JP2005201851A - Drainage behavior visualization method for tire - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To obtain a water flow vector of sufficiently high precision in the vicinity of circumferential-directional groove, an inclined groove or the like of a tire, when visualizing a drainage property of the tire. <P>SOLUTION: A prescribed pixel size of target area R is set in the vicinity of a tread end of the tire, using a tread image photographed at a fixed interval, and a search area S is set in a periphery of a moving destination for moving the target area R by a moving distance of the tire. A moving window W having the size same to the target area R is moved thereafter within the search area S to find a correlation between a concentration gradation value of an image data within the moving window W and a concentration gradation value of an image data within the target area R, in every moving. A position of the moving window W in the highest correlation is found out of the found correlations, and a flow of water drained from the tire is found based on positional information of the moving window W and positional information of the target area R therein. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a tire drainage behavior visualization method for visualizing drainage behavior (water flow) of a tire traveling on a road surface having a water film formed on the surface thereof.

  Tire drainage performance in grooved tires is a significant concern for drivers traveling at high speeds in the rain. Since the tire forms a tread with a certain width in contact with the road surface, a part of the water film formed on the road surface is directed forward in the tire moving direction or forward obliquely with respect to the moving direction (front side direction). To be eliminated. Moreover, a part passes through the circumferential groove | channel provided in the tire tread part along the tire circumferential direction, and is drained from the back of a tire. Moreover, a part passes through the inclined groove | channel inclined with respect to the tire circumferential direction extended in the tire width direction provided in the tread part, and is drained from the side of a tire.

  However, when the tire moving speed increases, the water that enters the tire is removed when the tire is drained forward or obliquely forward (drainage), or drained from the side through the inclined groove, or drained from the circumferential groove. Can not be drained completely. For this reason, the water that cannot be drained accumulates in the front of the tire, thickens the water film, and further enters the ground contact area between the tire and the tread surface like a wedge to reduce the contact area where the tire contacts the road surface. For this reason, braking and turning of the tire become impossible, and hydroplaning occurs.

From such a background, the tire drainage behavior when the tire travels on the road surface on which the water film is formed, for example, the water flow of the tire is obtained qualitatively and quantitatively, and the place where the water stops is found. Therefore, it is desired to eliminate the place where water stops by adjusting the arrangement position of the circumferential groove and the arrangement position of the inclined groove.
Non-Patent Document 1 below discloses a technique for visualizing a hydroplaning phenomenon, that is, a method for visualizing the drainage behavior (water flow) of a tire. In the visualization technique, a water film in which tracer particles are dispersed is formed on a transparent glass plate, and when the tire passes over the transparent glass plate, the tire tread is photographed with a video camera from the opposite side of the transparent glass plate. A method for visualizing the flow field of water at the front end of the tread of a tire by capturing a long afterimage of the tracer particle from the photographed tread image and obtaining the length and direction of the afterimage for each tracer particle. Is disclosed.

"Visualization technology of hydroplaning phenomenon", Tadashi Suzuki, Journal of Rubber Association, Vol. 74, No. 4 (2001)

  However, in this method, since the water flow vector required by the distribution density of the tracer particles does not vary and becomes uniform, a sufficiently accurate water flow vector cannot be obtained around the circumferential groove or the inclined groove of the tire. There was a problem.

  Therefore, the present invention obtains a sufficiently accurate water flow vector around the circumferential grooves and inclined grooves of the tire when visualizing the drainage behavior of the tire running on the road surface on which the water film is formed. It is an object to provide a method for visualizing the drainage behavior of a tire.

The present invention is a method for visualizing the drainage behavior of a tire that visualizes the drainage behavior of a tire that travels on a road surface on which a water film is formed. The tire tread when the tire travels on a water film is set at a set time interval. Shooting from the road surface side and obtaining a tread image of the set number of pixels,
Among the at least two tread images photographed at the set time interval, in the first tread image photographed first, an area of a predetermined pixel size is set as a target area in the vicinity of the tire tread edge, and later In the photographed second tread image, an area having a pixel size larger than the target area is searched around the destination area that has moved the target area according to the moving distance of the tire that has moved during the time interval. A step of setting as an area; a moving window having the same pixel size as the target area is moved in the search area, and a density gradation value of image data in the moving window and an image in the target area each time the movement is performed The step of obtaining the correlation with the density gradation value of the data and the highest correlation among the obtained correlations And the position of the moving window in the second tread image and the position information of the target area in the first tread image at this time, the flow of water drained by the tire is obtained. And a method for visualizing the drainage behavior of a tire.

Here, the tire has a circumferential groove along a tire circumferential direction, and in the tread image, the number of pixels of the tread image in the tire width direction orthogonal to the tire circumferential direction is N ₁ , occupied by the circumferential groove, the number of pixels of the tire width direction and N _2, a tread width of the tire in the tire width direction of the tire and W _T, the groove width in the tire width direction of the circumferential groove W _G Then, it is preferable to take a tread image so as to satisfy the following formula (1).
_{1.5 × (W T / W G} ) × N 2 ≦ N 1 (1)

Further, it is preferable that tracer particles are dispersed in the water film on which the tire travels.
Furthermore, the area occupied by the tracer particles in the tread image is preferably smaller than the target area and larger than one pixel of the tread image.

The number of pixels in the tire width direction of the search area is preferably 3 to 6 times the number of pixels of the target area in the tire width direction.
Further, the time interval Δt for photographing the tread image has a relationship set by the following expression (2), where L is the visual field length in the tire moving direction in the tread image and V is the tire moving speed. It is preferable to satisfy.
Δt ≦ (L / V) × (1/6) (2)

  In the present invention, using at least two tread images taken at set time intervals, an image area having a high correlation with the target area with respect to the image information is extracted from the search area, and the position information of the image area and the target area are extracted. The position information and the flow of water drained by the tire is obtained. Thereby, the flow vector of water around the circumferential grooves and inclined grooves of the tire, which has been difficult in the past, can be obtained with high accuracy.

  The tire drainage behavior visualization method of the present invention will be described based on a tire drainage behavior visualization system (hereinafter referred to as a system) 10 shown in FIG.

  A system 10 shown in FIG. 1 includes an observation room 12 provided in the basement for observing a tread surface of a traveling tire T for a passenger car from the road surface side, and a measurement device 14 installed inside the observation room 12. Yes.

The observation room 12 has a ceiling wall surface in which a glass plate 18 capable of withstanding the load of the tire T is provided on a part of the road surface 16 so as to be flush with the road surface 16. A water film 20 is formed. The vehicle is driven on the glass plate 18 by the driver, and the tire T moves.
On the other hand, a measuring device 14 is installed in the observation room 12.
The measuring device 14 includes lights 22 and 24 that illuminate to photograph the tread surface of the tire from the road surface side, a high-speed camera 26 that photographs the tread surface of the illuminated tire T at set time intervals, and a high-speed camera 26. The processing device 28 for processing the tread image captured in step 1 using the tire drainage visualization method of the present invention, the display 30 connected to the processing device 28, and various conditions input and settings to the processing device 28. And an input device 32 such as a keyboard and a mouse.

  A water film having a constant water depth, for example, a water depth of 5 mm, is formed on the upper surface of the glass plate 18, and tracer particles are dispersed in the water film. The color of the tracer particles is not particularly limited, but for example, white particles or transparent particles that diffusely reflect illumination light are preferable so that the tracer particles can be well distinguished from the black tire T and water in the photographed tread image. The size of the tracer particles is preferably 1/4 to 1/16 of the groove width (for example, 8 mm) of the circumferential groove of the tire, for example, spherical particles having a diameter of 0.5 to 2 mm. Is preferred. More preferably, the diameter is 0.5 to 1 mm. The material of the tracer particle is not particularly limited as long as it does not absorb water, and a resin material is preferably used. The specific gravity of water is preferably substantially the same, that is, the specific gravity is preferably 0.8 to 1.5.

  In this embodiment, the tracer particles are dispersed in the water film and the water flow vector is calculated by the method described later. However, in the present invention, the tracer particles need not necessarily be dispersed in the water film. Since the tire T that rolls and moves on the road surface that forms the water film contacts the water film while entraining air, the air bubbles of about 0.5 to 1 mm in diameter generated at this time can be substituted for the tracer particles. can do. However, tracer particles are preferably used when it is desired to obtain a flow vector with certainty.

The high speed camera 26 is a digital camera capable of photographing 2000 frames per second, and can set a frame rate, that is, a photographing time interval according to the traveling speed of the tire T. For example, when the traveling speed of the tire T is 40 km / hour, the frame rate is set to 1500 fps.
The lights 22 and 24 are light sources that illuminate the tread surface of the tire T so that a sufficient amount of light can be obtained by high-speed shooting by the high-speed camera 26. The type of the lights 22 and 24 is not particularly limited.

  When receiving the image data of the tread image captured by the high speed camera 26, the processing device 28 is a device that obtains a water flow vector representing the drainage performance of the tire T by a drainage behavior visualization method described later. The obtained water flow vector is displayed on the display 30 together with the photographed tread image of the tire T. Further, the display 30 inputs various conditions for implementing the drainage behavior visualization method described later, and displays an input screen for setting a target area and search area described later. The operator can input using the input device 12 while viewing the input screen.

  Next, the tire drainage behavior visualization method of the present invention will be described. FIG. 2 is a flowchart showing an example of a method for visualizing the drainage behavior of a tire according to the present invention.

First, the tread surface of the tire T is illuminated by the lights 22 and 24, and a tread image of the tire T when the tire T passes through the water film in which the tracer particles are dispersed is captured by the high speed camera 26 at a predetermined frame rate. Then, the processing device 28 acquires a tread image (step S10).
For example, when the viewing range (length) in the moving direction of the tire T in the tread image of the tire T is L and the traveling speed (moving speed) of the tire T is V, the frame rate is expressed by the following equation (2). The frame rate is adjusted so that the tread image is captured at the set time interval Δt.
Δt ≦ (L / V) × (1/6) (2)

  That is, it is set so that at least six images of the tread surface of the tire T can be obtained in the field of view taken by the high speed camera 26. For example, when the visual field length L in the photographing visual field range is 240 mm and the traveling speed V of the tire T is 100 km / hour (27.77 m / second), the photographing time interval Δt is set to 1.44 milliseconds or less, and the frame The rate is 694.44 fps or higher. Accordingly, the frame rate needs to be approximately 700 fps or more, preferably 1000 fps or more, and more preferably 2000 fps or more. The reason why the visual field length L is 240 mm in the above example is that the width of the tread surface of the tire T is approximately 100 to 200 mm in the tire width direction, and the tread surface of the tire T is photographed as large as possible to leave a margin. is there. This is because if the tread surface of the tire T is to be photographed so as not to leave a blank space, the passing position of the tire T must be adjusted to the photographing position without any difference of 1 cm, which greatly increases the burden on the driver driving the vehicle. . The reason why the tread surface is photographed as large as possible is that the tracer particles dispersed in the water film are photographed as large as possible to accurately obtain the water flow vector around the circumferential groove of the tire T.

The number of pixels when shooting with the high-speed camera 26 is the number of pixels of the tread image in the tire width direction orthogonal to the tire circumferential direction as N ₁ and the number of pixels in the tire width direction occupied by the circumferential groove. and N _2, a tread width of the tire and W _T in the tire width direction, when the groove width in the tire width direction of the circumferential groove was set to W _G, preferably satisfy the following formula (1).
α × (W _T / W _G ) × N ₂ ≦ N ₁ (1)
(Α is a coefficient)

That is, assuming that the number of pixels N ₂ corresponding to the groove width of the circumferential groove of the tire T is the minimum number of pixels necessary to accurately visualize the flow around the circumferential groove, the groove width W _G and the tire T The number of pixels in the tire width direction of the tread surface of the tire T obtained using the tread surface width W _T is N ₂ × (W _T / W _G ). As described above, it is desirable to photograph as large as possible so that the tread surface of the tire T leaves a margin, and the coefficient α is used to multiply the number of pixels N ₂ × (W _T / W _G ) by the coefficient α. This is the minimum number of pixels required for shooting with the high-speed camera 26. As long as shooting is performed with a number of pixels larger than the minimum number of pixels, image analysis can be performed using a clear captured image, and a highly accurate water flow vector can be obtained. In the above equation, the coefficient α is 1.5 or more in order to photograph as much as possible to the extent that the tread surface of the tire T leaves a margin. If the number of pixels of an image photographed by the high speed camera 26 is extremely larger than the minimum number of pixels, the processing time required to calculate a flow vector, which will be described later, increases, which is not practically suitable. The coefficient α is preferably 1.5 or more and 3 or less. More preferably, the coefficient α is 1.5 times or more and 2 times or less.

For example, when the number of pixels N ₂ = 10 pixels, the groove width W _G = 8 mm, the tread width W _T = 200 mm of the tire T, and the coefficient α = 1.5, the number of pixels of the image captured by the high-speed camera 26 is The minimum required number of pixels in the tire width direction is 375 pixels. For example, the image is taken with 700 pixels in the tire width direction. As for the number of pixels of an image photographed by the high speed camera 26, a level that is acceptable as a processing time required for calculating a flow vector, which will be described later, does not cause any practical problem, but depends on the processing capability of the processing device 28. The upper limit of the number of pixels in the tire width direction of the image captured at 26 is, for example, 2048 pixels.

In addition, in order for the tracer particles to freely move in the circumferential grooves and further in the inclined grooves, the size of the tracer particles dispersed in the water film has an upper limit of 2 mm in diameter. On the other hand, when the tracer particles are fine, it may be difficult to identify the tracer particles in the tread image taken. For this reason, the lower limit value of the tracer particles is 0.5 mm. Furthermore, in order to identify the tracer particles in the captured tread image, the number of pixels occupied by one tracer particle in the captured image must be at least one pixel.
Therefore, the tire width direction of the pixel number N ₂ of the circumferential groove, one pixel number N ₃ occupied by the tracer particles, the groove width W _G of the diameter R _T and the circumferential groove of the tracer particles, associating by the following formula It has been.
_{N 2 = (W G / R} T) × N 3 (3)
When the diameter R _T of the tracer particle is 1 mm, the number of pixels occupied by one tracer particle is N ₃ = 4 pixels, and the groove width W _{G is} 8 mm, the number of pixels N ₂ in the tire width direction of the circumferential groove is determined to be 32 pixels. Can do.
Therefore, the lower limit value of the pixel number N ₁ of the tread image in the tire width direction can be obtained from the above equation (1) using the obtained pixel number N ₂ .
Under the shooting conditions set in this way, a tread image is taken at a predetermined time interval by the high speed camera 26.

Next, a target area and a search area in the tread image acquired in the processing device 28 are set (step S12).
This setting is performed, for example, when an operator inputs an instruction from the input device 32 while viewing the tread image displayed on the display 30. FIGS. 3A and 3B are schematic views schematically illustrating a state in which the tread surface of the tire T moves from the lower direction to the upper direction in the drawing. In the drawing, reference numeral 40 denotes a front end of the tire T, and reference numeral 42 denotes a circumferential groove of the tire T. The inclined groove of the tire T is omitted.

When the tread image at time t is displayed on the display 30 as shown in FIG. 3A, the operator looks at the display 30 and displays the number of images L _t at the stepped-side tip 40 of the circumferential groove 42 of the tire T. When the input instruction is given to set the square-shaped target area R (the hatched area in FIG. 3A), the target area R having a square shape as shown in FIG. Is set.
This target area R is set for each circumferential groove 42, and the target area R of the same size is shown in the tread image so as to interpolate the target area R set around each circumferential groove. Multiple settings are made in the horizontal direction.

Further, a tread image after a certain time interval Δt (time t + Δt) is displayed on the display 30 in the same manner. The operator inputs a search area size (number of pixels L _s ) to set the search area S (area within the thick line range in FIG. 3B) in the processing device 28. Specifically, a destination area (movement destination area) R ′ (where the target area set in FIG. 3A is moved in the movement direction of the tire T by the distance obtained by multiplying the movement speed V of the tire T by Δt. A hatched area in FIG. 3B is set, and a square shape having a pixel number L _s centered on the destination area R ′ is formed in accordance with the size (number of pixels L _s ) of the search area designated for input. The searched area S is set. Such a search area S is set for each set target area R.

Here, the pixel number L _t to be set is greater than at least 2 pixels, and preferably set to the range determined by the following formula (3). When the number of pixels _Lt is 2 pixels or less, it is difficult to specify where the tracer particles have moved.
L _t ² ≧ 3 · S _p / N _p (3)
Here, S _p is the total number of pixels in the tread image (the number of pixels in the vertical direction × the number of pixels in the horizontal direction), and N _p is the number of tracer particles photographed in the tread image.

The above equation (3) determines the average number of pixels that one tracer particle occupies in the tread image so that the number of tracer particles included in the target area R is at least three or more. By multiplying, an appropriate range of the number of pixels L _t ^{2 on} one side of the target area can be determined.
For example, if the total number of pixels S _p = 524288 (= 512 × 1024) and the number of tracer particles N _p = 256, the lower limit value of the number of pixels L _{t in} the target area R is about 45 pixels.
In the above example, the target area has a square shape, but the shape is not particularly limited, and may be a rectangular shape. Further, the number of pixels L _s in the search area S is preferably set to be three times or more the number of pixels L _t in the target area R so as not to miss tracer particles scattered at high speed. On the other hand, if the search area S is greatly expanded, the processing time becomes long. Therefore, the upper limit of the number of pixels L _s in the search area S is preferably 6 times the number of pixels L _{t in} the target area R.
In addition, it is preferable that the search area S and the target area R are set so as to partially overlap (overlap) each other from the viewpoint of obtaining a flow vector with high accuracy. At this time, the overlap amount may be changed according to the size of the search area S and the target area R. When the overlap amount is set to be relatively large compared to the size of the search area S and the target area R, the target area R is gradually shifted in the search rear S, and a correlation coefficient to be described later is calculated each time it is shifted. Therefore, the calculation amount is drastically increased in the calculation of the correlation coefficient, which requires a lot of processing time, which is not preferable.

  Along with the setting of the target area R and the search area S, the image data of the tread image is converted into a gray scale value on one side (step S14). That is, the image data is converted into, for example, a gray density gradation value of 0 to 255. This conversion is performed to obtain image information for extracting from the search area S a region having the highest correlation with the target area R described later.

Next, the processing device 28 calculates a correlation coefficient using the moving window (step S16).
A moving window W having the same pixel size as that of the target area R is moved in the search area S set as shown in FIG. 3B, and the gray scale value of the image data in the moving window W each time the movement is performed, A correlation coefficient with the gray scale value of the image data in the target area R is obtained.

  FIG. 4A shows a state where the moving window W is moved in the search area S. A correlation coefficient between the gray scale value of the image data in the moving window W and the gray scale value of the image data in the target area R is calculated each time the moving window W moves. Since both the moving window W and the target area R have a square shape and the same size, for example, a number is assigned in order in the right direction with the position of the upper left end as the origin position, and further to the right end, one step A number is assigned in order from the left end to the right end, and the gray scale value of the image data in the moving window W is associated with the gray scale value of the image data in the target area R for each number as shown in FIG. A scatter diagram as shown in b) can be created. The correlation coefficient is calculated by performing linear regression from the created scatter diagram.

  Such a correlation coefficient is calculated every time the moving window W moves, and it is determined whether or not all the moving windows W have moved within the search area S (step S18). If the determination is affirmative, the position information of the moving window W having the maximum value among the calculated correlation coefficients is obtained (step S20). On the other hand, if the determination in step S18 is negative, the process returns to step S16, and correlation coefficients are sequentially calculated until the window W has moved all within the search area S. The position information acquired in step S20 is, for example, the center position of the moving window W having the highest correlation coefficient.

  It is determined whether or not the acquisition of the position information of the moving window W having the maximum correlation coefficient has been performed for all of the set target areas R (step S22). If the determination is negative, the process returns to step S16, and steps S16 to S20 are repeated for another target area R.

The acquisition of the position information of the moving window W at which the correlation coefficient between the gray scale value of the target area R and the gray scale value in the search area S is maximized is the tread image at time t and the tread image at time t + Δt. The position information is acquired by calculating from the search area S a place that is most approximate to the dispersion state of the tracer particles that can be identified by the density of the image in the target area R. This corresponds to determining the movement destination of the tracer particles in the target area R after the time Δt.
Therefore, by creating a vector having the position information (for example, the center position) of the target area R as the start point and the position information (for example, the center position) of the moving window W as the end point, the water as shown in FIG. A flow vector is generated (step S24).

  The flow vector may be calculated using the tread image at time t and the tread image at time t + Δt. For example, when the flow of water in the circumferential groove is dominant compared to the inclined groove, When the water flow when draining water is in a steady state, the tread image at time t + 2 · Δt and the tread image at time t + 3 · Δt are used using the tread image at time t + Δt and the tread image at time t + 2 · Δt. Further, a water flow vector is created using the tread image at time t + n · Δt (n is a natural number of 3 or more) and the tread image at time t + (n + 1) · Δt, respectively. You may superimpose as one flow vector. This is because there is no difference in the flow vector regardless of the tread image at any time and the tread image after time Δt.

FIG. 5 is a diagram showing a flow vector representing the flow of water on the tread surface of the tire T thus obtained.
In the example shown in FIG. 5, the tire T is a tire for a passenger car having a tire size of 205 / 65R15, and the traveling speed (moving speed) of the tire T is 40 km / hour. The image size to be photographed was 700 × 470 pixels, and the frame rate was 1500 fps. The pixel number L _t of the target area R was set to 21 pixels, and the pixel number L _S of the search area S was set to 63 pixels.

According to FIG. 5, the flow vector of water around the circumferential groove is finely represented, and the magnitude and direction of the flow vector change depending on the location, and it can be seen that highly accurate information is represented. In particular, as can be seen in FIG. 5, the shape of the stepping tip of the tread is asymmetrical, and it can be seen that the water flow is directed sideways in the region X where the stepping tip is rounded. That is, it can be seen that the direction in which water flows changes according to the shape of the stepping tip.
As described above, the flow of water in the vicinity of the stepping end of the tire T including the periphery such as the circumferential groove and the inclined groove of the tire can be obtained with high accuracy.

  As mentioned above, although the drainage behavior visualization method of the tire of the present invention has been described in detail, the present invention is not limited to the above embodiment, and various improvements and modifications may be made without departing from the gist of the present invention. Of course.

It is a schematic block diagram of the tire drainage behavior visualization system which implements the tire drainage behavior visualization method of the present invention. It is a flowchart which shows an example of the drainage behavior visualization method of the tire of this invention. (A), (b) is a schematic diagram which illustrates typically the tread image which image | photographed the tread of a tire, a target area, and a search area. (A)-(c) is explanatory drawing explaining calculation of a correlation coefficient. It is a figure which shows the flow vector of the water obtained using the drainage behavior visualization method of the tire of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Drainage behavior visualization system 12 Observation room 14 Measuring device 16 Road surface 18 Glass plate 20 Water film 22, 24 Light 26 High-speed camera 28 Processing device 30 Display 32 Input device

Claims (6)

A method for visualizing the drainage behavior of a tire that visualizes the drainage behavior of a tire traveling on a road surface on which a water film is formed,
Shooting the tire tread when the tire runs on the water film from the road surface side at a set time interval to obtain a tread image of the set number of pixels;
Among the at least two tread images photographed at the set time interval, in the first tread image photographed first, an area of a predetermined pixel size is set as a target area in the vicinity of the tire tread edge, and later In the photographed second tread image, an area having a pixel size larger than the target area is searched around the destination area that has moved the target area according to the moving distance of the tire that has moved during the time interval. A step to set as an area;
A moving window having the same pixel size as that of the target area is moved in the search area, and each time the moving window is moved, the density gradation value of the image data in the moving window and the density gradation value of the image data in the target area are Obtaining a correlation between
Of the obtained correlations, the position of the moving window when the correlation is the highest is obtained, and the position information of the moving window in the second tread image and the position information of the target area in the first tread image at this time And a step of obtaining a flow of water drained from the tire, and a method for visualizing the drainage behavior of the tire. The tire has a circumferential groove along the tire circumferential direction,
In the tread surface images, the number of pixels the tread image in the tire width direction orthogonal to the tire circumferential direction is N _1, the occupied circumferential grooves, the number of pixels the tire width direction and N _2, the tire of said tread width of the tire in the tire width direction and W _T, the groove width in the tire width direction of the circumferential groove when the W _G, of the tire to shoot tread image so as to satisfy the following formula (1) Drainage behavior visualization method.
_{1.5 × (W T / W G} ) × N 2 ≦ N 1 (1)   The method for visualizing tire drainage behavior according to claim 1 or 2, wherein tracer particles are dispersed in a water film on which the tire travels.   The method for visualizing tire drainage behavior according to claim 3, wherein an area occupied by tracer particles in the tread image is smaller than the target area and larger than one pixel of the tread image.   The method for visualizing tire drainage behavior according to any one of claims 1 to 4, wherein the number of pixels in the tire width direction of the search area is 3 to 6 times the number of pixels of the target area in the tire width direction. . The time interval Δt for photographing the tread image satisfies the relationship set by the following equation (2), where L is the visual field length of the tire moving direction in the tread image and V is the tire moving speed. Item 6. The method for visualizing tire drainage behavior according to any one of Items 1 to 5.
Δt ≦ (L / V) × (1/6) (2)

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