CN110595275A - Digital image-based cannon correcting device and method thereof - Google Patents
Digital image-based cannon correcting device and method thereof Download PDFInfo
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- CN110595275A CN110595275A CN201910735848.1A CN201910735848A CN110595275A CN 110595275 A CN110595275 A CN 110595275A CN 201910735848 A CN201910735848 A CN 201910735848A CN 110595275 A CN110595275 A CN 110595275A
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F41—WEAPONS
- F41F—APPARATUS FOR LAUNCHING PROJECTILES OR MISSILES FROM BARRELS, e.g. CANNONS; LAUNCHERS FOR ROCKETS OR TORPEDOES; HARPOON GUNS
- F41F1/00—Launching apparatus for projecting projectiles or missiles from barrels, e.g. cannons; Harpoon guns
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F41—WEAPONS
- F41G—WEAPON SIGHTS; AIMING
- F41G1/00—Sighting devices
- F41G1/54—Devices for testing or checking ; Tools for adjustment of sights
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/66—Analysis of geometric attributes of image moments or centre of gravity
Abstract
The invention discloses a digital image-based cannon checking device and a digital image-based cannon checking method, wherein the device comprises a gauge plug, an image acquisition module and an image processing module; the image acquisition module is fixed on one end face of the gauge plug; when checking the gun, pushing one end of the gauge plug, which is not provided with the image acquisition module, into the gun barrel outlet and fixing the end of the gauge plug at the gun barrel outlet, and then connecting the image acquisition module with the image processing module in a communication manner; then, image information is acquired by the image acquisition module and is transmitted to the image processing module for digital processing; and finally, the image processing module obtains a gun barrel position deviation value by comparing the cross target shape center coordinates of the images of the environment test twice before and after the environment test, so that intelligent gun calibration is realized. The intelligent gun calibration is realized by utilizing the gauge plug, the image acquisition module and the image processing module, and manual experience and multi-person cooperation are not needed; the automatic and digital gun calibration is realized, the labor input is greatly reduced, and the potential safety hazard of operators is reduced.
Description
Technical Field
The invention relates to the technical field of photoelectric imaging detection, in particular to a digital image-based cannon correction device and a digital image-based cannon correction method.
Background
The infrared thermal imaging sighting device is used as an important component device in a vehicle fire control system and is mainly responsible for target detection, tracking, sighting and the like. The tank vehicle can produce impact, vibration in the use such as traveling, shooting, the optical axis of aiming at the utensil can change, will directly influence the reliability and the hit rate of aiming at the system when serious change. The zero-position walking momentum of the thermal imager directly influences the accuracy of target aiming, so that after the sighting device leaves a factory and is loaded, the zero-position walking momentum of the fire control system is one of important indexes for measuring the performance stability of the sighting device.
In the traditional gun calibration method, an observer observes optical imaging of a gun barrel and guides a gun hand to calibrate the zero position of the gun barrel. The traditional method depends on the experience of observers, has large errors, needs cooperation of multiple persons, has low detection efficiency, and has the potential safety hazard that the cannon barrel accidentally injures the observers. An intelligent school big gun device based on digital image can effectively improve school big gun error, improves detection efficiency and reduces the potential safety hazard.
Disclosure of Invention
The invention provides a digital image-based cannon correction device, which realizes high-precision digital cannon correction.
The invention provides a digital image-based cannon calibration device, which comprises a gauge plug, an image acquisition module and an image processing module; the image acquisition module is fixed on one end face of the gauge plug; when checking the gun, pushing one end of the gauge plug, which is not provided with the image acquisition module, into the gun barrel outlet and fixing the end of the gauge plug at the gun barrel outlet, and then connecting the image acquisition module with the image processing module in a communication manner; then, image information is acquired by the image acquisition module and is transmitted to the image processing module for digital processing; and finally, the image processing module obtains a gun barrel position deviation value by comparing the cross target shape center coordinates of the images of the environment test twice before and after the environment test, so that intelligent gun calibration is realized.
Preferably, the image acquisition module adopts a CCD camera; the image processing module adopts a computer with an image acquisition card.
Preferably, the optical axis of the CCD camera is coaxial with the central axis of the gauge plug and the central axis of the gun barrel.
Preferably, the image acquisition module is fixed on the gauge through a fixed seat; and the positions of the gauge plug and the gun barrel are fixed through a fastener when the gun is calibrated.
On the other hand, the invention also provides a cannon calibration method applied to the cannon calibration device, which comprises the following steps:
step S1, device installation: the gun calibration device is fixedly arranged at the gun outlet of the gun barrel and is connected with the image acquisition module and the image processing module;
step S2, carrying out intelligent gun calibration: acquiring image information through an image acquisition module and transmitting the image information to an image processing module for digital processing to obtain a cross target centroid coordinate; the image processing module obtains a gun barrel position deviation value by comparing the cross target shape center coordinates of the images of the environment test twice before and after, and intelligent gun calibration is realized.
Preferably, the step S2 further includes:
step S21, collecting the image of the target by the image collecting module and transmitting the image to the image processing module, displaying and observing the target by the image processing module, moving the gun barrel to the central area of the target in the image, establishing a pixel space coordinate system, selecting the cross area of the target on the image, and carrying out the centroid point coordinate (X) on the cross area0，Y0) Calculating the centroid point of the reference datum point;
step S22, taking down the gun calibration device, and carrying out environmental test on the vehicle;
step S23, returning to the vehicle initial position after the environmental test is completed, and repeating the step S1;
step S24, collecting the image of the target by the image collecting module and transmitting the image to the image processing module, displaying and observing the target by the image processing module, moving the gun barrel to the central area of the target in the image, establishing a pixel space coordinate system, selecting the cross area of the target on the image, and carrying out the centroid point coordinate (X) on the cross area1，Y1) Calculating;
step S25, comparing the centroid point coordinates (X) obtained in step S21 by the image processing module0，Y0) And the centroid point coordinates (X) obtained in step S241，Y1) Obtaining a deviation value of the gun barrel position;
and step S26, moving the gun barrel so that X0 is equal to X1 and Y0 is equal to Y1, resetting the gun barrel and correcting the guns intelligently.
Preferably, the centroid point coordinate calculation procedures in steps S21 and S24 are as follows:
step a, image preprocessing: calculating an optimal threshold by adopting a maximum variance threshold segmentation method, and segmenting a high-brightness area of the cross target from a background;
step b, extracting a central line of the cross target: continuously removing the image boundary by adopting a morphological corrosion method until only the skeleton is left as a cross-shaped central line;
step c, calculating the cross centroid: and (3) calculating the best fitting straight lines L1 and L2 of the central lines by adopting a least square method, wherein the coordinates of the intersection point of the straight line L1 and the straight line L2 are the coordinates of the centroid point.
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) the intelligent gun calibration is realized by utilizing the gauge plug, the image acquisition module and the image processing module, and manual experience and multi-person cooperation are not needed; the automatic and digital gun calibration is realized, the labor input is greatly reduced, and the potential safety hazard of operators is reduced.
(2) The method is different from the traditional shot correction method, the image is preprocessed by adopting a maximum variance threshold value method, the center line of the cross target is extracted by combining a morphological erosion method, and the centroid coordinate calculation is carried out by adopting a least square method, namely the method realizes the full-digital image processing, and greatly improves the detection precision of the zero-position walking momentum of the sighting telescope in a fire control system.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a schematic structural view of a gun calibration device according to the present invention;
FIG. 2 is a schematic view of the overall structure of the gun calibration device and the gun barrel of the present invention;
FIG. 3 is a schematic view of the morphological etching process of the present invention;
FIG. 4 is a schematic diagram of the target cross target centroid offset according to the present invention.
Detailed Description
Hereinafter, the term "comprising" or "may include" used in various embodiments of the present invention indicates the presence of the invented function, operation or element, and does not limit the addition of one or more functions, operations or elements. Furthermore, as used in various embodiments of the present invention, the terms "comprises," "comprising," "includes," "including," "has," "having" and their derivatives are intended to mean that the specified features, numbers, steps, operations, elements, components, or combinations of the foregoing, are only meant to indicate that a particular feature, number, step, operation, element, component, or combination of the foregoing, and should not be construed as first excluding the existence of, or adding to the possibility of, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
In various embodiments of the invention, the expression "or" at least one of a or/and B "includes any or all combinations of the words listed simultaneously. For example, the expression "a or B" or "at least one of a or/and B" may include a, may include B, or may include both a and B.
Expressions (such as "first", "second", and the like) used in various embodiments of the present invention may modify various constituent elements in various embodiments, but may not limit the respective constituent elements. For example, the above description does not limit the order and/or importance of the elements described. The foregoing description is for the purpose of distinguishing one element from another. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of various embodiments of the present invention.
It should be noted that: if it is described that one constituent element is "connected" to another constituent element, the first constituent element may be directly connected to the second constituent element, and a third constituent element may be "connected" between the first constituent element and the second constituent element. In contrast, when one constituent element is "directly connected" to another constituent element, it is understood that there is no third constituent element between the first constituent element and the second constituent element.
The terminology used in the various embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the various embodiments of the invention. As used herein, the singular forms are intended to include the plural forms as well, unless the context clearly indicates otherwise. Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present invention belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments of the present invention.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1
The embodiment provides a digital image-based artillery checking device, as shown in fig. 1, the device includes a gauge plug 2, an image acquisition module 5 and an image processing module 6; the image acquisition module 5 is fixed on one end face of the gauge plug 2; during gun calibration, pushing and fixing one end of the gauge plug 2, which is not provided with the image acquisition module 5, into a gun outlet of the gun barrel 1, and then performing communication connection between the image acquisition module 5 and the image processing module 6; then, image information is acquired by an image acquisition module 5 and is transmitted to an image processing module 6 for digital processing; and finally, the image processing module 6 obtains a gun barrel position deviation value by comparing the coordinates of the cross target centroids of the two images, so that intelligent gun calibration is realized.
In this embodiment, the image acquisition module 5 adopts a CCD camera; the image processing module 6 adopts a computer with an image acquisition card.
In this embodiment, the device further comprises a fixing seat 4 and a fastening piece 3, wherein the CCD camera is fixed on one end face of the gauge plug 2 through the fixing seat 4; the position of the gauge plug 2 and the gun barrel 1 is fixed by a fastener 3 when the gun is calibrated. And the optical axis of the CCD camera is coaxial with the central axes of the gauge plug and the gun barrel so as to ensure the detection accuracy.
The working principle of the cannon calibration device of the embodiment is as follows:
when checking the cannon, the cannon checking device is pushed into the cannon orifice, the image information is collected by the CCD camera and is transmitted to the computer, and the coordinates (X) of the centroid point of the cross target are obtained0，Y0) After the environmental test, the cannon correcting device is pushed into the cannon pipe orifice again, image information is collected by the CCD camera and is transmitted to the computer, and the coordinates (X) of the centroid point of the cross target are obtained1，Y1). And the computer obtains the deviation value of the gun barrel position by comparing the coordinates of the cross target shape heart of the images of the environment before and after the environment test.
Example 2
Based on the foregoing embodiment 1, this embodiment proposes a digital image-based cannon calibration method, which includes the following steps:
step one, device installation
The gun calibration device is fixedly arranged at the gun outlet of the gun barrel, and then is connected with the image acquisition module and the image processing module (in a wired or wireless communication way), so that the stability of the equipment is ensured; as shown in fig. 2.
Step two, carrying out intelligent gun calibration
Acquiring image information through an image acquisition module and transmitting the image information to an image processing module for digital processing to obtain a cross target centroid coordinate; the image processing module obtains the position deviation value of the gun barrel by comparing the coordinates of the cross target centroid of the two images, and intelligent gun calibration is realized. Specifically, the method comprises the following steps:
step S21, collecting the image of the target by the image collecting module and transmitting the image to the image processing module, displaying and observing the target by the image processing module, moving the gun barrel to the central area of the target in the image, establishing a pixel space coordinate system, selecting the cross area of the target on the image, and carrying out the centroid point coordinate (X) on the cross area0，Y0) Calculating the centroid point of the reference datum point;
step S22, taking down the gun calibration device, and carrying out environmental test on the vehicle;
step S23, returning to the vehicle initial position after the environmental test is completed, and repeating the step S1;
step S24, collecting the image of the target by the image collecting module and transmitting the image to the image processing module, displaying and observing the target by the image processing module, moving the gun barrel to the central area of the target in the image, establishing a pixel space coordinate system, selecting the cross area of the target on the image, and carrying out the centroid point coordinate (X) on the cross area1，Y1) Calculating;
step S25, comparing the centroid point coordinates (X) obtained in step S21 by the image processing module0，Y0) And the centroid point coordinates (X) obtained in step S241，Y1) Obtaining a deviation value of the gun barrel position;
and step S26, moving the gun barrel so that X0 is equal to X1 and Y0 is equal to Y1, resetting the gun barrel and correcting the guns intelligently.
In this embodiment, the process of calculating the centroid point coordinates in the above steps S21 and S24 is as follows:
step a, image preprocessing: calculating an optimal threshold by adopting a maximum variance threshold segmentation method, and segmenting a high-brightness area of the cross target from a background;
step b, extracting a central line of the cross target: continuously removing the image boundary by adopting a morphological corrosion method until only the skeleton is left as a cross-shaped central line;
step c, calculating the cross centroid: and (3) calculating the best fitting straight lines L1 and L2 of the central lines by adopting a least square method, wherein the coordinates of the intersection point of the straight line L1 and the straight line L2 are the coordinates of the centroid point.
In this embodiment, the central idea of the maximum variance threshold segmentation method is: and selecting a segmentation threshold value, wherein the threshold value enables the difference between the average gray level of the foreground region, the average gray level of the background region and the average gray level of the whole image to be maximum, the difference is represented by the variance of the regions, and the image is further divided into a background part and a target part. Let n be the number of pixels in the image whose gray scale value is iiAnd if the total number of pixels is N, the probability of each gray value is: p is a radical ofi＝ni/N。
Assuming that an image is divided into two regions by a threshold value T, pixels with a gray scale of 0 to k-1 constitute a region A, pixels with a gray scale of k to L-1 constitute a region B, and the areas of the two regions A and B in the image are respectively:
the average gray levels of the region a and the region B are:
average gray scale of the entire image:
the two regions total variance is:
σ2＝ωA(μA-μ)2+ωB(μB-μ)2
when the variance between the divided regions is maximum, it is considered as the optimum separation state of the two regions, and thus the threshold T is determined:
Tm＝max[σ2(T)]
in this embodiment, the central idea of the morphological etching method is: and (5) a process of shrinking the boundary inwards by eliminating the boundary point of the connected domain. A structural element B with an origin is defined, the structural element B is convolved with the image A, the minimum value of pixel points in the coverage area of the structural element B is calculated, and the value is assigned to the designated pixel of the reference point to obtain a corrosion result. If point z is a point within A, when disk D (z) is the largest disk with point z, and D (z) contacts the boundary of A at two or more locations, this is the largest disk of the structural element. And corroding the A for k times by using the largest disc to obtain the skeleton of the image A. As shown in fig. 3.
Example 3
The measurements were carried out using the apparatus set forth in example 1 above and the method set forth in example 2: installing a gun calibrating device, collecting image information by a CCD camera and transmitting the image information to a computer to obtain the coordinates (X) of the centroid point of the cross target0，Y0) (ii) a And (5) taking down the gun calibration device, and carrying out an environmental test on the vehicle. Returning to the initial position of the vehicle after the test is finished, pushing the cannon calibration device into the cannon pipe opening again, and performing centroid point coordinates (X) on the cross target1，Y1) Calculating, moving the barrel so that X0＝X1，Y0＝Y1Realizing gun barrel reset; and comparing the centroid coordinates before and after the environmental test to obtain the offset of the two coordinates, namely the walking amount of the gun barrel. Such as the target cross target centroid displacement diagram shown in fig. 4.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (7)
1. An intelligent cannon correcting device based on a digital image is characterized by comprising a gauge plug, an image acquisition module and an image processing module; the image acquisition module is fixed on one end face of the gauge plug; when checking the gun, pushing one end of the gauge plug, which is not provided with the image acquisition module, into the gun barrel outlet and fixing the end of the gauge plug at the gun barrel outlet, and then connecting the image acquisition module with the image processing module in a communication manner; then, image information is acquired by the image acquisition module and is transmitted to the image processing module for digital processing; and finally, the image processing module obtains a gun barrel position deviation value by comparing the cross target shape center coordinates of the images of the environment test twice before and after the environment test, so that intelligent gun calibration is realized.
2. The device according to claim 1, wherein the image acquisition module employs a CCD camera; the image processing module adopts a computer with an image acquisition card.
3. The device of claim 2, wherein the optical axis of the CCD camera is coaxial with the central axis of the gauge plug and barrel.
4. The device according to any one of claims 1 to 3, wherein the image acquisition module is fixed on the gauge through a fixed seat; and the positions of the gauge plug and the gun barrel are fixed through a fastener when the gun is calibrated.
5. A method of calibrating a fire using a fire calibrating apparatus according to any one of claims 1 to 4, the method comprising the steps of:
step S1, device installation: the gun calibration device is fixedly arranged at the gun outlet of the gun barrel and is connected with the image acquisition module and the image processing module;
step S2, carrying out intelligent gun calibration: acquiring image information through an image acquisition module and transmitting the image information to an image processing module for digital processing to obtain a cross target centroid coordinate; the image processing module obtains a gun barrel position deviation value by comparing the cross target shape center coordinates of the images of the environment test twice before and after, and intelligent gun calibration is realized.
6. The method of calibrating a gun according to claim 5, wherein the step S2 further comprises:
step S21, collecting the target through the image collecting moduleThe image of the target is transmitted to the image processing module, the target is displayed and observed through the image processing module, the gun barrel is moved to the central area of the target in the image, a pixel space coordinate system is established, the cross area of the target is selected from the image, and the centroid point coordinate (X-ray coordinate) is carried out on the cross area0，Y0) Calculating the centroid point of the reference datum point;
step S22, taking down the gun calibration device, and carrying out environmental test on the vehicle;
step S23, returning to the vehicle initial position after the environmental test is completed, and repeating the step S1;
step S24, collecting the image of the target by the image collecting module and transmitting the image to the image processing module, displaying and observing the target by the image processing module, moving the gun barrel to the central area of the target in the image, establishing a pixel space coordinate system, selecting the cross area of the target on the image, and carrying out the centroid point coordinate (X) on the cross area1，Y1) Calculating;
step S25, comparing the centroid point coordinates (X) obtained in step S21 by the image processing module0，Y0) And the centroid point coordinates (X) obtained in step S241，Y1) Obtaining a deviation value of the gun barrel position;
and step S26, moving the gun barrel so that X0 is equal to X1 and Y0 is equal to Y1, resetting the gun barrel and correcting the guns intelligently.
7. The method of claim 5 or 6, wherein the centroid point coordinates calculation in steps S21 and S24 are as follows:
step a, image preprocessing: calculating an optimal threshold by adopting a maximum variance threshold segmentation method, and segmenting a high-brightness area of the cross target from a background;
step b, extracting a central line of the cross target: continuously removing the image boundary by adopting a morphological corrosion method until only the skeleton is left as a cross-shaped central line;
step c, calculating the cross centroid: and (3) calculating the best fitting straight lines L1 and L2 of the central lines by adopting a least square method, wherein the coordinates of the intersection point of the straight line L1 and the straight line L2 are the coordinates of the centroid point.
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| CN112902881A (en) * | 2021-01-26 | 2021-06-04 | 电子科技大学 | Parallel testing method of multi-optical-axis system based on digital image processing |
| CN113357956A (en) * | 2021-05-31 | 2021-09-07 | 无锡市星迪仪器有限公司 | Artillery zero position detector with quick self-calibration function and self-calibration method |
| CN113357956B (en) * | 2021-05-31 | 2022-05-20 | 无锡市星迪仪器有限公司 | Artillery zero position detector with quick self-calibration function and self-calibration method |
| CN114383468A (en) * | 2022-02-18 | 2022-04-22 | 无锡市星迪仪器有限公司 | Tank gun calibration method, processing device and tank gun calibration system |
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