CN111932494B - Tire wear degree evaluation method and device - Google Patents
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Abstract
The embodiment of the invention provides a tire wear degree evaluation method, which comprises the following steps: obtaining image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection; processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area; constructing a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown; and acquiring relative position data and depth data of each pattern on the rotating tire crown residual area of the tire to be evaluated, and splicing the relative position data and the depth data of each pattern on the residual area by taking the local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated. The embodiment of the invention also provides a tire wear degree evaluation device. The method can visually and integrally evaluate the abrasion position and the abrasion degree value of the tire to be evaluated.
Description
Technical Field
The invention relates to the technical field of image data processing, in particular to a tire wear degree evaluation method and device.
Background
Currently, when a driver or a maintenance person finds out that a tire is worn by observation or simple measurement, further detection is needed to determine the specific wear degree of the tire, and detection methods can be roughly divided into two types according to different tire types:
the first category is single-line detection for single-line tires: the related prior art for single line detection can be found in the prior patent application for a method, system and storage medium for measuring the depth of a tire pattern (application No. 20191127368.5). Because of being influenced by driver's driving habits, the different regional wear surface of each tire is different, but the single line detects and measures tire pattern radial height through single line laser, promptly: the single-line detection is to calculate the wear degree based on a two-dimensional plane, so that the three-dimensional shape of the whole tire cannot be reconstructed, and the wear degrees of different areas of the tire cannot be visually displayed. Meanwhile, the single-line detection has a large degree of dependence on detection personnel, for example, the detection personnel is required to perform operations such as region selection and placement, and the operations directly cause that the detection results of adjacent regions are obviously different.
The second category is "multi-line detection" for multi-line tires: although the multi-line tire firstly extracts the tire pattern characteristics through a plurality of laser lines, the multi-line tire is divided into a plurality of single lines to independently extract the grooves of each line, and finally, a plurality of lines are forcibly fitted into a plurality of line results. Obviously, in the process, only the influence of the current several lines is considered, and the overall relationship between the tire measurement area and the tire motion track is ignored, so that when the tire moves or the position changes, the current multi-line detection result is independent from the next multi-line detection result, and therefore, the position still needs to be manually selected to perform a large number of repeated operations.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for evaluating a tire wear degree to solve the above technical problems.
In order to achieve the above technical object, an embodiment of the present invention provides a tire wear degree evaluation method, which is improved by including:
obtaining image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection;
processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area;
constructing a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown;
the method comprises the steps of obtaining relative position data and depth data of each pattern on a residual area of a rotating tire crown to be evaluated, splicing the relative position data and the depth data of each pattern on the residual area by taking a local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated, and then visually and integrally evaluating the wear position and the wear extent value of the tire to be evaluated through the three-dimensional model.
In order to achieve the above object, an embodiment of the present invention provides a tire wear degree evaluation device, which is improved by including:
the acquisition module is used for acquiring the image data of the local area of the tire crown of the tire to be evaluated through multi-line laser projection;
the processing module is used for processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area;
the building module is used for building a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown;
and the evaluation module is used for acquiring the relative position data and the depth data of each pattern on the residual area of the crown of the rotating tire to be evaluated, splicing the relative position data and the depth data of each pattern on the residual area by taking the local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated, and then visually and integrally evaluating the wear position and the wear degree value of the tire to be evaluated through the three-dimensional model.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages:
according to the invention, the crown image data is processed to construct and obtain the three-dimensional model of the tire to be evaluated, so that the abrasion and the abrasion degree value of each different area of the tire to be evaluated can be visually and integrally evaluated, and the method is very convenient.
The invention has convenient operation and low cost, can be widely applied to the technical field of image data processing, in particular to the technical field of constructing a three-dimensional model of a workpiece or a product through image data so as to measure, evaluate or monitor the performance of the corresponding workpiece or product.
Drawings
FIG. 1 is a schematic flow chart diagram of one embodiment of a tire wear level evaluation method of the present invention;
FIG. 2 is a schematic flow chart of the method for evaluating the degree of wear of a tire according to the present invention applied to one embodiment of a multi-line tire;
FIG. 3 is an original image acquired by multiline laser projection;
FIG. 4 is an image of a local area of the crown of the tire to be evaluated;
FIG. 5 is a sub-pixel central image of each pattern on a partial region of the crown of the tire to be evaluated;
FIG. 6 is an image of the groove area of each pattern in a partial area of the crown of the tire to be evaluated;
FIG. 7 is an image of the grooves and the tread of each pattern on a partial region of the crown of the tire to be evaluated;
FIG. 8 is a representation of one of the three-dimensional models of a portion of a tire to be evaluated;
FIG. 9 is another illustration of a partial three-dimensional model of a tire under evaluation;
fig. 10 is a schematic diagram of one embodiment of the tire wear degree evaluation device of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
As shown in fig. 1 to 9, an embodiment of the present invention provides a method for evaluating a tire wear degree, including the following steps:
obtaining image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection;
processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area;
constructing a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown;
the method comprises the steps of obtaining relative position data and depth data of each pattern on a residual area of a rotating tire crown to be evaluated, splicing the relative position data and the depth data of each pattern on the residual area by taking a local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated, and then visually and integrally evaluating the wear position and the wear extent value of the tire to be evaluated through the three-dimensional model.
The multi-line laser is a light source which emits a plurality of laser lines, so that the acquired tire crown image data of the tire to be evaluated is three-dimensional image data which is obviously different from two-dimensional plane image data acquired by single-line laser projection, and an image data basis is further provided for constructing a three-dimensional model of the tire to be evaluated.
Therefore, the tire crown image data are processed to construct and obtain the three-dimensional model of the tire to be evaluated, so that the abrasion and the abrasion degree value of each different area of the tire to be evaluated can be visually and integrally evaluated, and the method is very convenient.
Meanwhile, the tire wear degree evaluation method can be carried out in the automobile advancing process, full-automatic, intelligent and accurate measurement is realized, and interference of human factors is effectively avoided.
In addition, the method is suitable for single-line tire detection or evaluation, is also suitable for multi-line tire detection or evaluation, and effectively widens the application range.
In some embodiments, the image data of the local crown area of the tyre to be evaluated are acquired by means of a multi-line laser projection, including the following:
obtaining pattern outline image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection;
and determining the image data of the local area of the tire crown to be evaluated according to the pattern outline image data of the local area of the tire crown and the gray value of the pixel point.
In some embodiments, the crown partial area image data is processed to obtain relative position data and depth data of the patterns on the crown partial area, including the following:
and processing the image data of the local area of the crown to acquire the sub-pixel center image data of each pattern on the local area of the crown. Aiming at the problems that a plurality of center lines are extracted at the depth of the tire tread by an original light bar center line extraction (steger) algorithm and the center line positioning at the depth is inaccurate, the steger algorithm is improved to solve the problem of the center line positioning at the depth during the specific operation of the step, and the improved steger algorithm is as follows:
a. image pre-processing
Line edges appear as a sudden change in image brightness from one gray level to another, followed by a rapid return to the original or near-original gray level. Visually the line edge is at the turning point of the change in gray value from increasing to decreasing (or from decreasing to increasing). In an actual image, the line edge becomes a roof-shaped edge due to the influence of the characteristics of the image sensing device and the optical diffraction miniaturization. Smoothing filtering by convolution with a gaussian function and at a certain pixel (x) in the image0,y0) The second-order taylor expansion is carried out by:
wherein g isx、gy、gxx、gyy、gxyThe results of the convolution of the image with a gaussian kernel such as a first-order x-partial derivative, a first-order y-partial derivative, a second-order x-partial derivative, etc., are respectively obtained. The gaussian kernels of each order are as follows:
note: for the two-dimensional image f (x, y), the first derivative at the line edge center point is 0, and the point where the second directional derivative takes the minimum value is the line edge center point.
b. Determining the minimum value of the first derivative and the second derivative of the line edge
Since the line edge normal direction is the direction of the maximum gray scale variation, taylor expansion can be performed along the normal direction:
for line edge, let
The following can be obtained:
to find the edge normal direction (n)x,ny) And the second derivative in that direction, the second derivative can be directly found:
ftt can be obtained＝nx 2gxx+2nxnygxy+ny 2gyy(1.6)
The Hessian matrix method can also be used, namely:
two eigenvalues of the Hessian matrix are respectively a maximum value and a minimum value of a second derivative of the image gray scale function, and the corresponding two eigenvectors represent the direction taken by the two extreme values. And the maximum absolute eigenvalue of the Hessian matrix and the corresponding eigenvector are obtained, so that the edge normal direction and the second derivative value in the direction can be obtained.
c. Extracting center points by discrimination criteria
If it is
If the minimum value of the second derivative in the direction is less than a certain threshold, the central point of the line edge can be extracted more accurately by two-layer judgment.
Classifying the patterns in the sub-pixel center image data and determining the relative position data of the patterns, wherein during the specific operation of the step, a positioning algorithm is used, and a color can be correspondingly set for each pattern; preferably, the localization algorithm is a neighborhood addressing algorithm, classifying a plurality of centerlines of the tire tread, and being able to determine to which straight line each point belongs and the position of the straight line.
Identifying each groove and the corresponding tread on each pattern based on the relative position data of each pattern, and merging adjacent grooves belonging to the same groove;
and respectively extracting a bottom point and a tread point of each groove, fitting a central axis of the three-dimensional model of the tire to be evaluated according to the tread points, and calculating and obtaining the spatial distance between the bottom point and the tread point of each groove to obtain the actual depth data of each groove so as to obtain the depth data of each pattern, wherein the bottom point is the point with the minimum distance to the central axis, and the tread point is the point with the maximum distance to the central axis.
In some embodiments, the tire wear level evaluation method further comprises:
the three-dimensional model of the tire to be evaluated is corrected by rotating the tire to be evaluated, so that the accuracy of the evaluation result is effectively improved. The purpose of the rotation is to ensure that all positions of the tire during rolling are scanned by the laser line. Specifically, the rotation splicing is to fit a central axis at each position, calculate a linear velocity and a tire cambered surface change equation at adjacent positions, and map the next multiline result to a reference profile.
Specifically, take a straight uniform motion of an automobile as an example (assumed to be in the Y direction); in the moving process, the two adjacent central axes are in a translation track equation in the driving direction, the difference value in the Y direction (abs (difference value) is the linear speed of two-time image acquisition time)/(two-time image acquisition time) is the unit linear speed, and the change of the moving arc surface is the unit linear speed and the fitting radius of the two-time image acquisition time. And drawing by taking the first fitting data as an initial value and taking the cambered surface change of each time as an increment to finish all splicing.
Based on the same inventive concept, an embodiment of the present invention further provides a tire wear degree evaluation device, as shown in fig. 10, including:
the system comprises an acquisition module 1, a calculation module and a calculation module, wherein the acquisition module 1 is used for acquiring image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection;
the processing module 2 is used for processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area;
the building module 3 is used for building a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown;
and the evaluation module 4 is used for acquiring the relative position data and the depth data of each pattern on the residual area of the crown of the rotating tire to be evaluated, splicing the relative position data and the depth data of each pattern on the residual area by taking the local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated, and then visually and integrally evaluating the wear position and the wear extent value of the tire to be evaluated through the three-dimensional model.
The multi-line laser is a light source which emits a plurality of laser lines, so that the acquired tire crown image data of the tire to be evaluated is three-dimensional image data which is obviously different from two-dimensional plane image data acquired by single-line laser projection, and an image data basis is further provided for constructing a three-dimensional model of the tire to be evaluated.
Therefore, the tire crown image data are processed to construct and obtain the three-dimensional model of the tire to be evaluated, so that the abrasion of different areas of the tire to be evaluated and the abrasion degree value can be visually and integrally evaluated, and the method is very convenient.
Meanwhile, the tire wear degree evaluation device can be applied to the automobile advancing process, full-automatic, intelligent and accurate measurement is achieved, and interference of human factors is effectively avoided.
In addition, the method is suitable for single-line tire detection or evaluation, is also suitable for multi-line tire detection or evaluation, and effectively widens the application range.
In some embodiments, the obtaining module 1 includes:
the first acquisition module is used for acquiring pattern outline image data of a local area of a tire crown of the tire to be evaluated through multi-line laser projection;
and the second acquisition module is used for determining the image data of the local area of the crown of the tire to be evaluated according to the pattern outline image data of the local area of the crown and the gray value of the pixel point.
In some embodiments, the processing module 2 comprises:
the first processing module is used for processing the image data of the crown local area so as to obtain sub-pixel center image data of each pattern on the crown local area;
the second processing module is used for classifying all patterns in the sub-pixel center image data and determining the relative position data of all the patterns;
the third processing module is used for identifying each groove and the corresponding tread on each pattern based on the relative position data of each pattern and combining the adjacent grooves belonging to the same groove;
and the fourth processing module is used for respectively extracting the bottom point and the tread point of each groove, fitting the central axis of the three-dimensional model of the tire to be evaluated according to the tread points, calculating and obtaining the space distance between the bottom point and the tread point of each groove to obtain the actual depth data of each groove and further obtain the depth data of each pattern, wherein the bottom point is the point with the minimum distance from the central axis, and the tread point is the point with the maximum distance from the central axis.
In some embodiments, the tire wear degree evaluation device further includes:
and the correction module is used for correcting the three-dimensional model of the tire to be evaluated through the rotation of the tire to be evaluated, so that the accuracy of the evaluation result is effectively improved.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the invention described above may be implemented by a general purpose computing device, they may be centralized in a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that it may be stored in a memory device and executed by a computing device, and in some cases, the steps shown or described may be executed out of order, or separately as individual integrated circuit modules, or multiple modules or steps may be implemented as a single integrated circuit module. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A tire wear degree evaluation method is characterized by comprising the following steps:
obtaining image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection;
processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area;
constructing a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown;
acquiring relative position data and depth data of each pattern on the residual area of the crown of the tire to be evaluated in a rotating mode, rotatably splicing the relative position data and the depth data of each pattern on the residual area by taking a local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated, and then visually and integrally evaluating the wear position and the wear degree value of the tire to be evaluated through the three-dimensional model;
the rotation splicing is to fit the central axis at each position, calculate the linear velocity and the tire cambered surface change equation of the adjacent positions, draw a picture by taking the first fitting data as the starting point and each cambered surface change as the increment, and finish all splicing.
2. The method for evaluating the degree of tire wear according to claim 1, wherein the obtaining of the image data of the local area of the crown of the tire to be evaluated by means of the multi-line laser projection comprises the following steps:
obtaining pattern outline image data of a local area of a tire crown of a tire to be evaluated through multi-line laser projection;
and determining the image data of the local area of the tire crown to be evaluated according to the pattern outline image data of the local area of the tire crown and the gray value of the pixel point.
3. The tire wear evaluation method according to claim 1, wherein the processing of the crown local area image data to obtain the relative position data and the depth data of each pattern on the crown local area comprises the following steps:
processing the image data of the crown local area to obtain sub-pixel center image data of each pattern on the crown local area;
classifying each pattern in the sub-pixel center image data, and determining the relative position data of each pattern;
identifying each groove and the corresponding tread on each pattern based on the relative position data of each pattern, and merging adjacent grooves belonging to the same groove;
and respectively extracting a bottom point and a tread point of each groove, fitting a central axis of the three-dimensional model of the tire to be evaluated according to the tread points, and calculating and obtaining the space distance between the bottom point and the tread point of each groove to obtain the actual depth data of each groove and further obtain the depth data of each pattern.
4. The tire wear degree evaluation method according to claim 1, further comprising:
and correcting the three-dimensional model of the tire to be evaluated by rotating the tire to be evaluated.
5. A tire wear degree evaluation device characterized by comprising:
the acquisition module is used for acquiring the image data of the local area of the tire crown of the tire to be evaluated through multi-line laser projection;
the processing module is used for processing the image data of the crown local area to obtain the relative position data and the depth data of each pattern on the crown local area;
the building module is used for building a local three-dimensional model of the tire to be evaluated according to the relative position data and the depth data of each pattern on the local area of the tire crown;
the evaluation module is used for acquiring relative position data and depth data of each pattern on the residual area of the crown of the rotating tire to be evaluated, rotatably splicing the relative position data and the depth data of each pattern on the residual area by taking the local three-dimensional model as a reference according to a time sequence to form a complete three-dimensional model of the tire to be evaluated, and then visually and integrally evaluating the wear position and the wear extent value of the tire to be evaluated through the three-dimensional model;
the rotation splicing is to fit the central axis at each position, calculate the linear velocity and the tire cambered surface change equation of the adjacent positions, draw a picture by taking the first fitting data as the starting point and each cambered surface change as the increment, and finish all splicing.
6. The tire wear degree evaluation device according to claim 5, wherein the acquisition module includes:
the first acquisition module is used for acquiring pattern outline image data of a local area of a tire crown of the tire to be evaluated through multi-line laser projection;
and the second acquisition module is used for determining the image data of the local area of the crown of the tire to be evaluated according to the pattern outline image data of the local area of the crown and the gray value of the pixel point.
7. The tire wear degree evaluation device according to claim 5, wherein the processing module includes:
the first processing module is used for processing the image data of the crown local area so as to obtain sub-pixel center image data of each pattern on the crown local area;
the second processing module is used for classifying all patterns in the sub-pixel center image data and determining the relative position data of all the patterns;
the third processing module is used for identifying each groove and the corresponding tread on each pattern based on the relative position data of each pattern and combining the adjacent grooves belonging to the same groove;
and the fourth processing module is used for respectively extracting the bottom point and the tread point of each groove, fitting the central axis of the three-dimensional model of the tire to be evaluated according to the tread points, and calculating and obtaining the spatial distance between the bottom point and the tread point of each groove so as to obtain the actual depth data of each groove and further obtain the depth data of each pattern.
8. The tire wear degree evaluation device according to claim 5, further comprising:
and the correction module is used for correcting the three-dimensional model of the tire to be evaluated through the rotation of the tire to be evaluated.
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| CN112937223A (en) * | 2021-01-18 | 2021-06-11 | 王安竹 | Vehicle tire wear degree real-time monitoring platform |
| CN113008158B (en) * | 2021-03-25 | 2023-02-24 | 烟台大学 | Multi-line laser tire pattern depth measuring method |
| CN117115724A (en) * | 2023-10-25 | 2023-11-24 | 山东玲珑轮胎股份有限公司 | Tire impression determining method and system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017103809A1 (en) * | 2015-12-16 | 2017-06-22 | Pirelli Tyre S.P.A. | Apparatus and method for the analysis of tyres |
| CN107578464A (en) * | 2017-06-30 | 2018-01-12 | 长沙湘计海盾科技有限公司 | A kind of conveyor belt workpieces measuring three-dimensional profile method based on line laser structured light |
| CN108759714A (en) * | 2018-05-22 | 2018-11-06 | 华中科技大学 | A kind of multi-thread laser profile sensor coordinate system fusion and rotating axis calibration method |
| EP3460520A1 (en) * | 2017-09-25 | 2019-03-27 | Hexagon Technology Center GmbH | Multi-beam laser scanner |
| CN110068270A (en) * | 2019-04-18 | 2019-07-30 | 上海拓今智能科技有限公司 | A kind of monocular vision box volume measurement method based on multi-line structured light image recognition |
| CN110942460A (en) * | 2019-12-12 | 2020-03-31 | 湖南省鹰眼在线电子科技有限公司 | Tire pattern depth measuring method and system and storage medium |
| CN111308499A (en) * | 2020-03-09 | 2020-06-19 | 中振同辂(江苏)机器人有限公司 | Obstacle detection method based on multi-line laser radar |
-
2020
- 2020-07-01 CN CN202010619129.6A patent/CN111932494B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017103809A1 (en) * | 2015-12-16 | 2017-06-22 | Pirelli Tyre S.P.A. | Apparatus and method for the analysis of tyres |
| CN107578464A (en) * | 2017-06-30 | 2018-01-12 | 长沙湘计海盾科技有限公司 | A kind of conveyor belt workpieces measuring three-dimensional profile method based on line laser structured light |
| EP3460520A1 (en) * | 2017-09-25 | 2019-03-27 | Hexagon Technology Center GmbH | Multi-beam laser scanner |
| CN108759714A (en) * | 2018-05-22 | 2018-11-06 | 华中科技大学 | A kind of multi-thread laser profile sensor coordinate system fusion and rotating axis calibration method |
| CN110068270A (en) * | 2019-04-18 | 2019-07-30 | 上海拓今智能科技有限公司 | A kind of monocular vision box volume measurement method based on multi-line structured light image recognition |
| CN110942460A (en) * | 2019-12-12 | 2020-03-31 | 湖南省鹰眼在线电子科技有限公司 | Tire pattern depth measuring method and system and storage medium |
| CN111308499A (en) * | 2020-03-09 | 2020-06-19 | 中振同辂(江苏)机器人有限公司 | Obstacle detection method based on multi-line laser radar |
Non-Patent Citations (3)
| Title |
|---|
| 基于多个线激光传感器旋转扫描的铸钢车轮在线三维测量技术研究;陈瀚;《中国优秀硕士学位论文全文数据库 (信息科技辑)》;20200315(第3期);第9、18页 * |
| 基于红绿双色多线激光的三维深度图像***;杨琨;《潍坊学院学报》;20101231(第06期);全文 * |
| 轮胎外观质量自动检测装置的设计与分析;白跃峰;《中国优秀硕士学位论文全文数据库 (信息科技辑)》;20180115(第1期);第54、62页 * |
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