Tire contact patch shape analysis device and tire contact patch shape analysis method

Abstract

To analyze a tire ground shape in the case of such high speed traveling as to generate spray.SOLUTION: As for a grounding surface in a wet road surface, an evaluation object image and continuous images that are time-series images continuing before and after the evaluation object image are acquired. First and second image sets including a plurality of images are constructed from the acquired continuous images. Luminances of the plurality of images included in each of the constructed first and second image sets are subjected to arithmetic processing, and first and second result images that are arithmetic processing results of each of the image sets are obtained. The obtained first and second result images are subjected to binarization processing based on a predetermined threshold, and first and second binarization images are obtained. The obtained first binarization image and second binarization image are superposed, and a grounding shape is determined. The first image set is composed of the evaluation object image and the time-series image before the evaluation object image, and the second image set is composed of the evaluation object image and the time-series image after the evaluation object image.SELECTED DRAWING: Figure 4

Description

【Technical Field】 【0001】 The present invention relates to a tire contact shape analysis device and a tire contact shape analysis method. 【Background Art】 【0002】 Conventionally, in order to analyze the tire contact shape, there is known a technique of photographing the contact shape of a tire of a vehicle traveling on a transparent plate having a water film from below the transparent plate (Patent Document 1). Further, there is known a technique of analyzing the contact shape of a tire by providing a water film on the surface of a road surface plate of a tire contact shape analysis device to reproduce a wet road surface and photographing from below the road surface plate (Patent Document 2). 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2001-208653 【Patent Document 2】 Japanese Patent Application Laid-Open No. 2021-081246 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In both Patent Document 1 and Patent Document 2, the contact shape of the tire can be analyzed during low-speed driving. However, in the case of high-speed driving where splashes occur, it is difficult to analyze the contact shape of the tire. 【0005】 The present invention has been made in view of the above, and an object thereof is to provide a tire contact shape analysis device and a tire contact shape analysis method capable of analyzing the contact shape of a tire in the case of high-speed driving where splashes occur. 【Means for Solving the Problems】 【0006】 To solve the above-mentioned problems and achieve the objective, a tire contact shape analysis apparatus according to one aspect of the present invention includes: an image acquisition unit that acquires a target image and a series of time-series images that are continuous before and after it for the contact surface of a tire on a wet road surface; an image set construction unit that constructs first and second image sets containing multiple images from the series of images acquired by the image acquisition unit; and a calculation processing unit that calculates the brightness of multiple images included in the first and second image sets, respectively, constructed by the image set construction unit, and the calculation processing results for the first and second image sets, respectively. The system includes a luminance calculation processing unit for obtaining a result image, a binarization processing unit for obtaining first and second binary images by performing a binarization process based on a predetermined threshold on the first and second result images obtained by the calculation processing of the luminance calculation processing unit, and a ground shape calculation unit for determining the ground shape by superimposing the first binary image and the second binary image obtained by the binarization processing of the binarization processing unit, wherein the first image set consists of the evaluation target image and the preceding time series images, and the second image set consists of the evaluation target image and the subsequent time series images. 【0007】 Furthermore, a tire contact shape analysis method according to one aspect of the present invention includes an image acquisition step of acquiring a target image and a sequence of time-series images that are continuous before and after it for the contact surface of a tire on a wet road surface; an image set construction step of constructing first and second image sets containing multiple images from the sequence of images acquired in the image acquisition step; and a brightness calculation process of the multiple images included in the first and second image sets constructed in the image set construction step, and obtaining first and second result images which are the calculation results of the first and second image sets, respectively. The process includes a degree calculation step, a binarization step which involves performing a binarization process based on a predetermined threshold on the first and second result images obtained by the calculation process of the brightness calculation step to obtain first and second binary images, and a ground shape calculation step which involves superimposing the first binary image and the second binary image obtained by the binarization process of the binarization step to determine the ground shape, wherein the first image set consists of the evaluation target image and the time-series images preceding it, and the second image set consists of the evaluation target image and the time-series images following it. [Effects of the Invention] 【0008】 According to the present invention, the contact shape of the tire can be analyzed in the case of high-speed driving where water splashes are generated. [Brief explanation of the drawing] 【0009】 [Figure 1] Figure 1 is a schematic diagram showing a tire contact shape analysis device according to an embodiment. [Figure 2] Figure 2 is a block diagram showing the functions of the tire contact patch shape analysis device shown in Figure 1. [Figure 3] Figure 3 is a flowchart showing an example of the operation of the tire contact patch shape analysis device 1. [Figure 4] Figure 4 shows the processing performed by the tire contact patch shape analysis device. [Figure 5] Figure 5 illustrates the brightness calculation process performed by the brightness calculation processing unit. [Figure 6] FIG. 6 is a flowchart showing the ground shape calculation process by the ground shape calculation unit. [Figure 7] FIG. 7 is a diagram for explaining the process according to the comparative example. [Figure 8] FIG. 8 is a diagram schematically showing the process according to the present embodiment. [Figure 9] FIG. 9 is a diagram showing an example of the ground shape obtained by the process according to the present embodiment. [Figure 10] FIG. 10 is a diagram schematically showing the process according to another comparative example. [Figure 11] FIG. 11 is a diagram showing an example of the ground shape obtained by the process according to the comparative example of FIG. 10. [Figure 12] FIG. 12 is a diagram showing the process according to another comparative example. [Figure 13] FIG. 13 is a diagram showing an example where the ground shape does not disappear in the image set construction process. [Figure 14] FIG. 14 is a diagram showing an example where the ground shape disappears in the image set construction process. [Figure 15] FIG. 15 is a flowchart showing the process of obtaining the minimum number of images in the image set in the image set construction unit. [Figure 16] FIG. 16 is a diagram for explaining the definition of the wrapping amount. [Figure 17] FIG. 17 is a diagram for explaining the case where the wrapping amount is within half of the maximum ground length. [Figure 18] FIG. 18 is a diagram for explaining the case where the wrapping amount exceeds half of the maximum ground length. [Figure 19] FIG. 19 is a diagram for explaining the process of deleting the background image in the ground shape calculation unit. [Figure 20] FIG. 20 is a diagram for explaining the comparison between the comparative example and the present embodiment. 【Mode for Carrying Out the Invention】 【0010】 Hereinafter, embodiments of the present invention will be described in detail based on the drawings. In the description of each of the following embodiments, the same or equivalent components as those in other embodiments are denoted by the same reference numerals, and the description thereof will be simplified or omitted. The present invention is not limited by each embodiment. In addition, the components of each embodiment include those that can be replaced by those skilled in the art and are easy to replace, or those that are substantially the same. Note that the configurations described below can be combined as appropriate. In addition, omissions, substitutions, or changes in the configuration can be made without departing from the gist of the invention. 【0011】 (Embodiment) FIG. 1 is a configuration diagram schematically showing a tire contact shape analysis device 1 according to an embodiment. FIG. 2 is a block diagram showing the functions of the tire contact shape analysis device 1 shown in FIG. 1. In these figures, FIG. 1 schematically shows the overall configuration of the tire contact shape analysis device 1, and FIG. 2 shows the main functions of the tire contact shape analysis device 1. 【0012】 The tire contact shape analysis device 1 according to the present embodiment is applied to a system that analyzes the contact surface 61 by acquiring an image of the contact surface 61 of the pneumatic tire 60. The tire contact shape analysis device 1 includes a tire tester 2, a photographing device 10, and a tire contact surface analysis device 20. 【0013】 The tire tester 2 is a device that applies test conditions to the pneumatic tire 60 to be analyzed (hereinafter referred to as the tire 60). In the configuration of FIG. 1, the tire tester 2 includes a support device 3, a drive device 5, and a road surface plate 11. The support device 3 is a device that rotatably supports the tire 60 and has a rim 4 on which the tire 60 is mounted. The drive device 5 is a device that applies a driving force to the tire 60 and the road surface plate 11. The drive device 5 includes a motor 6 that drives the tire 60 and the road surface plate 11, and a motor control device 7 that controls the motor 6. 【0014】 The drive unit 5, which includes gears (not shown), drives the road plate 11 horizontally. The drive unit 5 drives the road plate 11 so that it moves relative to the tire 60, which is the object of analysis. That is, the drive unit 5 drives the motor 6 with the motor control device 7 to move the road plate 11 in the direction of arrow Y1. At this time, the road plate 11 is moved in the direction of arrow Y1 while the tire 60 and camera 15 remain fixed. 【0015】 In this tire testing machine 2, the support device 3 supports the tire 60 mounted on the rim 4, and the tire 60 is pressed against the upper surface 11U, which is one of the main surfaces of the road plate 11, thereby applying a load to the tire 60. The road plate 11 replicates a flat road surface. When the tire 60 is pressed against the road plate 11, the contact surface 61 deforms in the same way as when driving on a flat road surface. By driving the road plate 11 horizontally, the rolling state of the tire 60 during vehicle operation is replicated on the surface of the road plate 11 as the road surface, and the dynamic contact characteristics can be analyzed. 【0016】 The road surface plate 11 is a light-transmitting plate that has the property of transmitting light. The road surface plate 11 does not need to transmit 100% of the light; it is sufficient that it has a light transmittance that allows the surface of the tire 60 to be photographed through the road surface plate 11. The road surface plate 11 is, for example, a flat plate made of acrylic resin or a flat plate made of glass. By photographing the contact state between the tire 60 and the flat plate and performing image analysis, it is possible to analyze the contact state of the tire 60 that is closer to reality. As the road surface plate 11 moves due to the drive of the drive device 5, the contact characteristics of the tire 60 can be obtained when the tire 60 is in contact with the main surface of the road surface plate 11. There are no specifications for the road surface plate 11, such as the thickness of the plate or the angle of refraction. 【0017】 Here, as shown by the dashed line in Figure 1, a liquid film, or water film, is provided on the upper surface 11U of the road surface plate 11. The road surface plate 11 on which the water film 12 is provided functions as a wet road surface to which the tire 60 makes contact. Walls are provided around the road surface plate 11 (not shown), and the liquid is contained within the area enclosed by the walls. For example, if the road surface plate 11 is rectangular, walls are made on all four sides of the road surface plate 11, and the liquid is contained within the area enclosed by the walls. The thickness of the water film 12 is 0.5 [mm] or more from the upper surface 11U of the road surface plate 11. When the brightness of the liquid is expressed in 256 gradations (minimum 0, maximum 255), the numerical range of brightness of the liquid constituting the water film 12 is, for example, 59 or more and 183 or less. Note that if the thickness of the water film 12 is less than 0.5 [mm], a dark area with a gradation similar to that of the tire will be generated in the non-contact area of ​​the contact surface image, which is undesirable. 【0018】 The imaging device 10 has a camera 15, which is an imaging unit for imaging the tire 60. The camera 15 is, for example, a CCD (Charge Coupled Device) camera. The camera 15 is fixed inside the imaging device 10. The camera 15 images the tire 60 through the road surface plate 11, thereby capturing the contact surface 61 of the tire 60 pressed against the road surface plate 11. Specifically, the camera 15 is positioned on the other main surface of the road surface plate 11, the lower surface 11D side, with its optical axis oriented perpendicular to the lower surface 11D side, and images the tire 60 from the lower surface 11D side through the road surface plate 11. As a result, the camera 15 images the tire 60 including at least the contact surface 61 and generates digital image data of the tire 60 including the contact surface 61. 【0019】 The tire contact patch analysis device 20 is, for example, a PC (Personal Computer) with a predetermined analysis program installed, and processes images of the tire 60 input from the imaging device 10 to analyze the contact patch 61 of the tire 60. The process of analyzing the contact patch 61 of the tire 60 includes the process of calculating the contact patch 61 based on the captured images of the tire 60. The tire contact patch analysis device 20 has a processing device 30 that performs calculation processing such as the analysis of the contact patch 61 and saves data, an input unit 21 in which an operator performs input operations to the tire contact patch analysis device 20, and a display unit 22 that displays analysis results and various information. A keyboard or a pointing device such as a mouse is used in the input unit 21, and a display device such as a liquid crystal display is used in the display unit 22. The input unit 21 and the display unit 22 are electrically connected to the processing device 30, so that the tire contact patch analysis device 20 can be operated by an operator while viewing the display unit 22. Furthermore, the camera 15 is connected to the processing unit 30 of the tire contact patch analysis device 20, which enables the tire contact patch analysis device 20 to acquire images captured by the camera 15. 【0020】 The processing unit 30 of the tire contact patch analysis device 20 is configured to include a processing unit 31 having a CPU (Central Processing Unit), etc., and a storage unit 32 such as RAM (Random Access Memory). The processing unit 31 and the storage unit 32 configured in this way may be housed in the same enclosure, in different enclosures, or multiple storage units 32 may be provided in both configurations. 【0021】 The processing unit 31 of the processing device 30 functionally includes a road surface drive unit 33, an image acquisition unit 34, an image set construction unit 35, a brightness calculation processing unit 36, a binarization processing unit 37, and a ground contact shape calculation unit 38. The road surface drive unit 33 controls the drive device 5 to move the road surface plate 11. The road surface drive unit 33 drives the road surface plate 11 to move relative to the tire 60. Depending on the speed at which the road surface plate 11 moves, the rotation speed of the tire 60 may increase, so it is necessary to shorten the exposure time. If the exposure time is too short, the captured image may become too dark, which may reduce the accuracy of the analysis. Therefore, in order to prevent a decrease in the accuracy of the analysis, lighting may be provided to irradiate the ground contact surface 61 with light. It is preferable to provide this lighting on the lower surface 11D side of the road surface plate 11. 【0022】 The image acquisition unit 34 acquires a series of images of the contact surface on a wet road surface. The series of images are a sequence of images taken by the camera 15 in chronological order. The series of images consists of the image to be evaluated and the chronological images immediately before and after it. The image to be evaluated is the image that is being focused on as the subject of evaluation. 【0023】 The image set construction unit 35 constructs first and second image sets containing multiple images from the sequence of images acquired by the image acquisition unit 34. The first image set consists of the image to be evaluated and the preceding time-series images, and the second image set consists of the image to be evaluated and the subsequent time-series images. The brightness calculation processing unit 36 ​​calculates the brightness of the multiple images included in the first and second image sets constructed by the image set construction unit 35, and obtains first and second result images, which are the calculation results for each image set. 【0024】 The binarization processing unit 37 performs a binarization process on the first and second result images obtained by the calculation processing of the brightness calculation processing unit 36, using a predetermined threshold as the basis, to obtain the first and second binary images. The ground shape calculation unit 38 superimposes the first binary image and the second binary image obtained by the binarization processing of the binarization processing unit 37 to determine the ground shape. 【0025】 The memory unit 32 has pre-stored analysis programs used by the tire contact patch analysis device 20. When acquiring the contact characteristics of the tire 60's contact patch 61, the processing unit 31 calls the program stored in the memory unit 32 and executes each function by performing operations according to the program. 【0026】 The tire contact shape analysis device 1 according to this embodiment has the configuration described above. The operation of the tire contact shape analysis device 1 will now be explained. When the tire contact shape analysis device 1 analyzes the contact surface 61 of the tire 60, the tire 60 is mounted on the support device 3 of the tire testing machine 2, and the contact surface 61 is photographed by the camera 15 while the tire 60 is rotated with the tire 60 pressed against the road surface plate 11. 【0027】 (Operation of the tire contact patch shape analysis device) Figure 3 is a flowchart showing an example of the operation of the tire contact shape analysis device 1. When the tire contact shape analysis device 1 performs an operation on the input unit 21, the road surface drive unit 33 controls the drive unit 5 and starts driving the road plate 11 (step ST11). When the road plate 11 is moving, the tire contact shape analysis device 1 takes pictures of the contact surface 61 of the tire 60 with a camera (step ST12). The captured continuous images are stored in the storage unit 32 by the image acquisition unit 34. After that, the tire contact shape analysis device 1 stops driving the road plate 11 (step ST13). 【0028】 Next, the tire contact shape analysis device 1 constructs first and second image sets from the continuous images stored in the storage unit 32 using the image set construction unit 35 (step ST14). The tire contact shape analysis device 1 then uses the brightness calculation processing unit 36 ​​to calculate the brightness of multiple images included in the first and second image sets constructed by the image set construction unit 35 (step ST15). 【0029】 Furthermore, the tire contact shape analysis device 1 uses a binarization processing unit 37 to perform binarization on the first and second result images obtained by the calculation processing of the brightness calculation processing unit 36, using a predetermined threshold as the reference (step ST16). The tire contact shape analysis device 1 uses a contact shape calculation unit 38 to superimpose the first binary image and the second binary image obtained by the binarization processing of the binarization processing unit 37 to determine the contact shape (step ST17). Through the above processing, data on the contact surface on a wet road surface can be obtained. 【0030】 (Processing by tire contact patch shape analysis device) Figure 4 shows the processing performed by the tire contact shape analysis device. As shown in Figure 4, the processing performed by the tire contact shape analysis device includes an image set construction process S35 by the image set construction unit 35, a brightness calculation process S36 by the brightness calculation processing unit 36, a binarization process S37 by the binarization processing unit 37, and a contact shape calculation process S38 by the contact shape calculation unit 38. 【0031】 In the image set construction process S35 shown in Figure 4, images P1, ..., P61, ..., P121 are a sequence of images acquired by the image acquisition unit 34. Image P1 is the image taken earliest in the time series (i.e., the oldest image). Image P121 is the image taken most recently in the time series (i.e., the newest image). 【0032】 In this example, image P61 is selected as the image to be evaluated from this sequence of images. In the image set construction process S35, a first image set GS1 is constructed, consisting of the image to be evaluated P61 and the preceding time-series images, and a second image set GS2 is constructed, consisting of the image to be evaluated P61 and the subsequent time-series images. The image to be evaluated P61 is included in both the first image set GS1 and the second image set GS2. 【0033】 Next, in the brightness calculation process S36, the maximum brightness is selected for each pixel position in both the first image set GS1 and the second image set GS2, and the results of this selection are used as the first and second result images. That is, in the brightness calculation process S36, the maximum brightness is selected for each pixel position in the first image set GS1, and this becomes the first result image RG1. Also, in the brightness calculation process S36, the maximum brightness is selected for each pixel position in the second image set GS2, and this becomes the second result image RG2. The brightness calculation process S36 corresponds to the processing content of step ST15 in Figure 3. The brightness calculation process S36 will be described further later. 【0034】 In the binarization process S37, the first result image RG1 and the second result image RG2 are each subjected to binarization based on a predetermined threshold. For example, the binarization process sets the pixels constituting the image to 256 gradations from 0 to 255, with pixels between 0 and 80 gradations being set to black and pixels between 81 and 255 gradations being set to white. This binarization process yields the first binary image G1 and the second binary image G2. 【0035】 Focusing on the first binary image G1 and comparing it with the evaluation image P61, the ground contact shape is missing, as shown by the dashed line D1. Similarly, focusing on the second binary image G2 and comparing it with the evaluation image P61, the ground contact shape is missing, as shown by the dashed line D2. 【0036】 Next, in the ground shape calculation process S38, the first binary image G1 and the second binary image G2 are superimposed to obtain the ground shape image KG. In this example, the ground shape image KG includes background images B1 and B2. Therefore, background images B1 and B2 are removed from the ground shape image KG. This yields the ground shape image SK. In the ground shape image SK, the area of ​​the dashed line H1 is white, so the splashed water portion is correctly identified as an ungrounded area. 【0037】 (Brightness calculation processing) Figure 5 is a diagram illustrating the brightness calculation process S36 performed by the brightness calculation processing unit 36. The process shown in Figure 5 corresponds to the process of step ST15 in Figure 3 and the brightness calculation process S36 in Figure 4. For each of the first and second image sets, focus on a specific pixel (step ST21). For the pixel of focus, find the largest brightness value across the entire image and set that brightness value as the brightness of that pixel (step ST22). Next, determine whether or not processing has been performed on all pixels (step ST23). 【0038】 If the result of the determination in step ST23 is that processing has not been completed for all pixels (No in step ST23), the process returns to step ST21 and continues. On the other hand, if the result of the determination in step ST23 is that processing has been completed for all pixels (Yes in step ST23), the process ends. 【0039】 As described above, the brightness calculation process performed by the brightness calculation processing unit 36 ​​involves selecting the maximum brightness for each pixel position in each of the first and second image sets, and using the selected results as the first and second result images. 【0040】 Alternatively, another method for calculating brightness could be to arithmetic average the brightness across all images and obtain the result image. For example, one could focus on a particular pixel and calculate the brightness of that pixel by summing the brightness values ​​across all images and dividing the result by the total number of images. This process could then be performed for all pixels. However, this arithmetic averaging method does not provide sufficient accuracy in determining the ground contact shape. 【0041】 (Grounding shape calculation process) Figure 6 is a flowchart showing the ground shape calculation process by the ground shape calculation unit 38. In Figure 6, the ground shape calculation unit 38 extracts the pixel values ​​at the same positions in the first binary image G1 and the second binary image G2 (step ST31). It determines whether either of the extracted pixel values ​​is black (step ST32). If, as a result of the determination in step ST32, either one is black (Yes in step ST32), that pixel is set to black (step ST33). The process then proceeds to step ST35. 【0042】 If, as a result of the determination in step ST32, any of the pixels are not black (No in step ST32), then that pixel is set to white (step ST34). Then, the process proceeds to step ST35. In step ST35, it is determined whether or not processing has been performed on all pixels (step ST35). 【0043】 If the result of the determination in step ST35 is that processing has not been completed for all pixels (No in step ST35), the process returns to step ST31 and continues. On the other hand, if the result of the determination in step ST35 is that processing has been completed for all pixels (Yes in step ST35), the process ends. 【0044】 (Processing by comparative example) Here, we will explain the difference from the processing in the comparative example and clarify that the processing by the tire contact shape analysis device according to this embodiment is an effective process. Figure 7 is a diagram illustrating the processing in the comparative example. In the comparative example shown in Figure 7, instead of constructing the first and second image sets, the continuous images are combined into a single image set GS0. That is, in Figure 7, images P1, ..., P61, ..., P121 are combined into a single image set GS0. Brightness calculation processing is performed on the image set GS0. That is, the maximum brightness is selected from all images for each pixel position, and the result of this selection is taken as the result image RG0. By performing binarization processing on the result image RG0 based on a predetermined threshold, a contact shape image KG0 is obtained. This contact shape image KG0 is significantly different from image P61. For this reason, the processing in the comparative example shown in Figure 7 does not yield a correct contact shape image. 【0045】 (Processing according to the embodiment) Figure 8 is a schematic diagram showing the process according to this embodiment. Figure 9 is a diagram showing an example of the grounding shape obtained by the process according to this embodiment. 【0046】 The arrows shown in Figure 8 indicate the direction of tire movement. As shown in Figure 8, in this embodiment, images P1 to P61 are designated as the first image set (GS1), and images P61 to P121 are designated as the second image set (GS2). In other words, in this embodiment, the image to be evaluated P61 is included in the first image set (GS1), and the image to be evaluated P61 is also included in the second image set (GS2). 【0047】 Image P1 includes the tire contact patch area CA1 and the surrounding water film area. The contact patch area CA1 has a low brightness value, while the surrounding water film area has a higher brightness value than the contact patch area CA1. The same applies to the other images P60, P61, P62, ..., P121; the contact patch areas CA60, CA61, CA62, ..., CA121 have low brightness values, while the surrounding water film area has a higher brightness value than each of the contact patch areas. 【0048】 Here, the resulting image PA obtained by performing luminance calculation processing on the first set of images GS1 and the resulting image PB obtained by performing luminance calculation processing on the second set of images GS2 are compared with the evaluation target image P61. Assuming lines L1 and L2 along the edges of the ground shape portion CA61 in the evaluation target image P61, the ground shape matches around line L1 and around line L2. Due to the luminance calculation processing S36, the dashed line H3 portion of the ground shape disappears and matches the dashed line H2 portion of the evaluation target image P61. Therefore, in the ground shape image KG obtained by superimposing the black pixel regions of the resulting images PA and PB, the ground portion is correctly evaluated around line L1, and no ground shape portion is generated at the position of dashed line H4. 【0049】 Referring to Figure 9, in the image set construction process S35, the evaluation target image P61 is included in the first image set (first image set) GS1, and the evaluation target image P61 is also included in the second image set (second image set) GS2. Therefore, the ground shape obtained by the ground shape calculation process S38 is a correct ground shape image. In particular, as shown by the dashed line H5, the ground area is correctly evaluated, and the actual contact area (ACA) is, for example, 171.6 cm². 2 This is the result. 【0050】 (Processing using other comparative examples) Figure 10 schematically shows the processing according to another comparative example. Figure 11 shows an example of the grounding shape obtained by the processing according to the comparative example in Figure 10. 【0051】 The arrows shown in Figure 10 indicate the direction of tire movement. As shown in Figure 10, in the comparative example, images P1 to P60 are designated as the first image set (first image set) GS1b, and images P61 to P121 are designated as the second image set (second image set) GS2. In other words, in this comparative example, the image to be evaluated P61 is not included in the first image set (first image set) GS1b, but is included in the second image set (second image set) GS2. 【0052】 In this comparative example, the resulting image PAa obtained by performing luminance calculation processing on the first image set GS1b and the resulting image PB obtained by performing luminance calculation processing on the second image set GS2 are compared with the evaluation target image P61. Assuming lines L1 and L2 along the edges of the ground shape portion CA61 in the evaluation target image P61, the ground shape matches around line L2. In contrast, the ground shape does not match around line L1. Due to the luminance calculation processing S36, the dashed line H6 portion of the ground shape portion remains and does not match the dashed line H2 portion of the evaluation target image P61. Therefore, in the ground shape image KGa obtained by superimposing the black pixel regions of the resulting image PAa and the resulting image PB, the ground portion is not correctly evaluated around line L1, and the ground shape portion appears at the position of dashed line H7. 【0053】 Referring to Figure 11, in the image set construction process S35, the evaluation target image P61 is not included in the first image set (first image set) GS1b, but is included in the second image set (second image set) GS2. Therefore, the ground shape obtained by the ground shape calculation process S38 is not a correct ground shape image. In particular, as shown by the dashed line H8, the ground area is overestimated, and the ACA is, for example, 172.5 cm. 2 This is the result. Here, if we set the ACA of the ground shape image in Figure 9 to an index of 100 (reference), then the ACA of the ground shape image in Figure 11 will be an index of 101. 【0054】 Figure 12 shows the processing according to another comparative example. In the image set construction process S35 of Figure 12, a first image set GS1a consisting of the evaluation target image P61 and time-series images before and after it, and a second image set GS2 consisting of the evaluation target image P61 and subsequent time-series images are constructed. The evaluation target image P61 is included in both the first image set GS1a and the second image set GS2. 【0055】 Next, in the brightness calculation process S36, the maximum brightness is selected for each pixel position in the first image set GS1a and the second image set GS2, and the results are obtained as the resulting images RG1a and RG2. The resulting image RG2 is the same as in Figure 4. In contrast, the resulting image RG1a is different from the resulting image RG1 in Figure 4. As a result, the resulting image RG2 obtained by the binarization process S37 is the same as in Figure 4, while the resulting image RG1a is different from the result in Figure 4. 【0056】 In the ground shape calculation process S38, the first binary image G1a and the second binary image G2 are superimposed to obtain the ground shape image KGa. In this example, the ground shape image KGa includes background images B1 and B2. Therefore, background images B1 and B2 are removed from the ground shape image KGa. This yields the ground shape image SKa. As shown by the dashed line D3, the ground shape image SKa is missing and has not been properly determined. 【0057】 (Minimum number of images in the image set) In the image set construction process S35, when constructing the first image set GS1 and the second image set GS2, the image set construction unit 35 preferably performs the same brightness calculation process as the brightness calculation processing unit 36 ​​to determine the minimum number of image sets at which the grounding shape disappears. 【0058】 In this case, the image set construction unit 35 performs brightness calculation processing on a set consisting of the image to be evaluated and the preceding time-series images, and on a set consisting of the image to be evaluated and the subsequent time-series images. The image set construction unit 35 then determines the minimum number of image sets at which the grounding shape disappears, and determines the maximum grounding length defined by the following equation (1). The following equation (1) determines the maximum grounding length by multiplying the grounding length moved per image by (minimum number of images - 1). Maximum contact length [mm] = (tire speed [mm / sec] / frame rate [frames / sec]) × (minimum number of frames - 1) [frames] ... (1) Frame rate refers to the number of images per second in a sequence of images. 【0059】 The cases in which the grounding shape does not disappear and cases in which it does disappear during the image set construction process S35 will be explained. Figure 13 shows an example in which the grounding shape does not disappear during the image set construction process S35. In Figure 13, images P1 and P61 are examples of continuous images of the grounding surface. Focusing on the grounding center Ce of the grounding shape portion CA1 in image P1 and the grounding shape portion CA61 in image P61, the position of the grounding center Ce of the grounding shape portion CA1 is within the range of the grounding length Wr of the grounding shape portion CA61. 【0060】 The same brightness calculation process as the brightness calculation processing unit 36 ​​is performed on the image set GS, which consists of two images, image P1 and image P61. That is, for images P1 and P61, the process is performed to adopt the maximum brightness for each pixel position. The resulting image PA includes the ground shape portion CA. In other words, the ground shape does not disappear. 【0061】 On the other hand, Figure 14 shows an example in which the grounding shape disappears during the image set construction process S35. In Figure 14, images P1, P30, and P61 are other examples of continuous images of the grounding surface. Focusing on the grounding center Ce of each image P1, P30, and P61, the positions of the grounding shape portions CA1, CA30, and CA61 are shifted by half the grounding length Wr (Wr / 2). Therefore, the position of the grounding center Ce of the grounding shape portion CA30 in image P30 is within the range of the grounding length Wr of the grounding shape portion CA1 in image P1. However, the position of the grounding center Ce of the grounding shape portion CA61 in image P61 is outside the range of the grounding length Wr of the grounding shape portion CA1 in image P1. 【0062】 The same brightness calculation process as the brightness calculation processing unit 36 ​​is performed on the image set GS', which consists of three images: image P1, image P30, and image P61. That is, for these images P1, P30, and P61, the process is performed to adopt the maximum brightness for each pixel position. As a result of the brightness calculation process, image PA' does not include the ground shape portion. In other words, the ground shape disappears. 【0063】 In this example, the ground shape disappears in the case of the image set GS', which consists of 3 images. Therefore, the minimum number of images in an image set when the ground shape disappears is "3". Based on this minimum number "3" minus "1", which is "2", the maximum ground length is calculated using the above formula (1). 【0064】 In the process described with reference to Figures 13 and 14, the minimum number of images is determined by determining whether or not the ground contact shape has disappeared for each image and repeating this process. Figure 15 is a flowchart showing the process of determining the minimum number of images in an image set in the image set construction unit 35. In Figure 15, first, the initial number of images is set (step ST41). 【0065】 The brightness calculation processing unit 36 ​​performs brightness calculation on the set of images with the set initial number of images (step ST42). Based on the result of the brightness calculation processing by the brightness calculation processing unit 36, it is determined whether or not the ground shape has disappeared (step ST43). 【0066】 If the result of the determination in step ST43 is that the ground contact shape does not disappear (No in step ST43), the number of images is increased by one (step ST44), and the brightness calculation processing unit 36 ​​performs brightness calculation processing on the increased number of image sets (step ST42). Thereafter, the brightness calculation processing is performed in the same manner, increasing the number of images by one each time. 【0067】 If the determination in step ST43 indicates that the grounding shape has disappeared (Yes in step ST43), the maximum grounding length is determined by formula (1) above, based on the current number of sheets minus one sheet (step ST45). 【0068】 (Amount of wrapping) Here, we will explain the appropriate amount of wrapping when constructing an image set. Figure 16 is a diagram illustrating the definition of the amount of wrapping. The center of contact with the ground contact shape portion CA61 of the image to be evaluated P61 is defined as the reference center CeS. The center of contact with the ground contact shape portion of images other than the image to be evaluated P61 is defined as the reference center CeC. The circumferential distance of the tire from the reference center CeS to the reference center CeC is defined as the amount of wrapping. In Figure 16, the amount of wrapping between the image to be evaluated P61 and image P60 is LP1, and the amount of wrapping between the image to be evaluated P61 and image P1 is LP2. 【0069】 The image set construction unit 35 constructs the image set GS3 such that the wrapping amounts LP1 and LP2 satisfy the following equation (2). 0 [mm] < Wrapping amount ≤ (Maximum contact length / 2) [mm] ... (2) 【0070】 In equation (2) above, if the wrapping amount is 0 [mm], it is equivalent to analyzing a single-shot image of the ground surface, making it difficult to improve the accuracy of the analysis. Furthermore, if the wrapping amount exceeds (maximum ground length / 2), i.e., half of the maximum ground length, the central part of the ground shape will be incorrectly identified as ungrounded. This will be explained with reference to Figures 17 and 18. 【0071】 Figure 17 illustrates the case where the wrapping amount is within half of the maximum contact length. When the wrapping amount is within half of the maximum contact length, the reference contact center CeS of the evaluation image P61 is centered, and all the contrast contact centers CeC of all images are located within the range of the contact length Wr in the circumferential direction of the tire. Therefore, for the first image set, the first set of images GS1, if the maximum brightness is selected from all images at each pixel position, the resulting image PA will have a contact shape that is half of the maximum contact length. In other words, a contact shape that is at least half of the maximum contact length can be obtained. Similarly, for the second image set, the second set of images GS2, if the maximum brightness is selected from all images at each pixel position, the resulting image PB will have a contact shape that is half of the maximum contact length. In other words, a contact shape that is at least half of the maximum contact length can be obtained. By superimposing the resulting image PA and the resulting image PB, an appropriate and correct contact shape image KG can be obtained. 【0072】 Figure 18 illustrates the case where the wrapping amount exceeds half of the maximum contact length. When the wrapping amount exceeds half of the maximum contact length, with respect to the reference contact center CeS of the evaluation image P61, the comparative contact center CeC in image P1 is located outside the range of the contact length Wr in the tire circumferential direction. The distance between the reference contact center CeS and the comparative contact center CeC in image P1 is the distance obtained by adding a distance α (α is a positive real number, the same applies hereafter) to half of the maximum contact length (Wr / 2). Therefore, for the first image set, the first set of images GS1, if the maximum brightness is selected for each pixel position from all images, the resulting image PA' will have a contact shape of half the maximum contact length at a position α away from the contact center Ce. 【0073】 For the second set of images, GS2, if the maximum brightness is selected for each pixel position from all images, the resulting image PB will have a grounding shape that is half the maximum grounding length, similar to the case in Figure 17. In other words, a grounding shape that is at least half the maximum grounding length can be obtained. 【0074】 The ground shape image KGb obtained by superimposing the resulting image PA' and the resulting image PB incorrectly identifies the grounding center as ungrounded, causing the ground shape to disappear at a distance α from the grounding center Ce. Therefore, a correct ground shape image cannot be obtained. Accordingly, it is necessary to construct an image set such that the wrapping amount satisfies equation (2) above. 【0075】 Converting the above wrapping amount into the number of images results in the following equation (3). 1 < Number of images ≤ (Maximum contact length / 2) [mm] / (Tire speed [mm / sec] / Frame rate [frames / sec]) ... (3) 【0076】 According to equation (3), if there is only one image, it is equivalent to analyzing a single-shot image of the ground contact surface, making it difficult to improve the accuracy of the analysis. Furthermore, if the number of images exceeds the value on the right side of equation (3), the center of contact may be misidentified as non-contact, reducing the accuracy of the analysis. 【0077】 If the number of images is within the range given by equation (3), it is possible to obtain images of the ground surface in which water (i.e., areas with high brightness) flows into various parts of the ungrounded area. By constructing such an image set and performing brightness calculation processing S36 followed by binarization processing S37, water splashes can be reliably identified as ungrounded. This improves the accuracy of the ground shape analysis. 【0078】 (Remove background image) Figure 19 illustrates the process of deleting the background image in the ground shape calculation unit 38. The ground shape image KG shown in Figure 19 is an image obtained by superimposing the first binary image G1 and the second binary image G2 in the ground shape calculation process S38, as described above. The ground shape image KG includes background images B1 and B2. Therefore, background images B1 and B2 are deleted by the following process. 【0079】 In other words, in Figure 1, the road surface 11 is photographed by the camera 15 before the tire passes through the shooting area, and this is used as the background image BG1. That is, an image in which the tire is not visible is adopted as the background image BG1. The background image BG1 is subjected to binarization processing in the same manner as the binarization processing S37 by the binarization processing unit 37 to obtain the binary image BG2. In other words, in this binarization processing, the pixels that make up the image are set to 256 gradations from 0 to 255, with pixels between 0 and 80 gradations being set to black, and pixels between 81 and 255 gradations being set to white. 【0080】 By subtracting the binary image BG2 from the ground shape image KG, the portions corresponding to the background images B1 and B2 are removed. It is preferable to perform noise reduction at this stage. Noise reduction is a process that removes clusters of black pixels as noise. A threshold is set for the occupied area of ​​black pixels, and clusters of black pixels with an occupied area below this threshold are identified as noise and removed. Through this process, the ground shape image SK is obtained. 【0081】 (Summary of tire contact patch shape analysis equipment) Figure 20 is a diagram illustrating a comparative example and an embodiment in comparison. In Figure 20, in the comparative example, a single image P138, not a continuous image, but a single shot of the ground surface image taken by camera 15, is used for analysis. In this comparative example, when water splashes occur at the dashed line H10 on the kicking side of the ground contact shape, the water splashes at the dashed line H10 in the calculated image SKa of the ground contact shape are determined to be the ground contact area. 【0082】 In contrast, in this embodiment, a continuous image consisting of 252 images from image P1 to image P252 is used as the analysis target, and among the continuous image, image P138 is used as the image to evaluate the contact shape. In this embodiment, even if water splashes occur in the dashed line H1 portion on the push-off side of the contact shape, there is nothing in the dashed line H1 portion of the calculated contact shape image SK. Therefore, the water splashes are correctly determined to be non-contact areas. As described above, according to this embodiment, by using a continuous image as the analysis target, the contact shape of the tire can be analyzed even in the case of high-speed driving where water splashes occur. 【0083】 (Method for analyzing tire contact patch shape) The tire contact patch shape analysis device described above can implement the following tire contact patch shape analysis method. Specifically, the method includes: an image acquisition step of acquiring a sequence of images which are a target image and a sequence of images which are consecutive time series images before and after it, for the contact surface on a wet road surface; an image set construction step of constructing first and second image sets containing multiple images from the sequence of images acquired in the image acquisition step; a brightness calculation processing step of calculating the brightness of multiple images which are included in the first and second image sets constructed in the image set construction step, and obtaining first and second result images which are the calculation results for each of the image sets; a binarization processing step of performing a binarization process based on a predetermined threshold on the first and second result images obtained by the calculation processing in the brightness calculation processing step, respectively, to obtain first and second binary images; and a ground shape calculation step of superimposing the first binary image and the second binary image obtained by the binarization processing in the binarization processing step to determine the ground shape, wherein the first image set consists of the target image and the sequence of images which are before it, and the second image set consists of the target image and the sequence of images which are after it. This tire contact patch shape analysis method allows for the analysis of the tire's contact patch shape during high-speed driving where water spray is generated. 【0084】 This disclosure encompasses the following inventions: Invention [1] An image acquisition unit acquires a sequential image of the tire contact surface on a wet road surface, which is the image to be evaluated and the continuous time-series images before and after it. An image set construction unit constructs first and second image sets containing multiple images from the sequence of images acquired by the image acquisition unit, A brightness calculation processing unit calculates the brightness of multiple images included in the first and second image sets, respectively, constructed by the image set construction unit, and obtains first and second result images, which are the calculation results for the first and second image sets, respectively. A binarization processing unit performs a binarization process based on a predetermined threshold on the first and second result images obtained by the calculation processing of the luminance calculation processing unit to obtain first and second binary images, A ground shape calculation unit that calculates the ground shape by superimposing the first binary image and the second binary image obtained by the binarization process of the aforementioned binarization processing unit, Includes, The first image set is a set consisting of the image to be evaluated and the preceding time-series images, The tire contact patch shape analysis device is a set of images comprising the evaluation target image and subsequent time-series images, wherein the second image set is a set of images comprising the evaluation target image and subsequent time-series images. invention[2] The system includes a road surface plate which is the wet road surface on which the tire being analyzed makes contact, a road surface drive unit which drives the road surface plate to move relative to the tire, and a camera which photographs the contact surface of the tire. The image acquisition unit acquires the continuous images using the camera. A tire contact shape analysis device according to the invention [1]. Invention [3] The luminance calculation processing unit is, A tire contact patch shape analysis device according to invention [1] or invention [2], wherein the maximum brightness is adopted for each pixel position for each of the first and second image sets, and the results of this adoption are used as the first and second result images. invention [4] The aforementioned image set construction unit, The same brightness calculation process as the brightness calculation process performed by the brightness calculation processing unit is applied to the first image set and the second image set, and the minimum number of image sets at which the grounding shape disappears is determined, and the maximum grounding length is defined by equation (1). A tire contact shape analysis device according to any one of the inventions [1] to [3], wherein the contact center of the image to be evaluated is defined as the reference contact center, the contact center of images other than the image to be evaluated is defined as the comparison contact center, the tire circumferential distance from the reference contact center to the comparison contact center is defined as the wrapping amount, and the first and second image sets are defined such that the wrapping amount satisfies equation (2). Maximum contact length = (tire speed / frame rate) × (minimum number of treads - 1) ... (1) 0 < Wrapping amount ≤ (Maximum ground contact length / 2) ... (2) invention [5] The grounding shape calculation unit is, A tire contact shape analysis device according to any one of the inventions [1] to [4], wherein an image in which the tire is not visible is used as a background image, and the binary image of the background image is subtracted from the superposition result image of binary images obtained by the binarization processing of the binarization processing unit. invention [6] The image acquisition step involves obtaining a sequential image of the tire contact patch on a wet road surface, which is the image to be evaluated and the consecutive time-series images before and after it. An image set construction step in which a first and second image set containing multiple images is constructed from the sequential images acquired in the image acquisition step, A brightness calculation processing step is performed to calculate the brightness of multiple images contained in the first and second image sets constructed in the aforementioned image set construction step, and to obtain first and second result images which are the calculation results for the first and second image sets respectively. A binarization step is performed on the first and second result images obtained by the calculation process of the brightness calculation step, respectively, to obtain first and second binary images by performing a binarization process based on a predetermined threshold, A ground shape calculation step involves superimposing the first binary image and the second binary image obtained by the binarization process in the aforementioned binarization process to determine the ground shape, Includes, The first image set is a set consisting of the image to be evaluated and the preceding time-series images, The tire contact shape analysis method wherein the second image set comprises the evaluation target image and subsequent time-series images. [Explanation of symbols] 【0085】 6 motors 7 Motor control device 10 Imaging device 11 Road board 12 Water film 15 Cameras 20. Tire contact patch analysis device 21 Input section 22 Display section 30 Processing Unit 31 Processing Unit 32 Storage section 33 Road surface drive unit 34 Image acquisition unit 35 Image Set Construction Section 36. Brightness calculation processing unit 37. Binarization Processing Unit 38 Grounding shape calculation section 60 tires 61 Ground plane

Claims

[Claim 1] An image acquisition unit acquires a sequential image of the tire contact surface on a wet road surface, which is the image to be evaluated and the continuous time-series images before and after it. An image set construction unit constructs first and second image sets containing multiple images from the sequence of images acquired by the image acquisition unit, A brightness calculation processing unit calculates the brightness of multiple images included in the first and second image sets, respectively, constructed by the image set construction unit, and obtains first and second result images, which are the calculation results for the first and second image sets, respectively. A binarization processing unit performs a binarization process based on a predetermined threshold on the first and second result images obtained by the calculation processing of the luminance calculation processing unit to obtain first and second binary images, A ground shape calculation unit that calculates the ground shape by superimposing the first binary image and the second binary image obtained by the binarization process of the aforementioned binarization processing unit, Includes, The first image set is a set consisting of the image to be evaluated and the preceding time-series images, The tire contact patch shape analysis device is a set of images comprising the evaluation target image and subsequent time-series images, wherein the second image set is a set of images comprising the evaluation target image and subsequent time-series images. [Claim 2] The system includes a road surface plate which is the wet road surface on which the tire being analyzed makes contact, a road surface drive unit which drives the road surface plate to move relative to the tire, and a camera which photographs the contact surface of the tire. The image acquisition unit acquires the continuous images using the camera. The tire contact shape analysis device according to claim 1. [Claim 3] The luminance calculation processing unit is, The tire contact patch shape analysis apparatus according to claim 1 or claim 2, wherein the maximum brightness is adopted for each pixel position for each of the first and second image sets, and the results of this adoption are used as the first and second result images. [Claim 4] The aforementioned image set construction unit, The same brightness calculation process as the brightness calculation process performed by the brightness calculation processing unit is applied to the first image set and the second image set, and the minimum number of image sets at which the grounding shape disappears is determined, and the maximum grounding length is defined by equation (1). The tire contact shape analysis device according to claim 3, wherein the contact center of the image to be evaluated is defined as the reference contact center, the contact center of images other than the image to be evaluated is defined as the comparison contact center, the tire circumferential distance from the reference contact center to the comparison contact center is defined as the wrapping amount, and the first and second image sets are defined such that the wrapping amount satisfies equation (2). Maximum contact length = (tire speed / frame rate) × (minimum number of treads - 1) ... (1) 0 < Wrapping amount ≤ (Maximum contact length / 2) ... (2) [Claim 5] The grounding shape calculation unit is, The tire contact shape analysis apparatus according to claim 1, wherein an image in which the tire is not visible is used as a background image, and the binary image of the background image is subtracted from the superposition result image of binary images obtained by the binarization processing of the binarization processing unit. [Claim 6] The image acquisition step involves obtaining a sequential image of the tire contact patch on a wet road surface, which is the image to be evaluated and the consecutive time-series images before and after it. An image set construction step in which a first and second image set containing multiple images is constructed from the sequential images acquired in the image acquisition step, A brightness calculation processing step is performed to calculate the brightness of multiple images contained in the first and second image sets constructed in the aforementioned image set construction step, and to obtain first and second result images which are the calculation results of the first and second image sets respectively. A binarization step is performed to obtain first and second binary images by performing a binarization process based on a predetermined threshold on the first and second result images obtained by the calculation process of the brightness calculation step, A ground shape calculation step is performed by superimposing the first binary image and the second binary image obtained by the binarization process in the aforementioned binarization process to determine the ground shape, Includes, The first image set is a set consisting of the image to be evaluated and the preceding time-series images, The tire contact shape analysis method wherein the second image set is a set consisting of the evaluation target image and subsequent time-series images.

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