WO2022111626A1 - 基于线激光的胎纹沟槽深度测量方法、装置及计算设备 - Google Patents

基于线激光的胎纹沟槽深度测量方法、装置及计算设备 Download PDF

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WO2022111626A1
WO2022111626A1 PCT/CN2021/133462 CN2021133462W WO2022111626A1 WO 2022111626 A1 WO2022111626 A1 WO 2022111626A1 CN 2021133462 W CN2021133462 W CN 2021133462W WO 2022111626 A1 WO2022111626 A1 WO 2022111626A1
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point cloud
laser
line
cloud data
image
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PCT/CN2021/133462
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English (en)
French (fr)
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王维林
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深圳市道通科技股份有限公司
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Publication of WO2022111626A1 publication Critical patent/WO2022111626A1/zh

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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
    • G01B11/22—Measuring arrangements characterised by the use of optical techniques for measuring depth

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  • the present application relates to the technical field of vehicles, in particular to a method, device and computing device for measuring the depth of a tread groove based on a line laser.
  • the traditional tire tread wear measurement is based on the observation of the wear indicator line, coin detection, vernier caliper and other measurement methods. These methods have one characteristic: insufficient precision, inconvenient operation, and many factors affected by the measurement person. Monocular laser measurement can be used for tread depth detection, which can solve the above-mentioned problem of insufficient measurement. However, how to improve the measurement accuracy and support the application scenarios of measuring tires with various patterns will be a challenging task.
  • embodiments of the present invention provide a method, device, and computing device for measuring the depth of a sipe groove based on a line laser, which overcome the above problems or at least partially solve the above problems.
  • a method for measuring the depth of a sipe groove based on a line laser comprising: acquiring a laser line image obtained by projecting a laser line onto the surface of the tire to be tested, and analyzing the The pixel coordinates of the laser line in the laser line image are rotated to obtain the original 2D point cloud image of the laser line in the laser coordinate system; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data.
  • the straight line fitted by the pixel points on the tread surface is parallel to the horizontal X-axis; the gradient analysis method is applied to locate the tread groove according to the point cloud data; Measurements or unilateral measurements calculate the depth of the sipe.
  • rotating the pixel coordinates of the laser line in the laser line image to obtain the original 2D point cloud image of the laser line in the laser coordinate system includes: obtaining the original 2D point cloud image of the laser line in the laser coordinate system Obtain the pixel coordinates (u, v) of the laser line from the line image; convert the pixel coordinates (u, v) into camera coordinates (xc, yc, zc) through projective transformation; convert the camera coordinates (xc, yc, zc) yc, zc) are rotated and transformed into laser coordinates (xL, yL, zL), where the abscissa xL is the direction of the laser line, the ordinate yL is the projection direction of the laser line, and the vertical coordinate zL is the normal vector of the laser light knife plane; The 2D coordinates (xL, yL) in the laser coordinates (xL, yL, zL) are used as the original 2D point cloud image of the laser line
  • the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data, and a straight line fitted according to the pixel points located on the tread surface in the point cloud data is obtained.
  • Parallel to the horizontal X-axis including: performing straight line fitting on the first pixel point set after the edge pixel points are removed from the original 2D point cloud image to obtain a first straight line, and calculating the rotation of the first straight line to the horizontal X
  • the first rotation angle required for axis-parallel rotate the first pixel point set by the first rotation angle to obtain a first point cloud set; obtain the rotation required to eliminate the influence of the tread groove according to the first point cloud set
  • the second rotation angle of the first point cloud set, and the second point cloud set obtained by excluding the sipe part points in the first point cloud set and rotating the second rotation angle; according to the second point cloud set, the elimination
  • the interference point affects the third rotation angle of the required rotation; the pixel points in the original 2D point cloud image are respectively rotated by the first rotation angle
  • the obtaining, according to the first point cloud set, the second rotation angle required to eliminate the influence of the sipe includes: arranging the pixel points in the first point cloud set according to the following steps: The ordinates are arranged in ascending order, and the preset ratio of pixels with smaller ordinates is reserved to form a second set of pixels; a second straight line is obtained by performing straight line fitting according to the second set of pixels; and the rotation of the second straight line is calculated to said second rotation angle required to be parallel to the horizontal X axis.
  • the obtaining, according to the second set of point clouds, the third rotation angle required to eliminate the influence of the interference point includes: performing line fitting according to the second set of pixel points, and calculating the Euclidean distance from the pixel points in the second pixel point set to the fitted straight line; keep the pixel points whose Euclidean distance is within the preset threshold to form a third pixel point set; perform straight line fitting according to the third point cloud set Obtain a third straight line; calculate the third rotation angle required to rotate the third straight line to be parallel to the horizontal X-axis.
  • applying a gradient analysis method to sipe groove positioning according to the point cloud data includes: performing sampling calculation according to the point cloud data, and obtaining a gradient map of the point cloud data; The gradients continuously changing in one direction are integrated according to the gradient map, only the crests and troughs in a local range are retained, and the sipe is positioned according to the crests and the troughs.
  • the calculation of the depth of the sipe by applying bilateral measurement or unilateral measurement according to the point cloud data includes: in the point cloud data, moving toward the edge of the sipe The left and right sides are respectively searched for a certain distance, and each point is taken to form a straight line as a reference line; the distance from the bottom of the sipe groove to the reference line is calculated as the depth of the sipe groove.
  • the calculating the depth of the sipe by applying bilateral measurement or unilateral measurement according to the original 2D point cloud image includes: according to the point cloud data, in the sipe Searching for line segments with preset lengths respectively within the preset distance range to the left and right of the edge point to obtain a first reference line segment and a second reference line segment; calculating the Euclidean distance between the first reference line segment and the second reference line segment that are parallel to each other as The depth of the sipe.
  • a line laser-based sipe depth measurement device comprising: a point cloud image acquisition unit for acquiring a laser line projected onto the tire surface to be tested. laser line image, and rotate the pixel coordinates of the laser line in the laser line image to obtain the original 2D point cloud image of the laser line in the laser coordinate system; a parallel rotation unit is used to convert the original 2D point The pixel points in the cloud image are rotated in parallel to obtain point cloud data, so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis; the groove positioning unit is used for according to the point Gradient analysis method is applied to the cloud data to locate the sipe; the depth measurement unit is used to calculate the depth of the sipe according to the point cloud data by applying bilateral measurement or unilateral measurement.
  • a computing device including: a processor, a memory, a communication interface, and a communication bus, and the processor, the memory, and the communication interface communicate with each other through the communication bus. communication between;
  • the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the steps of the above-mentioned method for measuring the groove depth based on a line laser.
  • the laser line image obtained by projecting the laser line onto the surface of the tested tire is obtained, and the pixel coordinates of the laser line in the laser line image are rotated to obtain the laser line in the laser coordinate system.
  • the original 2D point cloud image; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis;
  • the gradient analysis method is applied to locate the tread groove; the depth of the tread groove is calculated by applying bilateral measurement or unilateral measurement according to the point cloud data, which can support various tread groove depth measurements. , High measurement accuracy, fast measurement speed, convenient operation, bilateral measurement can reach 0.1mm measurement accuracy, unilateral measurement can reach 0.3mm measurement accuracy.
  • FIG. 1 shows a schematic flowchart of a method for measuring the depth of a sipe groove based on a line laser provided by an embodiment of the present invention
  • FIG. 2 shows a schematic diagram of a handheld sipe depth measuring device based on a line laser-based sipe depth measuring method provided by an embodiment of the present invention
  • Fig. 3 shows the original 2D point cloud image of the line laser-based sipe depth measurement method provided by the embodiment of the present invention
  • Fig. 4 shows the gradient map obtained from the original 2D point cloud image in Fig. 3;
  • Fig. 5 shows the gradient effect graph after integrating according to the gradient graph in Fig. 4;
  • FIG. 6 shows a schematic diagram of the sipe depth analysis of the method for measuring the sipe depth based on a line laser provided by an embodiment of the present invention
  • FIG. 7 shows a schematic diagram of a tire suitable for unilateral measurement of the method for measuring sipe depth based on a line laser provided by an embodiment of the present invention
  • FIG. 8 shows a schematic diagram of a unilateral measurement of a method for measuring the depth of a sipe groove based on a line laser provided by an embodiment of the present invention
  • FIG. 9 shows a schematic structural diagram of a device for measuring the depth of a sipe groove based on a line laser provided by an embodiment of the present invention.
  • FIG. 10 shows a schematic structural diagram of a computing device provided by an embodiment of the present invention.
  • FIG. 1 shows a schematic flowchart of a method for measuring the depth of a sipe groove based on a line laser provided by an embodiment of the present invention. The method is performed by an electronic device. As shown in Figure 1, the measurement method of sipe depth based on line laser includes:
  • Step S11 Acquire a laser line image obtained by projecting the laser line onto the surface of the tested tire, and rotate the pixel coordinates of the laser line in the laser line image to obtain the original 2D image of the laser line in the laser coordinate system Point cloud map.
  • the electronic device may be a hand-held tread groove depth measurement device, and may also be used in other system solutions other than hand-held devices, including a floor-standing tread measurement solution, a PC system measurement solution, and the like.
  • the hand-held tread groove depth measurement equipment includes a base, a line laser, a camera, a host, a display system, a battery, and a body.
  • the laser and the camera are installed on the same axis, but there is a certain distance.
  • the projection direction of the laser line and the Z-axis direction of the camera form a preset angle. Preferably, it is generally 25 to 30 degrees.
  • the tire When the laser line is projected, the tire can be on the bottom, and the laser can be on the top to project the laser line to the tire surface, and the tread groove is upward. It can also be flipped 180 degrees vertically, the tire surface is on top, the laser is on the bottom and the laser line is projected to the tire surface, and the tread grooves are facing down.
  • the choice of laser can support other wavelengths of lasers except 520nm, such as 650nm red laser.
  • the laser is turned on, the laser line is projected onto the measured object, and the camera captures the image of the laser line.
  • step S11 the laser line image captured by the camera is obtained, the pixel coordinates (u, v) of the laser line are obtained from the laser line image, and the pixel coordinates (u, v) are converted into camera coordinates (x c , y c , z c ), rotate the camera coordinates (x c , y c , z c ) into laser coordinates (x L , y L , z L ), where x L is the direction of the laser line, and y L is The projection direction of the laser line, the vertical coordinate z L is the normal vector of the laser light knife plane.
  • the base is attached to the surface of the tire, and the laser is projected almost perpendicular to the surface of the tire.
  • the 2D coordinates (x L , y L ) in L ) are used as the original 2D point cloud image of the laser line in the laser coordinate system, so as to analyze the depth information of the tread pattern in the 2D coordinate system.
  • Step S12 Rotate the pixel points in the original 2D point cloud image in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X axis.
  • the original 2D point cloud of the laser line on the tire surface in the laser coordinate system is shown in FIG. 3
  • the horizontal coordinate is the position x L of the laser line on the tire surface
  • the longitudinal coordinate is the projection distance y L of the laser line .
  • the methods of removing invalid treads include: the depth of the tread groove is too small, which is generally caused by tire miscellaneous treads; the tread groove is incomplete, usually caused by laser occlusion. If the bottom area of the sipe (the y L value is almost the same) is smaller than a certain width, the sipe is invalid.
  • a first straight line is obtained by performing straight line fitting according to the first pixel point set after excluding edge pixels in the original 2D point cloud image, and the rotation of the first straight line to the horizontal X axis is calculated.
  • Parallel to the required first rotation angle rotate the first pixel point set by the first rotation angle to obtain a first point cloud set.
  • the consistency of the pixels at the edge and the pixels on the surface is too different. If they are not near the same straight line, the parallel rotation operation will be greatly affected.
  • the rotation is calculated, the pixels at the edge will be deleted first.
  • Deletion method search for a distance from the two edges to the middle, and the position of the part where the consistency begins to become relatively close, then remove the pixels from the point cloud edge to obtain the first set of pixels. Fit a straight line with the pixels in the first pixel point set after removing edge pixels, and use the least squares method to fit the straight line to obtain the first straight line, and calculate the inclination angle ⁇ of the first straight line, that is, the first straight line. Rotate the straight line to the first rotation angle ⁇ required to be parallel to the horizontal X-axis, rotate the pixels in the first pixel point set by the first rotation angle ⁇ to obtain the first point cloud set, and keep the first point cloud set roughly parallel. On the horizontal X axis, the first point cloud set S is output.
  • the pixel points in the first point cloud set are arranged in ascending order according to the ordinate, and the pixel points of the preset ratio with the smaller ordinate are reserved to form the second pixel point set S1.
  • a third rotation angle required to eliminate the influence of the interference point is obtained according to the second point cloud set. Specifically, perform line fitting according to the second set of pixel points, and calculate the Euclidean distance from the pixel points in the second set of pixel points to the fitted line; retain the pixels whose Euclidean distance is within a preset threshold to form A third pixel point set S3; a third straight line is obtained by performing straight line fitting according to the third point cloud set S3; and the third rotation angle ⁇ required to rotate the third straight line to be parallel to the horizontal X-axis is calculated.
  • the pixel points in the original 2D point cloud image are respectively rotated by the first rotation angle ⁇ , the second rotation angle ⁇ and the third rotation angle ⁇ to obtain the point cloud data.
  • the pixels in the original 2D point cloud image are rotated by the first rotation angle ⁇ to make the overall trend of the rotated pixels parallel to the horizontal X-axis, and the effect of the tread groove can be eliminated by rotating the second rotation angle ⁇ .
  • rotating the third rotation angle ⁇ can further eliminate the influence of the interference points generated by the twill part of the tire, and the finally obtained point cloud data is almost parallel to the horizontal X-axis, which can make the subsequent gradient calculation more accurate and in-depth analysis more convenient.
  • Step S13 applying the gradient analysis method to locate the tread groove according to the point cloud data.
  • a gradient analysis method is applied to locate the sipe groove according to the point cloud data. Specifically, sampling calculation is performed according to the point cloud data, and a gradient map of the point cloud data is obtained; the gradients continuously changing in one direction are integrated according to the gradient map, and only the peaks and troughs in the local range are retained, and according to the The wave crests and the wave troughs perform sipe positioning. For the application scenario of tires, it can be calculated according to the spacing of 0.3mm.
  • the calculation method is the adjacent points P1(x L1 , y L1 ), P2 (x L2 , y L2 ), and calculated according to the following formula:
  • FIG. 4 is a gradient map obtained by applying the above calculation method according to the original 2D point cloud image in FIG. 3 .
  • the three peaks represent the left edge positions of the three sipes, where yL changes most drastically; similarly, the three troughs represent the right sides of the three sipes along, where yL also changes most dramatically.
  • the gradients continuously changing in one direction are integrated, and only the wave crests and wave troughs in a local range are retained, and the sipe grooves are positioned according to the wave crests and the wave troughs.
  • Each adjacent wave crest and wave trough represents a sipe groove, and the integrated gradient effect is shown in Figure 5.
  • the peaks and troughs When locating the sipe grooves, the peaks and troughs generally appear in pairs. If the peaks and troughs are lower than the preset threshold, such sipe grooves will be ignored, because the interference of the tire patterns or point cloud data will also occur. Localized wave fronts and valleys are generated in the gradient map. If the peaks and troughs exceed the preset threshold, the oblique line from the peak to the trough represents a sipe, the peaks and troughs represent the left and right edges of the sipe, respectively, and the gap between the peaks and the troughs represents the sipe bottom area.
  • Step S14 Calculate the depth of the sipe groove by applying bilateral measurement or unilateral measurement according to the point cloud data.
  • the sipe groove after the positioning of the sipe groove is completed, a certain distance is searched for the left and right sides of the sipe groove edge in the point cloud data, and each point is taken to form a straight line as a reference line; calculate the sipe groove The distance from the bottom to the reference line is the depth of the sipe. Specifically, according to the depth analysis of the sipe groove as shown in FIG.
  • a certain distance is searched for the left and right sides of the sipe groove edge, and two point cloud sets are obtained: the left point cloud set L and the right side
  • For the point cloud set R take a point from each of the two point cloud sets and connect them to form a straight line as a reference line, and calculate the distance h from the bottom of the sipe groove to the reference line, which is the depth of the sipe groove.
  • the pixels selected in the left point cloud set L and the right point cloud set R meet the first preset condition: the distance between the pixel point at the bottom of the sipe and the reference line is the largest, or, in the left point cloud set L and In the point cloud set R on the right, there are no more than 3 pixels below the reference line.
  • the groove depth due to interference or data jitter, a single point in the groove area G is used to calculate the groove depth. The fluctuation is too large, and the average optimization algorithm is used to calculate the groove depth. Specifically, the distance d from all pixels in the sipe area G to the reference line is calculated, the calculated distances are sorted in descending order, and the largest 10% of the distance values are averaged as the sipe depth.
  • the bilateral measurement is used when the reference position can be found on both sides of the sipe.
  • the tread grooves of some tires cannot find two reference positions, only one reference position can be found, such as the off-road tire shown in Figure 7, at this time, the unilateral measurement method needs to be used.
  • the unilateral measurement method is shown in Figure 8. According to the point cloud data, the line segments of the preset length are respectively searched within the preset distance range on the left and right of the pixel point on the edge of the sipe groove to obtain the first reference line segment and the second reference line segment; if The first reference line segment and the second reference line segment are substantially parallel, and the Euclidean distance between the mutually parallel first reference line segment and the second reference line segment is calculated as the tread depth.
  • the second preset condition needs to be satisfied: within the preset length range of the line segment, the point cloud data are all near the line segment, the line segment is within a certain range of edge pixels, and the line segment length needs to meet a certain the threshold value.
  • the method for determining that the first reference line segment and the second reference line segment are parallel may be determined according to the fact that the slope of the line segment is close to or the included angle is close to 0.
  • the line laser-based sipe depth measurement method of the embodiment of the present invention has high measurement accuracy, fast measurement speed, convenient operation, wide coverage of tires, and supports most sipe groove depth measurements. Among them, bilateral measurement can achieve a measurement accuracy of 0.1mm, and unilateral measurement can achieve a measurement accuracy of 0.3mm.
  • the laser line image obtained by projecting the laser line onto the surface of the tested tire is obtained, and the pixel coordinates of the laser line in the laser line image are rotated to obtain the laser line in the laser coordinate system.
  • the original 2D point cloud image; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis;
  • the gradient analysis method is applied to locate the tread groove; the depth of the tread groove is calculated by applying bilateral measurement or unilateral measurement according to the point cloud data, which can support various tread groove depth measurements. , High measurement accuracy, fast measurement speed and easy operation.
  • FIG. 9 shows a schematic structural diagram of a device for measuring the depth of a sipe groove based on a line laser according to an embodiment of the present invention.
  • the line laser-based sipe depth measuring device is applied to electronic equipment.
  • the electronic device can be a hand-held tread groove depth measurement device, and can also be used for other system solutions other than hand-held devices, including a floor-standing tread measurement solution, a PC system measurement solution, and the like.
  • the electronic equipment includes a base, a line laser, a camera, a host, a display system, a battery, a fuselage, etc.
  • the line laser-based tread groove depth measurement device is specifically arranged in the host.
  • the line laser-based sipe depth measurement device includes: a point cloud image acquisition unit 901 , a parallel rotation unit 902 , a groove positioning unit 903 and a depth measurement unit 904 . in:
  • the point cloud image acquisition unit 901 is used to acquire the laser line image obtained by projecting the laser line onto the surface of the tested tire, and rotate the pixel coordinates of the laser line in the laser line image to obtain the laser line in the laser coordinate system.
  • the parallel rotation unit 902 is used to parallel rotate the pixel points in the original 2D point cloud image to obtain point cloud data and fit the pixel points located on the tread surface according to the point cloud data.
  • the straight line is parallel to the horizontal X axis;
  • the groove positioning unit 903 is used for applying the gradient analysis method to locate the sipe groove according to the point cloud data;
  • the depth measuring unit 904 is used for applying bilateral measurement or unilateral measurement according to the point cloud data. Measure the depth of the sipe.
  • the point cloud image obtaining unit 901 is configured to: obtain the pixel coordinates (u, v) of the laser line from the laser line image; Transform into camera coordinates (x c , y c , z c ); rotate the camera coordinates (x c , y c , z c ) into laser coordinates (x L , y L , z L ), where, The abscissa x L is the direction of the laser line, the ordinate y L is the projection direction of the laser line, and the vertical coordinate z L is the normal vector of the laser light knife plane; select the 2D in the laser coordinates (x L , y L , z L ) The coordinates (x L , y L ) serve as the original 2D point cloud image of the laser line in the laser coordinate system.
  • the parallel rotation unit 902 is configured to: perform line fitting according to the first set of pixel points in the original 2D point cloud image after removing edge pixels to obtain a first straight line, and calculate the first straight line. Rotate a line to the first rotation angle required to be parallel to the horizontal X axis, and rotate the first pixel point set by the first rotation angle to obtain a first point cloud set; obtain and eliminate the first point cloud set according to the first set of points.
  • the sipe affects the second rotation angle required to rotate, and obtains a second point cloud set obtained by excluding some points of the sipe from the first point cloud set and rotating the second rotation angle;
  • the second point cloud set obtains the third rotation angle required to eliminate the influence of the interference point; rotate the pixel points in the original 2D point cloud image by the first rotation angle, the second rotation angle and the third rotation angle respectively.
  • Three rotation angles are obtained to obtain the point cloud data.
  • the parallel rotation unit 902 is used for: arranging the pixels in the first point cloud set in ascending order according to the ordinate, and retaining the pixels of the preset ratio with the smaller ordinate to form the first point cloud set.
  • a set of two pixel points; a second straight line is obtained by performing straight line fitting according to the second set of pixel points; and the second rotation angle required to rotate the second straight line to be parallel to the horizontal X-axis is calculated.
  • the parallel rotation unit 902 is configured to: perform straight line fitting according to the second set of pixel points, and calculate the Euclidean distance from the pixel points in the second set of pixel points to the fitted straight line; The pixel points whose Euclidean distance is within the preset threshold form a third pixel point set; perform straight line fitting according to the third point cloud set to obtain a third straight line; calculate and rotate the third straight line to a position parallel to the horizontal X-axis. the required third rotation angle.
  • the groove positioning unit 903 is configured to: perform sampling calculation according to the point cloud data, and obtain a gradient map of the point cloud data; Integration, retaining only the crests and troughs in a local range, and sipe positioning based on the crests and troughs.
  • the depth measurement unit 904 is used to: search for a certain distance to the left and right sides of the sipe edge in the point cloud data, and take each point to form a straight line as a reference line; calculate the sipe The distance from the bottom of the groove to the reference line is the depth of the sipe.
  • the depth measurement unit 904 is configured to: according to the point cloud data, search for line segments with preset lengths respectively within a preset distance range to the left and right of the edge point of the sipe, to obtain the first reference line segment and the first reference line segment and the first reference line segment and the first reference line segment.
  • Two reference line segments; the Euclidean distance between the first reference line segment and the second reference line segment that are parallel to each other is calculated as the tread depth.
  • the laser line image obtained by projecting the laser line onto the surface of the tested tire is obtained, and the pixel coordinates of the laser line in the laser line image are rotated to obtain the laser line in the laser coordinate system.
  • the original 2D point cloud image; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis;
  • the gradient analysis method is applied to locate the tread groove; the depth of the tread groove is calculated by applying bilateral measurement or unilateral measurement according to the point cloud data, which can support various tread groove depth measurements. , High measurement accuracy, fast measurement speed and easy operation.
  • An embodiment of the present invention provides a non-volatile computer storage medium, where the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the line laser-based sipe in any of the above method embodiments Groove depth measurement method.
  • Executable instructions can specifically be used to cause the processor to perform the following operations:
  • the gradient analysis method is applied to locate the tread groove
  • the depth of the sipe is calculated from the point cloud data using bilateral or unilateral measurements.
  • executable instructions cause the processor to perform the following operations:
  • pixel coordinates (u, v) are transformed into camera coordinates (x c , y c , z c ) through projective transformation;
  • the 2D coordinates (x L , y L ) in the laser coordinates (x L , y L , z L ) are selected as the original 2D point cloud image of the laser line in the laser coordinate system.
  • executable instructions cause the processor to perform the following operations:
  • a first straight line is obtained by performing straight line fitting according to the first pixel point set after removing edge pixels in the original 2D point cloud image, and the first rotation required to rotate the first straight line to be parallel to the horizontal X-axis is calculated angle, rotating the first pixel point set by the first rotation angle to obtain a first point cloud set;
  • the point cloud data is obtained by rotating the pixel points in the original 2D point cloud image by the first rotation angle, the second rotation angle and the third rotation angle respectively.
  • executable instructions cause the processor to perform the following operations:
  • executable instructions cause the processor to perform the following operations:
  • executable instructions cause the processor to perform the following operations:
  • the gradients continuously changing in one direction are integrated according to the gradient map, only the crests and troughs in a local range are retained, and the sipe is positioned according to the crests and the troughs.
  • executable instructions cause the processor to perform the following operations:
  • the distance from the bottom of the sipe to the reference line is calculated as the depth of the sipe.
  • executable instructions cause the processor to perform the following operations:
  • line segments with preset lengths are respectively searched within a preset distance range to the left and right of the edge point of the sipe groove to obtain a first reference line segment and a second reference line segment;
  • the Euclidean distance between the first reference line segment and the second reference line segment that are parallel to each other is calculated as the depth of the tread.
  • the laser line image obtained by projecting the laser line onto the surface of the tested tire is obtained, and the pixel coordinates of the laser line in the laser line image are rotated to obtain the laser line in the laser coordinate system.
  • the original 2D point cloud image; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis;
  • the gradient analysis method is applied to locate the tread groove; the depth of the tread groove is calculated by applying bilateral measurement or unilateral measurement according to the point cloud data, which can support various tread groove depth measurements. , High measurement accuracy, fast measurement speed and easy operation.
  • An embodiment of the present invention provides a line laser-based sipe depth measurement device, which is used to execute the above-mentioned line laser-based sipe depth measurement method.
  • An embodiment of the present invention provides a computer program, which can be invoked by a processor to cause a base station device to execute the line laser-based sipe depth measurement method in any of the above method embodiments.
  • An embodiment of the present invention provides a computer program product, where the computer program product includes a computer program stored on a computer storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, causes the computer to The line laser-based sipe depth measurement method in any of the above method embodiments is performed.
  • Executable instructions can specifically be used to cause the processor to perform the following operations:
  • the gradient analysis method is applied to locate the tread groove
  • the depth of the sipe is calculated from the point cloud data using bilateral or unilateral measurements.
  • executable instructions cause the processor to perform the following operations:
  • pixel coordinates (u, v) are transformed into camera coordinates (x c , y c , z c ) through projective transformation;
  • the 2D coordinates (x L , y L ) in the laser coordinates (x L , y L , z L ) are selected as the original 2D point cloud image of the laser line in the laser coordinate system.
  • executable instructions cause the processor to perform the following operations:
  • a first straight line is obtained by performing straight line fitting according to the first pixel point set after removing edge pixels in the original 2D point cloud image, and the first rotation required to rotate the first straight line to be parallel to the horizontal X-axis is calculated angle, rotating the first pixel point set by the first rotation angle to obtain a first point cloud set;
  • the point cloud data is obtained by rotating the pixel points in the original 2D point cloud image by the first rotation angle, the second rotation angle and the third rotation angle respectively.
  • executable instructions cause the processor to perform the following operations:
  • executable instructions cause the processor to perform the following operations:
  • executable instructions cause the processor to perform the following operations:
  • the gradients continuously changing in one direction are integrated according to the gradient map, and only the crests and troughs in a local range are retained, and the sipe is positioned according to the crests and the troughs.
  • executable instructions cause the processor to perform the following operations:
  • the distance from the bottom of the sipe to the reference line is calculated as the depth of the sipe.
  • executable instructions cause the processor to perform the following operations:
  • line segments with preset lengths are respectively searched within a preset distance range to the left and right of the edge point of the sipe groove to obtain a first reference line segment and a second reference line segment;
  • the Euclidean distance between the first reference line segment and the second reference line segment that are parallel to each other is calculated as the depth of the tread.
  • the laser line image obtained by projecting the laser line onto the surface of the tested tire is obtained, and the pixel coordinates of the laser line in the laser line image are rotated to obtain the laser line in the laser coordinate system.
  • the original 2D point cloud image; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis;
  • the gradient analysis method is applied to locate the tread groove; the depth of the tread groove is calculated by applying bilateral measurement or unilateral measurement according to the point cloud data, which can support various tread groove depth measurements. , High measurement accuracy, fast measurement speed and easy operation.
  • FIG. 10 shows a schematic structural diagram of a computing device provided by an embodiment of the present invention.
  • the specific embodiment of the present invention does not limit the specific implementation of the device.
  • the computing device may include: a processor (processor) 1002 , a communications interface (Communications Interface) 1004 , a memory (memory) 1006 , and a communication bus 1008 .
  • processor processor
  • communications interface Communication Interface
  • memory memory
  • communication bus 1008
  • the processor 1002 , the communication interface 1004 , and the memory 1006 communicate with each other through the communication bus 1008 .
  • the communication interface 1004 is used to communicate with network elements of other devices such as clients or other servers.
  • the processor 1002 is configured to execute the program 1010, and specifically may execute the relevant steps in the above embodiments of the method for measuring the depth of a sipe groove based on a line laser.
  • the program 1010 may include program code including computer operation instructions.
  • the processor 1002 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or each integrated circuit configured to implement an embodiment of the present invention.
  • One or each processor included in the device may be the same type of processor, such as one or each CPU; or may be different types of processors, such as one or each CPU and one or each ASIC.
  • the memory 1006 is used to store the program 1010 .
  • Memory 1006 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.
  • the program 1010 can specifically be used to cause the processor 002 to perform the following operations:
  • the gradient analysis method is applied to locate the tread groove
  • the depth of the sipe is calculated from the point cloud data using bilateral or unilateral measurements.
  • program 1010 causes the processor to perform the following operations:
  • pixel coordinates (u, v) are transformed into camera coordinates (x c , y c , z c ) through projective transformation;
  • the 2D coordinates (x L , y L ) in the laser coordinates (x L , y L , z L ) are selected as the original 2D point cloud image of the laser line in the laser coordinate system.
  • program 1010 causes the processor to perform the following operations:
  • a first straight line is obtained by performing straight line fitting according to the first pixel point set after removing edge pixels in the original 2D point cloud image, and the first rotation required to rotate the first straight line to be parallel to the horizontal X-axis is calculated angle, rotating the first pixel point set by the first rotation angle to obtain a first point cloud set;
  • the point cloud data is obtained by rotating the pixel points in the original 2D point cloud image by the first rotation angle, the second rotation angle and the third rotation angle respectively.
  • program 1010 causes the processor to perform the following operations:
  • program 1010 causes the processor to perform the following operations:
  • program 1010 causes the processor to perform the following operations:
  • the gradients continuously changing in one direction are integrated according to the gradient map, only the crests and troughs in a local range are retained, and the sipe is positioned according to the crests and the troughs.
  • program 1010 causes the processor to perform the following operations:
  • the distance from the bottom of the sipe to the reference line is calculated as the depth of the sipe.
  • program 1010 causes the processor to perform the following operations:
  • line segments with preset lengths are respectively searched within a preset distance range to the left and right of the edge point of the sipe groove to obtain a first reference line segment and a second reference line segment;
  • the Euclidean distance between the first reference line segment and the second reference line segment that are parallel to each other is calculated as the depth of the tread.
  • the laser line image obtained by projecting the laser line onto the surface of the tested tire is obtained, and the pixel coordinates of the laser line in the laser line image are rotated to obtain the laser line in the laser coordinate system.
  • the original 2D point cloud image; the pixel points in the original 2D point cloud image are rotated in parallel to obtain point cloud data so that the straight line fitted according to the pixel points located on the tread surface in the point cloud data is parallel to the horizontal X-axis;
  • the gradient analysis method is applied to locate the tread groove; the bilateral measurement or unilateral measurement is applied to calculate the tread groove depth according to the point cloud data, which can support various tread groove depth measurements, and the measurement accuracy High, fast measurement speed, easy to operate.
  • modules in the device in the embodiment can be adaptively changed and arranged in one or more devices different from the embodiment.
  • the modules or units or components in the embodiments may be combined into one module or unit or component, and they may be divided into multiple sub-modules or sub-units or sub-assemblies. All features disclosed in this specification (including accompanying claims, abstract and drawings) and any method so disclosed may be employed in any combination unless at least some of such features and/or procedures or elements are mutually exclusive. All processes or units of equipment are combined.
  • Each feature disclosed in this specification may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

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Abstract

本发明实施例涉及车辆技术领域，公开了一种基于线激光的胎纹沟槽深度测量方法、装置及计算设备，该方法包括：获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。通过上述方式，本发明实施例能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便。

Description

基于线激光的胎纹沟槽深度测量方法、装置及计算设备
本申请要求于2020年12月1日提交中国专利局、申请号为202011371022.0、申请名称为“基于线激光的胎纹沟槽深度测量方法、装置及计算设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及车辆技术领域，具体涉及一种基于线激光的胎纹沟槽深度测量方法、装置及计算设备。
背景技术
传统的轮胎花纹磨损测量基于观察磨损指示线、硬币探测、游标卡尺等测量方法，这些方法都有一个特点：精度不足、操作不便、受测量人影响因素多。单目激光测量可用于胎纹深度检测，可解决上述的测量不足问题。但如何提高测量精度，支持测量多种花纹轮胎的应用场景，将是一项比较有挑战性的工作。
发明内容
鉴于上述问题，本发明实施例提供了一种基于线激光的胎纹沟槽深度测量方法、装置及计算设备，克服了上述问题或者至少部分地解决了上述问题。
根据本发明实施例的一个方面，提供了一种基于线激光的胎纹沟槽深度测量方法，所述方法包括：获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
在一种可选的方式中，所述对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图，包括：从所述激光线图像中获取所述激光线的像素坐标(u，v)；根据所述像素坐标(u，v)通过投影变换转换成相机坐标(xc，yc，zc)；将所述相机坐标(xc，yc，zc)进行旋转变换成激光器坐标(xL，yL，zL)，其中，横坐标xL为激光线方向，纵坐标yL为激光线的投射方向，垂直坐标zL为激光光刀平面的法向量；选取所述激光器坐标(xL，yL，zL)中的2D坐标(xL，yL)作为所述激光线在激光坐标系中的所述原始2D点云图。
在一种可选的方式中，所述将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴，包括：根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X 轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合；根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合；根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度；将所述原始2D点云图中的像素点分别旋转所述第一旋转角度、所述第二旋转角度以及所述第三旋转角度，得到所述点云数据。
在一种可选的方式中，所述根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，包括：将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合；根据所述第二像素点集合进行直线拟合得到第二直线；计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度。
在一种可选的方式中，所述根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度，包括：根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合；根据所述第三点云集合进行直线拟合得到第三直线；计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度。
在一种可选的方式中，所述根据所述点云数据应用梯度分析方法进行胎纹沟槽定位，包括：根据所述点云数据进行采样计算，获取所述点云数据的梯度图；根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。
在一种可选的方式中，所述根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度，包括：所述点云数据中向所述胎纹沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；计算所述胎纹沟槽底部到所述参考线的距离即为所述胎纹沟槽的深度。
在一种可选的方式中，所述根据所述原始2D点云图应用双边测量或单边测量计算所述胎纹沟槽的深度，包括：根据所述点云数据在所述胎纹沟槽边沿点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为所述胎纹沟槽的深度。
根据本发明实施例的另一个方面，提供了一种基于线激光的胎纹沟槽深度测量装置，所述装置包括：点云图获取单元，用于获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；平行旋转单元，用于将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；沟槽定位单元，用于根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；深度测量单元，用于根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深 度。
根据本发明实施例的另一方面，提供了一种计算设备，包括：处理器、存储器、通信接口和通信总线，所述处理器、所述存储器和所述通信接口通过所述通信总线完成相互间的通信；
所述存储器用于存放至少一可执行指令，所述可执行指令使所述处理器执行上述基于线激光的胎纹沟槽深度测量方法的步骤。
本发明实施例通过获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度，能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便，双边测量能够达到0.1mm的测量精度，单边测量能够达到0.3mm的测量精度。
上述说明仅是本发明实施例技术方案的概述，为了能够更清楚了解本发明实施例的技术手段，而可依照说明书的内容予以实施，并且为了让本发明实施例的上述和其它目的、特征和优点能够更明显易懂，以下特举本发明的具体实施方式。
附图说明
通过阅读下文优选实施方式的详细描述，各种其他的优点和益处对于本领域普通技术人员将变得清楚明了。附图仅用于示出优选实施方式的目的，而并不认为是对本发明的限制。而且在整个附图中，用相同的参考符号表示相同的部件。在附图中：
图1示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的流程示意图；
图2示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的手持式胎纹沟槽深度测量设备示意图；
图3示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的原始2D点云图；
图4示出了根据图3中的原始2D点云图得到的梯度图；
图5示出了根据图4中的梯度图整合后的梯度效果图；
图6示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的胎纹沟槽深度分析示意图；
图7示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的适用单边测量的轮胎示意图；
图8示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的单边测量示意图；
图9示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量装置的结构示意图；
图10示出了本发明实施例提供的计算设备的结构示意图。
具体实施方式
下面将参照附图更详细地描述本发明的示例性实施例。虽然附图中显示了本发明的示例性实施例，然而应当理解，可以以各种形式实现本发明而不应被这里阐述的实施例所限制。相反，提供这些实施例是为了能够更透彻地理解本发明，并且能够将本发明的范围完整的传达给本领域的技术人员。
图1示出了本发明实施例提供的基于线激光的胎纹沟槽深度测量方法的流程示意图。该方法由电子设备执行。如图1所示，基于线激光的胎纹沟槽深度测量方法包括：
步骤S11：获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图。
在本发明实施例中，该电子设备可以为手持式胎纹沟槽深度测量设备，也可以用于除非手持式设备的其它系统方案，包括落地式胎纹测量方案，PC系统测量方案等。如图2所示，手持式胎纹沟槽深度测量设备包括底座、线激光器、摄像头、主机、显示系统、电池、机身等部分。激光器和摄像机安装在同一轴线上，但有一定的距离，激光线的投射方向和相机的Z轴方向成预设夹角。优选地，一般为25～30度。激光线投射时，可以轮胎在下，激光器在上投射激光线到轮胎表面，胎纹沟槽向上。也可以垂直翻转180度，轮胎表面在上，激光器在下投射激光线到轮胎表面，胎纹沟槽向下。激光器的选择可以支持除520nm之外的其它波段激光，比如650nm的红色激光。测量时，激光器打开，激光线投射到被测物体上，摄像头抓取激光线图像。在步骤S11中，获取摄像机抓取的激光线图像，从激光线图像中获取激光线的像素坐标(u，v)，根据所述像素坐标(u，v)通过投影变换转换成相机坐标(x c，y c，z c)，将相机坐标(x c，y c，z c)进行旋转变换成激光器坐标(x L，y L，z L)，其中x L为激光线方向，y L为激光线的投射方向，垂直坐标z L为激光光刀平面的法向量。测量时，底座贴在轮胎表面，激光几乎垂直于轮胎表面投射，对于胎纹的深度分析，仅需关心激光在y L方向的投射距离，如此选取所述激光器坐标(x L，y L，z L)中的2D坐标(x L，y L)，作为所述激光线在激光坐标系中的所述原始2D点云图，以在2D坐标系中分析胎纹的深度信息。
步骤S12：将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴。
在本发明实施例中，轮胎表面激光线在激光坐标系中的原始2D点云图如图3所示，水平坐标为激光线在轮胎表面的位置x L，纵向坐标为激光线的投 射距离y L。在进行胎纹深度分析之前，需要对胎纹的有效性进行判断，如图3中所示的原始2D点云图，左侧三个凹槽正常，为有效凹槽；右侧有一个干扰点(斜纹影响)和不完全凹槽(激光遮挡影响)，它们是无效的，不能作为胎纹深度输出。剔除无效胎纹的方法包括：胎纹沟槽的深度太小，一般为轮胎杂纹造成；胎纹沟槽不完整，通常由于激光遮挡造成。如果胎纹沟槽底部区域(y L值大小几乎一致)小于一定宽度，则该胎纹沟槽无效。
分析胎纹的深度信息，需要在原始2D点云图中找到胎纹沟槽的位置并比较胎纹沟槽底部和轮胎表面在激光投射方向上的距离深度。为了方便分析和提高后续梯度计算的准确性，需要尽可能把轮胎表面旋转与X轴平行，这样查找胎纹沟槽位置与计算胎纹沟槽深度更方便。
在本发明实施例中，根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合。边缘处的像素点与表面部分的像素点一致性差异太大，如不在同一条直线附近，对平行旋转运算影响比较大，旋转计算时候首先删除边缘部分的像素点。删除方法：从两个边缘向中间搜索一段距离，一致性开始变得比较密切部分的位置，则从该处到点云边缘的像素点剔除，得到第一像素点集合。用剔除边缘像素点后的第一像素点集合中的像素点拟合直线，常用最小二乘法来拟合直线，得到第一直线，计算出该第一直线的倾斜角度θ，即第一直线旋转到与水平X轴平行所需的第一旋转角度θ，对第一像素点集合中的像素点旋转第一旋转角度θ，得到第一点云集合，保持第一点云集合大致平行于水平X轴，输出该第一点云集合S。
然后，第一次旋转很难做到点云表面完全平行于水平X轴，需要做第二次旋转以去掉胎纹的影响。根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合。具体地，将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合S1。由于胎纹沟槽部分yL比较大，可以保留前面纵坐标yL较小的60％的点，相当于剔除胎纹沟槽部分点。根据所述第二像素点集合进行直线拟合得到第二直线；计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度α。将第二像素点集合S1中的像素点旋转第二旋转角度α，输出第二点云集合S2。
再者，根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度。具体地，根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合S3；根据所述第三点云集合S3进行直线拟合得到第三直线；计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度β。
最后，将所述原始2D点云图中的像素点分别旋转所述第一旋转角度θ、所述第二旋转角度α以及所述第三旋转角度β，得到所述点云数据。原始2D点云图中的像素点通过旋转第一旋转角度θ使旋转后的像素点整体趋势与水平X轴平行，通过旋转第二旋转角度α能够消除胎纹沟槽影响，通过旋转第三旋转角度β能够进一步消除由轮胎斜纹部分产生的干扰点的影响，最终得到的所述点云数据几乎与水平X轴平行，能够使后续的梯度计算更精准，深度分析更方便。
步骤S13：根据所述点云数据应用梯度分析方法进行胎纹沟槽定位。
在本发明实施例中，根据所述点云数据应用梯度分析方法进行胎纹沟槽定位。具体地，根据所述点云数据进行采样计算，获取所述点云数据的梯度图；根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。对于轮胎的应用场景，可以按照0.3mm的间距采样计算，计算方法为相邻的点P1(x L1,y L1)，P2(x L2,y L2)，按照以下公式进行计算：
Figure PCTCN2021133462-appb-000001
y＝y L2-y L1。
图4是根据图3中的原始2D点云图应用以上计算方法得到的梯度图。在得到的图4所示的梯度图中，三个波峰表示三个胎纹沟槽的左边沿位置，在该处yL变化最剧烈；同理，三个波谷表示三个胎纹沟槽的右边沿，在该处yL也变化最剧烈。为了分析方便，连续向一个方向变化的梯度做整合，仅仅保留局部范围内波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。每个相邻波峰和波谷之间代表了一个胎纹沟槽，整合后的梯度效果如图5所示。在进行胎纹沟槽定位的时候，波峰和波谷一般成对出现，如果波峰和波谷低于预设阈值，则忽略这样的胎纹沟槽，因为轮胎杂纹或者点云数据受干扰也会在梯度图中产生局部的波锋和波谷。如果波峰与波谷超过预设阈值，从波峰到波谷的斜线就代表一个胎纹沟槽，波峰和波谷分别表示胎纹沟槽的左边沿和右边沿，波峰和波谷之间表示胎纹沟槽底部的区域。
步骤S14：根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
在本发明实施例中，完成胎纹沟槽定位后，所述点云数据中向胎纹沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；计算胎纹沟槽底部到所述参考线的距离即为所述胎纹沟槽的深度。具体地，根据图6所示进行胎纹沟槽深度分析，根据点云数据，向胎纹沟槽边缘左右侧分别搜索一段距离，得到两个点云集合：左侧点云集合L和右侧点云集合R，分别从这两个点云集合中各取一个点连成一条直线作为参考线，计算胎纹沟槽底部到参考线的距离h即为胎纹沟槽的深度。在左侧点云集合L和右侧点云集合R选取的像素点满足第一预设条件：胎纹沟槽底部的像素点到参考线的距离最大，或者， 在左侧点云集合L和右侧点云集合R中，在参考线下方的像素点不超过3个。进行胎纹沟槽深度计算时，由于干扰或者数据抖动，胎纹沟槽区域G取单个点来计算胎纹沟槽深度波动太大，一把采取均值优化算法计算胎纹沟槽深度。具体地，计算胎纹沟槽区域G中所有像素点到参考线的距离d，对计算的距离进行降序排序，取前面最大的10％的距离值求平均值作为胎纹沟槽的深度。
在本发明实施例中，双边测量使用于胎纹沟槽两边能找到参考位置的情况。但部分轮胎的胎纹沟槽找不到两个参考位置，只能找到一个参考位置，如图7所示的越野轮胎，此时就需要采用单边测量法。单边测量方法如图8所示，根据所述点云数据在胎纹沟槽边沿像素点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；如果第一参考线段和第二参考线段基本平行，计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为胎纹的深度。在搜索预设长度的线段时，需满足第二预设条件：在该线段的预设长度范围内，点云数据都在该线段附近，线段在边缘像素点一定范围内，线段长度需要满足一定的阈值。第一参考线段和第二参考线段平行的判定方法可以根据线段的斜率接近或者夹角趋于0来判断。
本发明实施例的基于线激光的胎纹沟槽深度测量方法测量精度高，测量速度快，操作方便，对轮胎的覆盖范围广，支持大部分胎纹沟槽深度测量。其中，双边测量能够达到0.1mm的测量精度，单边测量能够达到0.3mm的测量精度。
本发明实施例通过获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度，能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便。
图9示出了本发明实施例的基于线激光的胎纹沟槽深度测量装置的结构示意图。该基于线激光的胎纹沟槽深度测量装置应用于电子设备。如该电子设备可以为手持式胎纹沟槽深度测量设备，也可以用于除非手持式设备的其它系统方案，包括落地式胎纹测量方案，PC系统测量方案等。电子设备包括底座、线激光器、摄像头、主机、显示系统、电池、机身等部分，基于线激光的胎纹沟槽深度测量装置具体设置在其中的主机中。图9所示，该基于线激光的胎纹沟槽深度测量装置包括：点云图获取单元901、平行旋转单元902、沟槽定位单元903以及深度测量单元904。其中：
点云图获取单元901用于获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；平行旋转单元902用于将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；沟槽定位单元903用于根据 所述点云数据应用梯度分析方法进行胎纹沟槽定位；深度测量单元904用于根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
在一种可选的方式中，点云图获取单元901用于：从所述激光线图像中获取所述激光线的像素坐标(u,v)；根据所述像素坐标(u,v)通过投影变换转换成相机坐标(x c,y c,z c)；将所述相机坐标(x c,y c,z c)进行旋转变换成激光器坐标(x L,y L,z L)，其中，横坐标x L为激光线方向，纵坐标y L为激光线的投射方向，垂直坐标z L为激光光刀平面的法向量；选取所述激光器坐标(x L,y L,z L)中的2D坐标(x L，y L)作为所述激光线在激光坐标系中的所述原始2D点云图。
在一种可选的方式中，平行旋转单元902用于：根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合；根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合；根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度；将所述原始2D点云图中的像素点分别旋转所述第一旋转角度、所述第二旋转角度以及所述第三旋转角度，得到所述点云数据。
在一种可选的方式中，平行旋转单元902用于：将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合；根据所述第二像素点集合进行直线拟合得到第二直线；计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度。
在一种可选的方式中，平行旋转单元902用于：根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合；根据所述第三点云集合进行直线拟合得到第三直线；计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度。
在一种可选的方式中，沟槽定位单元903用于：根据所述点云数据进行采样计算，获取所述点云数据的梯度图；根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。
在一种可选的方式中，深度测量单元904用于：所述点云数据中向胎纹沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；计算胎纹沟槽底部到所述参考线的距离即为所述胎纹沟槽的深度。
在一种可选的方式中，深度测量单元904用于：根据所述点云数据在胎纹沟槽边沿点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为胎纹的深度。
本发明实施例通过获取激光线投射到被测轮胎表面上得到的激光线图像， 并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度，能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便。
本发明实施例提供了一种非易失性计算机存储介质，所述计算机存储介质存储有至少一可执行指令，该计算机可执行指令可执行上述任意方法实施例中的基于线激光的胎纹沟槽深度测量方法。
可执行指令具体可以用于使得处理器执行以下操作：
获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；
将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；
根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；
根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
从所述激光线图像中获取所述激光线的像素坐标(u，v)；
根据所述像素坐标(u，v)通过投影变换转换成相机坐标(x c，y c，z c)；
将所述相机坐标(x c，y c，z c)进行旋转变换成激光器坐标(x L，y L，z L)，其中，横坐标x L为激光线方向，纵坐标y L为激光线的投射方向，垂直坐标z L为激光光刀平面的法向量；
选取所述激光器坐标(x L，y L，z L)中的2D坐标(x L，y L)作为所述激光线在激光坐标系中的所述原始2D点云图。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合；
根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合；
根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度；
将所述原始2D点云图中的像素点分别旋转所述第一旋转角度、所述第二旋转角度以及所述第三旋转角度，得到所述点云数据。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合；
根据所述第二像素点集合进行直线拟合得到第二直线；
计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；
保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合；
根据所述第三点云集合进行直线拟合得到第三直线；
计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述点云数据进行采样计算，获取所述点云数据的梯度图；
根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
所述点云数据中向胎纹沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；
计算胎纹沟槽底部到所述参考线的距离即为所述胎纹沟槽的深度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述点云数据在胎纹沟槽边沿点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；
计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为胎纹的深度。
本发明实施例通过获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度，能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便。
本发明实施例提供一种基于线激光的胎纹沟槽深度测量装置，用于执行上述基于线激光的胎纹沟槽深度测量方法。
本发明实施例提供了一种计算机程序，所述计算机程序可被处理器调用使基站设备执行上述任意方法实施例中的基于线激光的胎纹沟槽深度测量方法。
本发明实施例提供了一种计算机程序产品，所述计算机程序产品包括存储在计算机存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行上述任意方法实施例中的基于线激光的胎纹沟槽深度测量方法。
可执行指令具体可以用于使得处理器执行以下操作：
获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图 像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；
将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；
根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；
根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
从所述激光线图像中获取所述激光线的像素坐标(u，v)；
根据所述像素坐标(u，v)通过投影变换转换成相机坐标(x c，y c，z c)；
将所述相机坐标(x c，y c，z c)进行旋转变换成激光器坐标(x L，y L，z L)，其中，横坐标x L为激光线方向，纵坐标y L为激光线的投射方向，垂直坐标z L为激光光刀平面的法向量；
选取所述激光器坐标(x L，y L，z L)中的2D坐标(x L，y L)作为所述激光线在激光坐标系中的所述原始2D点云图。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合；
根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合；
根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度；
将所述原始2D点云图中的像素点分别旋转所述第一旋转角度、所述第二旋转角度以及所述第三旋转角度，得到所述点云数据。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合；
根据所述第二像素点集合进行直线拟合得到第二直线；
计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；
保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合；
根据所述第三点云集合进行直线拟合得到第三直线；
计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述点云数据进行采样计算，获取所述点云数据的梯度图；
根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的 波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
所述点云数据中向胎纹沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；
计算胎纹沟槽底部到所述参考线的距离即为所述胎纹沟槽的深度。
在一种可选的方式中，所述可执行指令使所述处理器执行以下操作：
根据所述点云数据在胎纹沟槽边沿点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；
计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为胎纹的深度。
本发明实施例通过获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度，能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便。
图10示出了本发明实施例提供的计算设备的结构示意图，本发明具体实施例并不对设备的具体实现做限定。
如图10所示，该计算设备可以包括：处理器(processor)1002、通信接口(Communications Interface)1004、存储器(memory)1006、以及通信总线1008。
其中：处理器1002、通信接口1004、以及存储器1006通过通信总线1008完成相互间的通信。通信接口1004，用于与其它设备比如客户端或其它服务器等的网元通信。处理器1002，用于执行程序1010，具体可以执行上述基于线激光的胎纹沟槽深度测量方法实施例中的相关步骤。
具体地，程序1010可以包括程序代码，该程序代码包括计算机操作指令。
处理器1002可能是中央处理器CPU，或者是特定集成电路ASIC(Application Specific Integrated Circuit)，或者是被配置成实施本发明实施例的一个或各个集成电路。设备包括的一个或各个处理器，可以是同一类型的处理器，如一个或各个CPU；也可以是不同类型的处理器，如一个或各个CPU以及一个或各个ASIC。
存储器1006，用于存放程序1010。存储器1006可能包含高速RAM存储器，也可能还包括非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。
程序1010具体可以用于使得处理器002执行以下操作：
获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；
将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；
根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；
根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
从所述激光线图像中获取所述激光线的像素坐标(u，v)；
根据所述像素坐标(u，v)通过投影变换转换成相机坐标(x c，y c，z c)；
将所述相机坐标(x c，y c，z c)进行旋转变换成激光器坐标(x L，y L，z L)，其中，横坐标x L为激光线方向，纵坐标y L为激光线的投射方向，垂直坐标z L为激光光刀平面的法向量；
选取所述激光器坐标(x L，y L，z L)中的2D坐标(x L，y L)作为所述激光线在激光坐标系中的所述原始2D点云图。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合；
根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合；
根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度；
将所述原始2D点云图中的像素点分别旋转所述第一旋转角度、所述第二旋转角度以及所述第三旋转角度，得到所述点云数据。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合；
根据所述第二像素点集合进行直线拟合得到第二直线；
计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；
保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合；
根据所述第三点云集合进行直线拟合得到第三直线；
计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
根据所述点云数据进行采样计算，获取所述点云数据的梯度图；
根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的波峰和波谷，并根据所述波峰和所述波谷进行胎纹沟槽定位。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
所述点云数据中向胎纹沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；
计算胎纹沟槽底部到所述参考线的距离即为所述胎纹沟槽的深度。
在一种可选的方式中，所述程序1010使所述处理器执行以下操作：
根据所述点云数据在胎纹沟槽边沿点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；
计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为胎纹的深度。
本发明实施例通过获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；根据所述点云数据应用双边测量或单边测量计算胎纹沟槽深度，能够支持各种胎纹沟槽深度测量，测量精度高，测量速度快，操作方便。
在此提供的算法或显示不与任何特定计算机、虚拟系统或者其它设备固有相关。各种通用系统也可以与基于在此的示教一起使用。根据上面的描述，构造这类系统所要求的结构是显而易见的。此外，本发明实施例也不针对任何特定编程语言。应当明白，可以利用各种编程语言实现在此描述的本发明的内容，并且上面对特定语言所做的描述是为了披露本发明的最佳实施方式。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本发明的实施例可以在没有这些具体细节的情况下实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
类似地，应当理解，为了精简本发明并帮助理解各个发明方面中的一个或多个，在上面对本发明的示例性实施例的描述中，本发明实施例的各个特征有时被一起分组到单个实施例、图、或者对其的描述中。然而，并不应将该公开的方法解释成反映如下意图：即所要求保护的本发明要求比在每个权利要求中所明确记载的特征更多的特征。
本领域技术人员可以理解，可以对实施例中的设备中的模块进行自适应性地改变并且把它们设置在与该实施例不同的一个或多个设备中。可以把实施例中的模块或单元或组件组合成一个模块或单元或组件，以及可以把它们分成多个子模块或子单元或子组件。除了这样的特征和/或过程或者单元中的至少一些是相互排斥之外，可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明确陈述，本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。
应该注意的是上述实施例对本发明进行说明而不是对本发明进行限制，并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施 例。在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。单词“包含”不排除存在未列在权利要求中的元件或步骤。位于元件之前的单词“一”或“一个”不排除存在多个这样的元件。本发明可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。上述实施例中的步骤，除有特殊说明外，不应理解为对执行顺序的限定。

Claims (10)

  1. 一种基于线激光的胎纹沟槽深度测量方法，其特征在于，所述方法包括：
    获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；
    将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；
    根据所述点云数据应用梯度分析方法进行胎纹沟槽定位；
    根据所述点云数据应用双边测量或单边测量计算所述胎纹沟槽的深度。
  2. 根据权利要求1所述的方法，其特征在于，所述对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图，包括：
    从所述激光线图像中获取所述激光线的像素坐标(u，v)；
    根据所述像素坐标(u，v)通过投影变换转换成相机坐标(x c，y c，z c)；
    将所述相机坐标(x c，y c，z c)进行旋转变换成激光器坐标(x L，y L，z L)，其中，横坐标x L为激光线方向，纵坐标y L为激光线的投射方向，垂直坐标z L为激光光刀平面的法向量；
    选取所述激光器坐标(x L，y L，z L)中的2D坐标(x L，y L)作为所述激光线在激光坐标系中的所述原始2D点云图。
  3. 根据权利要求1所述的方法，其特征在于，所述将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴，包括：
    根据所述原始2D点云图中的剔除边缘像素点后的第一像素点集合进行直线拟合得到第一直线，计算所述第一直线旋转到与水平X轴平行所需的第一旋转角度，将所述第一像素点集合旋转所述第一旋转角度得到第一点云集合；
    根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，以及获取所述第一点云集合中剔除胎纹沟槽部分点且旋转了所述第二旋转角度得到的第二点云集合；
    根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度；
    将所述原始2D点云图中的像素点分别旋转所述第一旋转角度、所述第二旋转角度以及所述第三旋转角度，得到所述点云数据。
  4. 根据权利要求3所述的方法，其特征在于，所述根据所述第一点云集合获取消除胎纹沟槽影响所需旋转的第二旋转角度，包括：
    将所述第一点云集合中的像素点按照纵坐标进行升序排列，保留纵坐标较小的预设比例的像素点，形成第二像素点集合；
    根据所述第二像素点集合进行直线拟合得到第二直线；
    计算所述第二直线旋转到与水平X轴平行所需的所述第二旋转角度。
  5. 根据权利要求3所述的方法，其特征在于，所述根据所述第二点云集合获取消除干扰点影响所需旋转的第三旋转角度，包括：
    根据所述第二像素点集合进行直线拟合，计算所述第二像素点集合中像素点到拟合直线的欧式距离；
    保留所述欧式距离在预设阈值内的像素点，形成第三像素点集合；
    根据所述第三点云集合进行直线拟合得到第三直线；
    计算所述第三直线旋转到与水平X轴平行所需的所述第三旋转角度。
  6. 根据权利要求1所述的方法，其特征在于，所述根据所述点云数据应用梯度分析方法进行沟槽定位，包括：
    根据所述点云数据进行采样计算，获取所述点云数据的梯度图；
    根据所述梯度图连续向一个方向变化的梯度做整合，仅保留局部范围内的波峰和波谷，并根据所述波峰和所述波谷进行沟槽定位。
  7. 根据权利要求1所述的方法，其特征在于，所述根据所述点云数据应用双边测量或单边测量计算胎纹沟槽深度，包括：
    所述点云数据中向沟槽边缘左右侧分别搜索一段距离，并各取一点连成一直线作为参考线；
    计算沟槽底部到所述参考线的距离即为所述沟槽的深度。
  8. 根据权利要求1所述的方法，其特征在于，所述根据所述原始2D点云图应用双边测量或单边测量计算胎纹沟槽深度，包括：
    根据所述点云数据在沟槽边沿点左右预设距离范围内分别搜索预设长度的线段，得到第一参考线段和第二参考线段；
    计算相互平行的所述第一参考线段和所述第二参考线段之间的欧式距离作为胎纹的深度。
  9. 一种基于线激光的胎纹沟槽深度测量装置，其特征在于，所述装置包括：
    点云图获取单元，用于获取激光线投射到被测轮胎表面上得到的激光线图像，并对所述激光线图像中的所述激光线的像素坐标进行旋转获取所述激光线在激光坐标系中的原始2D点云图；
    平行旋转单元，用于将所述原始2D点云图中像素点进行平行旋转，得到点云数据使根据所述点云数据中位于胎纹表面的所述像素点拟合的直线平行于水平X轴；
    沟槽定位单元，用于根据所述点云数据应用梯度分析方法进行沟槽定位；
    深度测量单元，用于根据所述点云数据应用双边测量或单边测量计算胎纹沟槽深度。
  10. 一种计算设备，其特征在于，包括：处理器、存储器、通信接口和通信总线，所述处理器、所述存储器和所述通信接口通过所述通信总线完成相互间的通信；
    所述存储器用于存放至少一可执行指令，所述可执行指令使所述处理器执行根据权利要求1-7任一项所述基于线激光的胎纹沟槽深度测量方法的步骤。
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