height coordinate values of both ends of the normal uneven mark.
  • This is an interpolation method in which values on a straight line that are connected by a straight line and change linearly are assigned as height coordinate values at positions corresponding to the mask range.
  • the average interpolation is the average of the height coordinate values of two positions sandwiching the position (area) corresponding to the mask range of the mask image, that is, the height coordinates of both ends of the normal uneven mark.
  • This is an interpolation method in which the average of the values is obtained and the average of the height coordinate values (average height coordinate value) is assigned as the height coordinate value of the position corresponding to the mask range.
  • the envelope interpolation is a method of setting a window as a partial range at a position (region) corresponding to a mask range along the X-axis direction, and setting the maximum in the window range. Is assigned as the height coordinate value of the position corresponding to the mask range for interpolation.
  • the window in the envelope interpolation is a range that overlaps at least part of the position corresponding to the mask range, is shorter than the mask range, and extends in the direction along the mask range (X-axis direction).
  • the mask range shown in the inverted mask image in FIG. 8B has a length of 40 pixels in the X-axis direction, for example.
  • the point with the smallest X coordinate (leftmost point) of the mask range is set as the window center point.
  • a range including the window center point and several pixels on the left and right of the window center point is set as a window, and the height image in FIG. 8A is set.
  • the window is set to a length of 21 pixels with the leftmost point of the mask range as the window center point.
  • the number of pixels in the window is desirably about half or less than the number of pixels in the mask range.
  • the maximum height coordinate value is detected within the window range set as described above, and the detected value is set as the height coordinate value of the position corresponding to the window center point, and the height after masking in FIG. Assign to an image.
  • the window center point is moved by one pixel in the X-axis direction, and a new window including the moved window center point is set by the method described above.
  • the maximum height coordinate value is detected within the set new window, and the detected value is assigned to the post-mask height image as the height coordinate value of the position corresponding to the window center point.
  • FIG. 8E shows a height image that has been subjected to the above-described envelope interpolation, and almost reproduces the outline of the profile of the normal concave / convex mark indicated by the height image of FIG. 8A.
  • the maximum height coordinate value in the window range is assigned as the height coordinate value of the position corresponding to the window center point, but the minimum height coordinate value is assigned to the height coordinate of the mask range. It may be assigned as a value.
  • the obtained height image substantially reproduces the outline of the profile of the base portion of the normal uneven mark indicated by the height image in FIG.
  • the global unevenness change (indicated by the low frequency component) of the mask range on the tire sidewall surface is evaluated. Can do.
  • the average of the maximum value and the minimum value of the height coordinate values within the window range can be assigned as the height coordinate value of the position corresponding to the window center point.
  • the tire shape inspection method inspects a shape defect on a sidewall surface of an inspection tire using an image of the sidewall surface of a sample tire having a sidewall surface on which concave and convex marks are formed.
  • the tire shape inspection method includes a teaching work process and an inspection work process.
  • the teaching work step in a sample original image that is a two-dimensional image of a sidewall surface of the sample tire, a boundary line that is an outline of the uneven mark is detected, and a mask image that indicates a position of the boundary line is generated
  • the image generation step in the sample original image, the height of the remaining area excluding the area corresponding to the position of the boundary line indicated in the mask image is classified using a plurality of discrete height thresholds.
  • a height offset image generating step for generating a height offset image indicating the height of the concave and convex marks.
  • the inspection work step includes subtracting the height offset image from an inspection image that is a two-dimensional image of a sidewall surface of the inspection tire, thereby removing the uneven mark from the inspection image to generate an unevenness removal image.
  • a processing step, and a shape defect inspection step for inspecting a shape defect on a sidewall surface of the inspection tire based on the unevenness removal image.
  • a differential image is obtained by applying a differential filter to emphasize the boundary line portion of the concave and convex marks, and a predetermined threshold is applied to the obtained differential image. May be used to generate the mask image by binarizing the differential image.
  • the threshold value can be set only in one direction of the differential direction, so that the boundary line portion of the concave and convex marks can be stably Can be extracted.
  • the undetected points in the sample original image are interpolated to remove the undetected points, and the undetected points are determined based on the profile shape of the sidewall surface.
  • the curved component of the sidewall surface may be removed from the removed image, and the image from which the undetected points are removed may be planarized.
  • a height difference between label areas in an area pair composed of adjacent label areas is obtained in order from an area pair including the calculation start area, and (V) the discrete plural heights Among the threshold values, a height threshold value closest to the height difference of each region pair is set as a height offset value of a label region whose arrangement order is later in a pair of label regions constituting each region pair, and the sample
  • the height offset image may be generated by repeating the steps (I) to (V) for all line data of the original image.
  • This configuration shows an example of a procedure (step) for generating an offset image.
  • the mask image is superimposed on the height offset image, and for each of the regions surrounded by the boundary indicated by the mask image, the highest number of heights in the region are present.
  • the offset value may be set as the height offset value of the entire area.
  • the height offset image generating step line data along the tire circumferential direction of the sample original image is extracted, and the extracted line data is duplicated and shifted in the luminance height direction.
  • a duplication line is generated, and the duplication line is such that a curve indicating a low frequency component other than the concave / convex mark portion of the extracted line data and a curve showing the low frequency component of the concave / convex mark portion of the shifted duplication line are substantially continuous.
  • Data may be shifted, the shift amount at that time may be determined, and the shift amount may be used as the discrete height threshold.
  • the height dimension value of the uneven mark obtained from the design drawing of the sample tire or the mold CAD data, or the height dimension of the uneven mark of the sample tire Actual measurement values may be used as the discrete height thresholds.
  • the inspection work step further includes an interpolation step of interpolating height coordinate values in a mask range masked by the mask image used in the difference processing step in the image obtained in the difference processing step. It may be.
  • this method includes the above-described interpolation process, even if there is a mask range (mask area) larger than the uneven defect (Bulge / Dent) to be detected in the generated mask image, the unevenness to be detected It can suppress that a defect is overlooked.
  • the height coordinate value at two positions sandwiching the mask range is selected and linearly changed from one height coordinate value to the other height coordinate value.
  • Interpolation may be performed by assigning the obtained height coordinate value to the mask range.
  • an average obtained by selecting height coordinate values at two positions sandwiching the mask range and obtaining an average value of one height coordinate value and the other height coordinate value You may interpolate by assigning a height coordinate value to the mask range.
  • a window that is at least partly overlapped with the mask range, is shorter than the mask range, and extends in a direction along the mask range is provided, and the window is disposed in the mask range. While moving from one end to the other end, the maximum height coordinate value or the minimum height coordinate value of the position corresponding to the window is selected in the inspection image, and the selected height coordinate value is set in the mask range. You may interpolate by assigning.
  • the processing method for interpolating the mask range may be changed depending on the size (length) of the mask range. For example, when the mask range is small (short), the height coordinate value is interpolated using linear interpolation as in (9) or average interpolation as in (10) above, and the mask range is large (long). In this case, it is also possible to select to interpolate the height coordinate value by envelope interpolation as described in (11) above.
  • the tire shape inspection apparatus inspects a shape defect of the sidewall surface of the inspection tire using an image of the sidewall surface of the sample tire having the sidewall surface on which the concave and convex marks are formed.
  • the tire shape inspection device includes an imaging unit that captures a two-dimensional image of the sidewall surface, and a sample original image that is a two-dimensional image of the sidewall surface of the sample tire.
  • a mask image generation unit that detects and generates a mask image indicating the position of the boundary line; and a height of a remaining area in the sample original image excluding an area corresponding to the position of the boundary line indicated in the mask image
  • a height offset image generation unit that generates a height offset image indicating the height of the concave-convex mark, which is an image obtained by classifying the height using a plurality of discrete height thresholds, and The uneven mark is removed from the inspection image by subtracting the height offset image from the inspection image which is a two-dimensional image of the sidewall surface of the inspection tire.
  • a difference processing section for generating a convex removed image, on the basis of the irregularities removed image, and a, a shape defect inspection unit for inspecting the shape defect in the sidewall surface of the test tire.
  • This device can reliably inspect for irregularities on the sidewall surface without being affected by marks (characters, logos, patterns, etc.) that are normal irregularities present on the sidewall surface of the tire.
  • the imaging unit captures a line light irradiation unit that irradiates the side wall surface with one light cutting line, and an image (reflected light) of the line light irradiated on the sidewall surface.

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Abstract

Selon l'invention, des lignes de délimitation, qui sont les contours d'empreintes, sont détectées dans une image échantillon original, qui est une image bidimensionnelle de la surface latérale d'un pneu échantillon, et une image DE masque affichant l'emplacement des lignes de délimitation est générée. Puis, une image de décalage de hauteur, qui affiche la hauteur des empreintes, est générée par l'utilisation de plusieurs seuils de hauteur discrets pour classifier la hauteur des régions dans l'image échantillon original qui reste lorsque les régions correspondant aux emplacements des lignes de délimitation montrées sur l'image de masque sont exclues. Une image à partir de laquelle les indentations ont été extraites est alors générée par élimination des empreintes de l'image d'inspection, qui est une image bidimensionnelle de la paroi latérale d'un pneu à inspecter, par déduction de l'image de décalage de hauteur de l'image d'inspection. Les irrégularités de forme dans la paroi latérale du pneu à tester sont détectées sur la base de l'image extraite de l'indentation.
PCT/JP2010/007038 2009-12-07 2010-12-02 Dispositif et procede d'inspection la forme d'un pneu WO2011070750A1 (fr)

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EP10835677.5A EP2500686B1 (fr) 2009-12-07 2010-12-02 Dispositif et procédé d'inspection la forme d'un pneu
CN201080055305.2A CN103038601B (zh) 2009-12-07 2010-12-02 轮胎形状检查方法以及轮胎形状检查装置
US13/514,285 US9097514B2 (en) 2009-12-07 2010-12-02 Device and method for inspecting tyre shape

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JP2010068107A JP5371848B2 (ja) 2009-12-07 2010-03-24 タイヤ形状検査方法、及びタイヤ形状検査装置
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