Classifications

• • G06T5/70—
• • 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
  • 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
• • G06T3/10—
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/20—Image enhancement or restoration by the use of local operators
  • G06T5/30—Erosion or dilatation, e.g. thinning
• • 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
  • G01N21/952—Inspecting the exterior surface of cylindrical bodies or wires
• • 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
  • G06T2207/10—Image acquisition modality
  • G06T2207/10028—Range image; Depth image; 3D point clouds
• • 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
  • G06T2207/20—Special algorithmic details
  • G06T2207/20036—Morphological image processing
• • 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
• • 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 invention relates to the field of tire manufacturing and more particularly to the field of automatic inspection of the surface of a tire in order to establish a conformity diagnosis with respect to pre-established references.
• One of the steps of this process consists, in known manner, in acquiring the three-dimensional image of the surface of the tire. [003]
• the acquisition of this image is done using means based on the principle of optical triangulation, implementing for example a 2D sensor coupled to a laser-type lighting source.
• the topographic image of the tire surface is in fact a two-dimensional image, called a gray level, in which, at any point, ie at any pixel (x, y) of the image, a value is associated with f (x, y), called gray level, and usually between 0 and 255.
• This gray level value can usefully be coded on 8, or 16 bits for better dynamics.
• the gray level represents the altitude of this point relative to the surface. For 8-bit encoding, the value 255 (white) corresponds to the highest altitude, and the value 0 (black) corresponds to the lowest altitude.
• the pixels of the image are arranged in line and in columns.
• the method of processing the three-dimensional digital image of the outer surface of a tire according to the invention provides for the use of image processing methods using tools of the morphological type.
• the morphological erosion or dilation operations consist, for each point of an image, to find the minimum value or the maximum value of gray level of the neighboring points included inside a structuring element , of given shape and area, centered on the point to be analyzed and defining a neighborhood of this point. For an erosion the value at this point then becomes the minimum value, and for a dilation the value at this point becomes the maximum value.
• the combination of erosion followed by expansion is called opening, and the combination of dilation followed by erosion is called closure.
• the morphological gradient type operator delimits the zones of strong variation of relief, i. e. outline.
• a gray level value is assigned equal to the difference between the level value of gis obtained after an expansion and the value of gray level obtained after erosion.
• the method according to the invention After realizing the three-dimensional image of the surface of said tire in which each pixel of the image contains information relating to the elevation of the corresponding point of the surface to be inspected, the method according to the invention provides for a first transformation of the image of the surface by means of an opening then a closure, so as to recalculate the gray level of the pixels situated abnormally above or below the surface to be inspected.
• the gray level of each pixel is representative of the elevation of the point corresponding to the surface to be inspected.
• the morphological operator to perform the opening and closing is a square.
• a square whose width is between 8 and 15 pixels corresponding to a size slightly greater than the size of the non-measurement zones.
• a second transformation is then performed after having carried out the first transformation of the image of the surface, in which:
• the contour elements of the relief of the surface are determined using a morphological operator of the gradient type, followed by a thresholding for extracting the contours of the relief,
• the morphological operator used to determine the contours of the relief is a square.
• This method is preferably applied to the inspection of the external surface of the tire.
• FIGS. 1 to 5 The following description is based on FIGS. 1 to 5 in which:
• FIG. 1 represents a schematic view of a means of capturing the image of the surface of a tire
• FIG. 2 represents a view of the image of the external surface of a tire coming directly from the image capture means
• FIG. 3 represents the partial image of the outer surface after treatment using the first transformation
• FIG. 4 represents the image of the contours of the reliefs of the external surface of the tire
• FIG. 1 The acquisition of the image of the surface of a tire is illustrated in FIG. 1. This acquisition is effected by way of example using a slot light emitted by a laser. 1 and a camera 3 capable of capturing the 2D image of the illuminated surface. The camera is positioned so that its aiming direction makes a given angle with the beam emitted by the laser source. By triangulation, it is then possible to determine the coordinates of the relief element 2 relative to the support surface 4.
• the slot light is directed in an axial or radial direction perpendicular to the circumferential direction corresponding to the direction the rotation imposed on the tire to capture a complete image of its surface.
• Figure 2 shows the image from this seizure. We observe the presence of false measurement points, noted PFM, whose presence is particularly marked on the edges of the reliefs of the sculpture.
• This first treatment uses a morphological operator of square shape.
• the size of this operator is adjusted to the size of the defects that one seeks to filter. In this case, good results are obtained with an operator whose area of the square is of the order of a hundred pixels and whose side is wide of ten pixels.
• FIG. 1 is a partial view of the image of the tire surface after the completion of the first treatment.
• this residual of abnormal values is preferentially concentrated or level zones corresponding to a strong variation of the relief.
• Figure 4 illustrates the result of this operation which detaches from the bottom of the image the only values of the contours of the reliefs of the surface.
• the second treatment is intended to reduce the false measurement values in the narrow band representing the contours of the reliefs. To do this, we assign to each pixel of this area, the value of gray level equal to the value obtained after the first transformation.
• Figure 5 illustrates the result obtained after the implementation of the first and second treatment. It is observed that the false measurement points have completely disappeared and are no longer likely to disturb the digital image processing in order to perform the inspection of the conformity of the surface of the tire.
• this method is particularly applicable to areas showing strong variations of relief and therefore to the external parts of the tire surface.
• this same method it is not excluded to use this same method to refine the images of the inner part of the tire when the latter comprise relief elements such as streaks.

Applications Claiming Priority (2)

Publications (1)

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Family Applications (1)

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• 2011
  • 2011-04-18 FR FR1153345A patent/FR2974219A1/fr not_active Withdrawn
• 2012
  • 2012-03-21 BR BR112013024106A patent/BR112013024106A2/pt not_active IP Right Cessation
  • 2012-03-21 EP EP12710502.1A patent/EP2700050A1/de not_active Withdrawn
  • 2012-03-21 US US14/112,448 patent/US9230318B2/en not_active Expired - Fee Related
  • 2012-03-21 CN CN201280019364.3A patent/CN103649989B/zh not_active Expired - Fee Related
  • 2012-03-21 JP JP2014505558A patent/JP2014517265A/ja active Pending
  • 2012-03-21 WO PCT/EP2012/055016 patent/WO2012143198A1/fr active Application Filing

Non-Patent Citations (1)

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