Intelligent target system for vertical target density test based on optical vision positioning measurement

Abstract

The invention relates to an intelligent target system for a vertical target density test based on optical vision positioning measurement, and solves the problems existing in current vertical target density measurement. Comprising a high-quality imaging system, a high-speed image acquisition, storage and transmission system, a calculation and analysis system and a report system, the high-quality imaging system comprises a camera module, the trigger controller issues a photographing instruction to the camera module, and the camera module photographs the target plate to obtain a high-quality clear target plate orthographic image and target center calibration; the high-speed image acquisition and storage system is used for acquiring and storing shot target surface image data before and after each shot; the calculation and analysis system performs geometric distortion correction on the acquired image, automatically extracts and identifies the bullet hole and quickly calculates the coordinates of the bullet hole; and the report subsystem is used for generating, displaying and exporting the analyzed data. The method can greatly reduce the labor intensity of workers, improve the labor efficiency, improve the data precision and reduce the safety risk, and can also be expanded to other similar tests.

Description

Technical Field

[0001] This invention belongs to the field of target range testing technology and relates to an intelligent target system for target density testing based on optical visual positioning measurement. Background Technology

[0002] Target accuracy testing involves measuring the two-dimensional coordinates of bullet holes on a target and calculating and correcting firing accuracy. Based on relevant literature and testing standards, the following methods are primarily used for target accuracy measurement: 1) Manual measurement method: This method involves manually inspecting the target after firing to find bullet holes, marking them, and measuring them with tape measure and calipers. This is currently the most reliable and commonly used method. 2) Photographic measurement method: The target is photographed manually using a high-precision camera after the cannon is fired, and the images are then imported into a computer to calculate the location of the bullet holes. 3) Sky-view optical measurement method: Based on the initial velocity of the projectile and the distance to the target, the shooting time is preset in advance. At the moment the projectile reaches the target, the lens captures the change in light flux caused by the projectile passing through. The dual lenses are used for Z-shaped cross measurement to calculate the target penetration coordinates. 4) Acoustic target shock wave measurement method: measures the shock wave in the air when a projectile is in flight, using a multi-point triangulation positioning method.

[0003] (2) Analysis of advantages and disadvantages Comparing the available target density measurement methods, each has its own advantages and disadvantages: 1) Manual measurement is a traditional method. Its advantages are accuracy and its disadvantages are low work efficiency. 2) Photogrammetry: Advantages: Computerized processing, accurate; Disadvantages: Low work efficiency, small processing capacity. 3) Sky-canopy optical measurement: It is fast, but it needs to be set up a few meters away from the target, which can easily cause equipment damage. It requires manual measurement of the target center point, the distance between the equipment and the target surface, and correction of multiple manual measurement data in advance. 4) Acoustic target shock wave measurement: High speed, but continuous firing is not possible. It needs to be positioned several meters away from the target, which can easily damage the sensor. Like sky-canopy target measurement, manual measurement data correction is required. Summary of the Invention

[0004] This invention provides an intelligent target system for target density testing based on optical vision positioning measurement, which solves the problems existing in current target density measurement.

[0005] This invention is achieved through the following technical solutions: A smart target system for testing the density of standing targets based on optical vision positioning measurement mainly consists of four parts: a high-quality imaging system, a high-speed image acquisition, storage and transmission system, a dedicated computing and analysis system, and a reporting system. 1) The first part is the high-quality imaging system: mainly consisting of a trigger controller that sends a shooting command to the camera and a camera module that takes a picture of the target board. The function of this system is to obtain a high-quality, clear orthogonal image of the target board and to calibrate the bullseye. 2) The second part is the high-speed image acquisition and storage system: It mainly consists of a wireless data transmission module or wired transmission, which connects the camera and the industrial control computer and transmits the captured data to the industrial control computer in a timely manner. The industrial control computer acquires and stores the target board photos. The function of this system is to acquire and store the target surface image data before and after each shot captured in the first part. 3) The third part of the calculation and analysis system: corrects the geometric distortion image of the target, the bullet hole detection module quickly identifies the bullet holes on the target plate, and the bullet hole 2D data position calculation module calculates the xy coordinates of the bullet hole on the target plate. The function of this system is to correct the geometric distortion of the image acquired in the second part, automatically extract and identify the bullet holes, and quickly calculate the bullet hole coordinates.

[0006] 4) The fourth part is the report subsystem: It mainly consists of a report generation module and an export module. The function of this system is to generate, display and export the data after the analysis in the third part.

[0007] This system establishes corresponding calculation relationships between the world coordinate system, camera coordinate system, image coordinate system, and pixel coordinate system, thereby achieving accurate measurement.

[0008] 1) From world coordinate system to camera coordinate system The transformation from the world coordinate system to the camera coordinate system includes rotation and translation (rigid body transformation). First, let's introduce the rotation process. Figure 3 Model for rotating the world coordinate system about the z-axis: from Figure 3 As can be seen from this, for a point in the world coordinate system In its corresponding camera coordinate system The coordinates are Because of the rotation around the z-axis, .

[0009] Writing the matrix in matrix form, we get: The 3x3 transformation matrix is ​​called... .

[0010] Similarly, the transformation matrices for rotation about the x-axis and y-axis can be obtained. The total rotation matrix is... Add a translation amount to the rotated base. The coordinates after translation can then be obtained.

[0011] In summary, the transformation from the world coordinate system to the camera coordinate system can be obtained: 2) From camera coordinate system to image coordinate system The transformation from the camera coordinate system to the image coordinate system satisfies the pinhole imaging model, which can be obtained using the simple principle of similar triangles: the transformation from the camera coordinate system to the image coordinate system is a conversion from 3D to 2D, belonging to the perspective projection relationship. from Figure 4 It can be seen that, , where f is the focal length. Through transformation, we can obtain... From this, we can obtain its augmented form. .

[0012] 3) From image coordinate system to pixel coordinate system Since the image coordinate system and the pixel coordinate system lie in the same plane, the difference between them lies in the position and unit of the origin. The origin of the pixel coordinate system is at the upper left corner of the image coordinate system, and the unit of the pixel coordinate system is pixels. Figure 5 As shown.

[0013] pass The relational expression yields the transformation from image coordinate system to pixel coordinate system as follows: .

[0014] Now that the transformation relationships between the four coordinate systems are known, the relationship from the world coordinate system to the pixel coordinate system can be determined, thus obtaining the bullet hole position coordinate information. Figure 6 This is a diagram showing the transformation between different coordinate systems.

[0015] This invention can not only greatly reduce the intensity of manual labor, improve labor efficiency, improve data accuracy, and reduce safety risks, but it can also be extended to other similar experiments. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the working principle of an intelligent target system for testing the density of upright targets based on optical vision positioning measurement. Figure 2 This is a schematic diagram illustrating the working principle of distortion correction. Figure 3 World coordinate system rotation model about the z-axis; Figure 4 From camera coordinate system to image coordinate system; Figure 5 Image coordinate system to pixel coordinate system Figure 6 Transformation diagrams for different coordinate systems. Detailed Implementation

[0017] This invention is designed for use in the density testing of small-caliber artillery shells on targets, eliminating the safety hazards of manual target measurement and improving measurement efficiency. It is an intelligent target system with real-time data acquisition, automatic processing, and remote display, thereby improving measurement accuracy and efficiency.

[0018] Figure 1 The diagram shows the working principle of an intelligent target system for target density testing based on optical vision positioning measurement. The components are a gun, a target, an optical camera, a communication antenna, a receiver, and a computer terminal. Figure 2 This is a diagram illustrating the working principle of distortion correction.

[0019] 1) Place a high-definition industrial camera on one side of the cannon muzzle and at a certain distance from the target (the distance is calculated based on the lens and resolution), focus on the target, and use a calibration plate to correct the image to obtain a high-quality, clear orthogonal image of the target plate. 2) Establish a target plate measurement coordinate system based on the orthophoto, with the horizontal X-axis and the vertical Y-axis, and the origin being the target plate center, and establish a target plate measurement and analysis template.

[0020] 3) After the device fires the shell, the target image is captured remotely by a person and transmitted to the computing and analysis system terminal in the gun position control room via a wireless transmission module. 4) Based on the previously established automatic bullet hole identification and deep learning algorithm, the software automatically calculates the two-dimensional coordinates and number of bullet holes, and quickly generates a results report.

Claims

1. An intelligent target system for stand target density testing based on optical vision positioning measurement, characterized in that: It comprises a high-quality imaging system, a high-speed image acquisition storage transmission system, a computing analysis system and a report system. The high-quality imaging system comprises a camera module, a trigger controller, a camera module, a target plate, a high-quality clear target plate front image and a target center calibration. The high-speed image acquisition storage system collects and stores the target surface image data before and after each shot. The computing analysis system corrects the collected images, automatically extracts and identifies the bullet holes and quickly calculates the bullet hole coordinates. The report subsystem generates, displays and exports the analyzed data.

2. The optical vision positioning measurement based vertical target density test intelligent target system according to claim 1, characterized in that: The high-speed image acquisition storage system transmits the shooting data to the industrial computer in time through the wireless data transmission module.

3. The optical vision positioning measurement based vertical target density test intelligent target system according to claim 1, characterized in that: The bullet hole detection module quickly identifies the bullet holes on the target plate, and the bullet hole 2D data position calculation module calculates the x-y coordinates of the bullet holes on the target plate.

4. The optical vision positioning measurement based vertical target density test intelligent target system according to claim 1, characterized in that: The report subsystem comprises a report generation module and an export module.

5. The optical vision positioning measurement based vertical target density test intelligent target system according to claim 1, characterized in that: The target system establishes corresponding calculation relationships among the world coordinate system, the camera coordinate system, the image coordinate system and the pixel coordinate system, thereby realizing accurate measurement.

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