CN112747685A

CN112747685A - Grain depth detection system and method thereof

Info

Publication number: CN112747685A
Application number: CN201911053006.4A
Authority: CN
Inventors: 许智渊
Original assignee: Nanning Fugui Precision Industrial Co Ltd
Current assignee: Nanning Fulian Fugui Precision Industrial Co Ltd
Priority date: 2019-10-31
Filing date: 2019-10-31
Publication date: 2021-05-04

Abstract

The texture depth detection system is characterized by comprising a texture copying material, a light-emitting unit, an image capturing unit and a processing unit. The grain copying material is used for presenting the grain expression of the object to be detected. The light emitting unit is used for irradiating the grain replication material. The image capturing unit is used for obtaining a grain image corresponding to the grain copying material. And the processing unit obtains a plurality of line depth values corresponding to the object to be detected according to the line images. The invention also discloses a grain depth detection method. Through the texture depth detection system and the method thereof, a driver can quickly obtain the depth values of all the tire textures, so as to judge the wear condition of the tire textures, and further judge whether the tire positioning is normal according to the distribution of the tire textures, so as to improve the driving safety.

Description

Grain depth detection system and method thereof

Technical Field

The present invention relates to a system for detecting a depth of a grain, and more particularly, to a system and a method for detecting a depth of a grain of a tire.

Background

Many of the traffic accidents are caused by tire burst or uncontrolled tire slip, and the reasons for these problems are usually insufficient tire pressure or insufficient tread depth, and the current methods for checking the tread depth include contact-type measurement and non-contact-type measurement. The contact measurement method is to measure the tread depth by directly contacting the tread and the groove bottom with a measuring ruler or a mechanical measuring meter, but the manual measurement of the tread depth can only detect a single point, which may cause erroneous judgment. The non-contact measurement method uses laser, infrared or ultrasonic techniques to detect the tire streak, but the laser ranging cost is too high, and the infrared or ultrasonic measurement error is larger. Therefore, how to provide a simple and fast method for detecting the tire tread with a large sampling area is a problem to be solved at present.

Disclosure of Invention

In view of the above, a system and method for detecting a depth of a tread is needed, which can quickly inform a driver of a change in a tire condition.

The invention provides a texture depth detection system which is characterized by comprising a texture copying material, a light-emitting unit, an image capturing unit and a processing unit. The grain copying material is used for presenting the grain expression of the object to be detected. The light emitting unit is used for irradiating the grain replication material. The image capturing unit is used for obtaining a grain image corresponding to the grain copying material. The processing unit is used for obtaining a plurality of line depth values corresponding to the object to be detected according to the line images.

The invention also provides a texture depth detection method, which is characterized by comprising the following steps: the grain expression of the object to be detected is presented through the grain copying material; irradiating the grain replication material through a light emitting unit; obtaining a grain image corresponding to the grain replication material through an image capturing unit; and obtaining a plurality of texture depth values corresponding to the object to be detected according to the texture image.

According to an embodiment of the present invention, the processing unit further establishes a gray level comparison table corresponding to the plurality of texture depth values, obtains a gray level image corresponding to the texture image, and obtains the plurality of texture depth values of the object to be measured according to the gray level image and the gray level comparison table.

According to another embodiment of the present invention, the processing unit further increases the contrast of the grayscale image to obtain a contrast-enhanced image, obtains a grayscale distribution of the contrast-enhanced image, and obtains a plurality of texture depth values of the object to be measured according to a plurality of modes in the grayscale distribution and the grayscale comparison table, wherein the texture replication material includes a light-transmissive deformation material.

According to another embodiment of the present invention, the texture replication material includes a light-permeable deformable material, the object to be measured is a tire, and the texture is expressed as a tire tread.

According to another embodiment of the present invention, after the object to be measured is located above the grain replication material, the light emitting unit and the image capturing unit are enabled by a switch.

Drawings

Fig. 1 is a block diagram of a texture depth detection system according to an embodiment of the invention.

Fig. 2 is a flowchart of a texture depth detection method according to an embodiment of the invention.

Description of the main elements

Grain depth detection system 100

Switch 110

Light emitting unit 120

Image capturing unit 130

Processing unit 140

Step flows S201-S206

Detailed Description

Further areas of applicability of the present systems and methods will become apparent from the detailed description provided hereinafter. It should be understood that the following detailed description and specific examples, while indicating exemplary embodiments of the texture depth detection system and method, are intended for purposes of illustration only and are not intended to limit the scope of the invention.

Fig. 1 is a block diagram of a texture depth detection system according to an embodiment of the invention. The texture depth detection system 100 at least includes a switch 110, a light emitting unit 120, an image capturing unit 130 and a processing unit 140. The switch 110 may be, for example, an infrared interrupter, and is used to determine whether the object to be tested has left its grain expression on the grain replication material, so as to send out a signal to enable the light emitting unit 120 and the image capturing unit 130. For example, the infrared interrupter is disposed over the grain replication material to determine whether the object is located over the grain replication material. Or, a weight sensor is arranged below the object to be detected to judge whether the object to be detected is pressed above the grain copying material, and the like. The light emitting unit 120 is any device capable of emitting visible light, such as a lamp, for irradiating the texture replication material. The grain copying material is a light-permeable deformation material and is used for copying grains of the object to be detected. The image capturing unit 130 is a camera lens for capturing an image of the grain replica material. The processing unit 140 can be implemented in various ways, such as with dedicated hardware circuits or general purpose hardware (e.g., a single processor, multiple processors with parallel processing capability, a graphics processor, or other processor with computing capability), and provides functions described hereinafter when executing program code or software.

According to an embodiment of the present invention, when the object to be measured is a tire, the texture replication material may be laid on a plane in advance, an infrared interrupter is disposed above the texture replication material, and the light emitting unit 120 and the image capturing unit 120 are disposed under the texture replication material. When the tire is placed on the texture replication material, the texture replication material will be depressed by the weight of the tire to present the tread of the tire. Moreover, since the tire blocks the emission source of the infrared interrupter disposed above the texture replication material, the infrared interrupter outputs the start signal to enable the light emitting unit 120 to emit light to irradiate the texture replication material due to no infrared signal being received, and the texture replication material exhibits different light transmittance due to the light irradiation. Then, the image capturing unit 130 captures images of the grain replication materials having different light transmittances according to the start signal, and transmits the captured images to the processing unit 140.

After obtaining the image of the grain copy material, the processing unit 140 further converts the image into a gray scale image and counts the number of each gray scale value. In order to avoid additional calculation procedures, the edges of the sipes can be identified in advance after the gray-scale image is obtained, and only the portion with the sipes is captured, so that the operation speed is increased. Furthermore, in order to improve the identification rate of the tire tread, before counting the number of each gray-scale value, the contrast of the gray-scale image can be improved, so that the texture characteristics on the texture copy material are more obvious. After the number of each gray level value is obtained, the mode of the first few names is taken as the tire grain characteristics, and the health condition of the tire is judged according to the tire grain distribution, so that whether the tire has the problem of abnormal positioning can be judged. The gray level comparison table recorded with the texture depth value corresponding to each gray level is pre-established and stored in a memory (not shown) for the processing unit 140 to use as the basis for texture depth determination. In addition, the processing unit 140 may also store the depth value of the texture and the distribution of the texture obtained each time for the driver to track for a long time.

Fig. 2 is a flowchart of a texture depth detection method according to an embodiment of the invention. First, in step S201, a gray level comparison table in which the texture depth value corresponding to each gray level is recorded is established. In step S202, the object to be measured is located above the grain replication material, so that the grain replication material replicates the grain expression of the object to be measured due to the pressing weight of the object to be measured. In step S203, the switch 110 disposed above the grain replication material determines that the object to be measured is located above the grain replication material, outputs an enable signal to enable the light emitting unit 120 to irradiate the grain replication material, and enables the image capturing unit 130 to obtain a grain image corresponding to the grain replication material. In step S204, the processing unit 140 converts the texture image into a grayscale image and increases the contrast of the grayscale image. In step S205, the processing unit 140 counts the number of each gray level value, and takes the mode of the first few names as the fetal streak feature. In step S206, the depth values and distribution of the sipes corresponding to the sipes are obtained according to the sipe characteristics and the grayscale table.

It is to be noted that although the above-described method has been described on the basis of a flowchart using a series of steps or blocks, the present invention is not limited to the order of the steps, and some steps may be performed in an order different from that of the rest of the steps or the rest of the steps may be performed simultaneously. Moreover, those skilled in the art will appreciate that the steps illustrated in the flow chart are not exclusive, that other steps of the flow chart may be included, or that one or more steps may be deleted without affecting the scope of the invention.

In summary, according to the texture depth detection system and method provided by some embodiments of the present invention, the texture features are left on the texture copy material by the object to be detected, and the light-emitting unit irradiates the texture copy material to generate the situation of different light transmittance, and then the image of the texture copy material is captured and subjected to gray scale statistics and analysis to obtain the distribution of the tire treads, so that the driver can know the health condition of the tire at a lower cost.

It should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A texture depth detection system, comprising:

the grain copying material is used for presenting the grain expression of the object to be detected;

a light emitting unit for irradiating the grain replication material;

an image capturing unit for obtaining a grain image corresponding to the grain replication material; and

and the processing unit is used for obtaining a plurality of line depth values corresponding to the object to be detected according to the line images.

2. The system of claim 1, wherein the processing unit further establishes a gray level comparison table corresponding to a plurality of depth values of the texture, obtains a gray level image corresponding to the texture image, and obtains a plurality of depth values of the texture of the object according to the gray level image and the gray level comparison table.

3. The system of claim 2, wherein the processing unit further increases a contrast of the grayscale image to obtain a contrast-enhanced image, obtains a grayscale distribution of the contrast-enhanced image, and obtains the plurality of texture depth values of the object according to a plurality of modes in the grayscale distribution and the grayscale comparison table.

4. The system of claim 1, wherein the texture replication material comprises a light transmissive deformable material, the object to be tested is a tire, and the texture is expressed as a tire tread.

5. The system of claim 1, further comprising:

and the switch is used for judging that the object to be detected is positioned above the grain copying material and enabling the light-emitting unit and the image capturing unit.

6. A method for detecting the depth of a grain is characterized by comprising the following steps:

the grain expression of the object to be detected is presented through the grain copying material;

irradiating the grain replication material through a light emitting unit;

obtaining a grain image corresponding to the grain replication material through an image capturing unit; and

and obtaining a plurality of texture depth values corresponding to the object to be detected according to the texture image.

7. The method of claim 6, wherein the step of obtaining the plurality of texture depth values corresponding to the object to be tested according to the texture image further comprises:

establishing a gray-scale value comparison table corresponding to a plurality of texture depth values;

obtaining a gray scale image corresponding to the grain image; and

and obtaining a plurality of line depth values of the object to be detected according to the gray scale image and the gray scale value comparison table.

8. The method of claim 7, wherein the step of obtaining the plurality of depth texture values of the object to be tested according to the grayscale image and the grayscale table further comprises:

improving the contrast of the gray-scale image to obtain a contrast enhanced image;

obtaining the gray-scale value distribution of the contrast enhanced image; and

and obtaining a plurality of line depth values of the object to be detected according to a plurality of modes in the gray scale value distribution and the gray scale value comparison table.

9. The method of claim 6, wherein the texture replication material comprises a light transmissive deformable material, the object to be tested is a tire, and the texture is expressed as a tire tread.

10. The method of claim 6, wherein the steps further comprise:

and after the object to be detected is positioned above the grain copying material, enabling the light-emitting unit and the image capturing unit through a switch.