CN111160123B - Aircraft target identification method, device and storage medium - Google Patents
Aircraft target identification method, device and storage medium Download PDFInfo
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- CN111160123B CN111160123B CN201911264988.1A CN201911264988A CN111160123B CN 111160123 B CN111160123 B CN 111160123B CN 201911264988 A CN201911264988 A CN 201911264988A CN 111160123 B CN111160123 B CN 111160123B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/08—Detecting or categorising vehicles
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention provides an aircraft target identification method, an aircraft target identification device and a storage medium, wherein the method comprises the following steps: acquiring aircraft video information through preset air target detection equipment, and decoding the aircraft video information to obtain a sample picture to be detected; processing a preset training set through a preset processor to obtain a characteristic file; importing the feature file into a Haar feature classifier, and detecting whether a sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result; and when the detection result is that the target aircraft exists in the sample picture to be detected, sending the position of the target aircraft in the sample picture to be detected to a designated terminal. The invention can effectively capture the aerial airplane target in the daytime or at night, has low requirement on the quality of the collected airplane target image, can accurately identify various airplane types, and provides real-time airplane target positions for ground-to-air monitoring and tracking of the airplane target, thereby having strong applicability.
Description
Technical Field
The invention mainly relates to the technical field of video monitoring, in particular to an aircraft target identification method, an aircraft target identification device and a storage medium.
Background
The aircraft target recognition is mainly used for recognizing an aircraft in the air, the target recognition technology is mature in the industry, and targets are mainly searched and recognized rapidly under various complex or pure backgrounds. In the existing aircraft target recognition technology, if the aircraft recognition method such as closed contour extraction and partial feature matching, PCA (principal component analysis) and image matching, corner point and clustering and the like is adopted, the image is generally collected by adopting a overlooking view angle, the image of a overlooking aircraft overall view with bilateral symmetry of the aircraft span can be collected, and whether the method is suitable for infrared thermal imaging aircraft target recognition is not described. In the video monitoring field, a certain position of the ground is taken as an observation point, so that a top view of an airplane target is difficult to collect, only a bottom view of the airplane target can be collected, and meanwhile, the problems of various airplane types, high flying speed, various flying postures, various viewing angles and the like of the airplane target lead to the defects that a picture collected by a camera has asymmetric wing span of the airplane, and the background brightness is higher than the foreground brightness.
Disclosure of Invention
The invention aims to solve the technical problem of providing an aircraft target identification method, an aircraft target identification device and a storage medium aiming at the defects of the prior art.
The technical scheme for solving the technical problems is as follows: an aircraft target recognition method comprising the steps of:
acquiring aircraft video information through preset air target detection equipment, and decoding the aircraft video information to obtain a sample picture to be detected;
processing a preset training set through a preset processor to obtain a characteristic file;
importing the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result;
and when the detection result is that the target aircraft exists in the sample picture to be detected, sending the position of the target aircraft in the sample picture to be detected to a designated terminal.
The other technical scheme for solving the technical problems is as follows: an aircraft target recognition device, comprising:
the video collection and analysis module is used for acquiring aircraft video information through preset air target detection equipment and decoding the aircraft video information to obtain a sample picture to be detected;
the feature file generation module is used for processing the preset training set through the preset processor to obtain a feature file;
the aircraft detection module is used for guiding the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result;
and the judging module is used for sending the position of the target aircraft in the sample picture to be detected to a designated terminal when the detection result is that the target aircraft exists in the sample picture to be detected.
The other technical scheme for solving the technical problems is as follows: an aircraft target recognition device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, which when executed by the processor implements an aircraft target recognition method as described above.
The other technical scheme for solving the technical problems is as follows: a computer readable storage medium storing a computer program which, when executed by a processor, implements an aircraft target recognition method as described above.
The beneficial effects of the invention are as follows: the method can effectively capture the aerial airplane targets in the daytime or at night, has low requirement on the quality of the collected airplane target images, can accurately identify airplanes of various types, and provides real-time airplane target positions for ground-to-air monitoring and tracking of the airplane targets, and has strong applicability.
Drawings
FIG. 1 is a flow chart of an aircraft target recognition method according to an embodiment of the present invention;
fig. 2 is a block diagram of an aircraft target recognition device according to an embodiment of the present invention.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
Fig. 1 is a flowchart of an aircraft target recognition method according to an embodiment of the present invention.
As shown in fig. 1, an aircraft target recognition method includes the following steps:
acquiring aircraft video information through preset air target detection equipment, and decoding the aircraft video information to obtain a sample picture to be detected;
processing a preset training set through a preset processor to obtain a characteristic file;
importing the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result;
and when the detection result is that the target aircraft exists in the sample picture to be detected, sending the position of the target aircraft in the sample picture to be detected to a designated terminal.
It should be understood that the position of the target aircraft uses a vector container to store the coordinates and the size of the target aircraft in the sample image to be detected, and when the detection result is that the target aircraft exists in the sample image to be detected, the coordinates of the vector container are output, that is, the position of the target aircraft in the sample image to be detected.
In the embodiment, the aerial airplane target can be effectively captured in daytime or at night, the acquired airplane target image quality requirement is low, various airplane types can be accurately identified, and real-time airplane target positions are provided for ground-to-air monitoring and tracking of the airplane target, so that the applicability is strong.
Optionally, as an embodiment of the present invention, the air target detection device includes a pre-installed video collecting device and a monitoring terminal; the process of obtaining the sample picture to be identified by obtaining the aircraft video information through the preset air target detection equipment and decoding the aircraft video information comprises the following steps:
the video collection device collects aircraft video information, wherein the aircraft video information comprises a video stream;
the monitoring terminal decodes the video stream in real time to obtain a video frame image, decodes the video frame image to obtain an RGB image, converts the RGB image to obtain a gray scale image, and takes the gray scale image as the sample image to be detected.
It should be appreciated that the video collection apparatus includes a visible light camera, a thermal imaging camera, a servo turntable, servo control and drive means; the servo control and driving device controls the rotation direction of the servo turntable and sends servo data of the servo turntable to the monitoring terminal; the servo data comprises azimuth and pitching states of the servo turntable; the monitoring terminal can also control the focal length of the thermal imaging camera and the visible light camera and focus and control the rotation of the servo turntable; and the monitoring terminal decodes the video stream in real time by using a sea-health SDK library function to obtain a YUV format video frame image, decodes the YUV format video frame image into an RGB image by using a YV12 function, and converts the RGB image into the gray image by using a cvCvtColor function.
Specifically, the aerial target detection equipment consists of a visible light camera, a thermal imaging camera, an information processor, a storage and transmission processor and a monitoring terminal; the detection equipment provides a video source for the aerial target detection equipment in real time through a visible light camera and a thermal imaging camera, and the video source is utilized for identifying and tracking targets; the servo turntable can rotate at 360 degrees, and the pitching can rotate at-45 degrees to 45 degrees, so that the servo turntable is used for tracking and controlling targets; the servo control and driving device is used for controlling the rotation of the servo turntable; the information processor and the storage and transmission processor are used for signal transmission, and the monitoring terminal is mainly used for decoding and displaying videos and displaying servo data of the servo turntable and can control the visible light camera, the thermal imaging camera and the servo turntable.
In the embodiment, the aerial aircraft can be captured in the daytime or at night, the applicability is high, the acquired aircraft target image quality requirement is low, and the high-definition capturing can be carried out on various postures of the aircraft.
Optionally, as an embodiment of the present invention, the processing, by a preset processor, the preset training set to obtain the profile includes:
importing the preset training set into the preset processor for data processing to obtain a sample description file; and importing the sample description file into the preset processor again for data processing to obtain the characteristic file.
Specifically, the preset training set includes a positive sample including an image including an airplane and a negative sample including an image not including an airplane.
It should be understood that, the sample description file of the positive and negative samples is specified by opencv_createsamples. Exe, then the haar features are extracted and the adaboost classifier is trained by opencv_haarotening. Exe, and finally the classifier is combined to generate the xml file.
In the embodiment, various sample pictures are collected, so that feature identification and confirmation are conveniently carried out on various machine types under various complex conditions, and the identification accuracy is improved.
Optionally, as an embodiment of the present invention, the process of importing the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has the target aircraft through the Haar feature classifier, to obtain a detection result includes:
and importing the feature file into a Haar feature classifier to obtain a Haar feature classifier object, and detecting the sample picture to be detected by the Haar feature classifier object by adopting a detectMultiScale function to obtain a result of whether a target airplane exists in the sample picture to be detected.
In the embodiment, the target aircraft in the image can be identified, the accuracy of identification is improved, and the applicability is high.
Fig. 2 is a block diagram of an aircraft target recognition device according to an embodiment of the present invention.
Alternatively, as another embodiment of the present invention, as shown in fig. 2, an aircraft target recognition device includes:
the video collection and analysis module is used for acquiring aircraft video information through preset air target detection equipment and decoding the aircraft video information to obtain a sample picture to be detected;
the feature file generation module is used for processing the preset training set through the preset processor to obtain a feature file;
the aircraft detection module is used for guiding the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result;
and the judging module is used for sending the position of the target aircraft in the sample picture to be detected to a designated terminal when the detection result is that the target aircraft exists in the sample picture to be detected.
Optionally, as an embodiment of the present invention, the air target detection device includes a pre-installed video collecting device and a monitoring terminal; the video collection and analysis module is specifically used for:
the video collection device collects aircraft video information, wherein the aircraft video information comprises a video stream;
the monitoring terminal decodes the video stream in real time to obtain a video frame image, decodes the video frame image to obtain an RGB image, converts the RGB image to obtain a gray scale image, and takes the gray scale image as the sample image to be detected.
Optionally, as an embodiment of the present invention, the profile generation module is specifically configured to:
importing the preset training set into the preset processor for data processing to obtain a sample description file; and importing the sample description file into the preset processor again for data processing to obtain the characteristic file.
Optionally, as an embodiment of the present invention, the aircraft detection module is specifically configured to:
and importing the feature file into a Haar feature classifier to obtain a Haar feature classifier object, and detecting the sample picture to be detected by the Haar feature classifier object by adopting a detectMultiScale function to obtain a result of whether a target airplane exists in the sample picture to be detected.
Alternatively, another embodiment of the present invention provides an aircraft target recognition device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, which when executed by the processor, implements an aircraft target recognition method as described above. The device may be a computer or the like.
Alternatively, another embodiment of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements an aircraft target recognition method as described above.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (6)
1. An aircraft target recognition method is characterized by comprising the following steps:
acquiring aircraft video information through preset air target detection equipment, and decoding the aircraft video information to obtain a sample picture to be detected;
processing a preset training set through a preset processor to obtain a characteristic file;
importing the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result;
when the detection result is that the target aircraft exists in the sample picture to be detected, the position of the target aircraft in the sample picture to be detected is sent to a designated terminal;
the aerial target detection equipment comprises pre-installed video collection equipment and a monitoring terminal; the process of obtaining the sample picture to be identified by obtaining the aircraft video information through the preset air target detection equipment and decoding the aircraft video information comprises the following steps:
the video collection device collects aircraft video information, wherein the aircraft video information comprises a video stream;
the monitoring terminal decodes the video stream in real time to obtain a video frame image, decodes the video frame image to obtain an RGB image, converts the RGB image to obtain a gray scale image, and takes the gray scale image as the sample image to be detected;
the process of processing the preset training set through the preset processor to obtain the characteristic file comprises the following steps:
importing the preset training set into the preset processor for data processing to obtain a sample description file; and importing the sample description file into the preset processor again for data processing to obtain the characteristic file.
2. The method for identifying an aircraft target according to claim 1, wherein the process of importing the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has the target aircraft by the Haar feature classifier, and obtaining a detection result includes:
and importing the feature file into a Haar feature classifier to obtain a Haar feature classifier object, and detecting the sample picture to be detected by the Haar feature classifier object by adopting a detectMultiScale function to obtain a result of whether a target airplane exists in the sample picture to be detected.
3. An aircraft target recognition device, comprising:
the video collection and analysis module is used for acquiring aircraft video information through preset air target detection equipment and decoding the aircraft video information to obtain a sample picture to be detected;
the feature file generation module is used for processing the preset training set through the preset processor to obtain a feature file;
the aircraft detection module is used for guiding the feature file into a Haar feature classifier, and detecting whether the sample picture to be detected has a target aircraft or not through the Haar feature classifier to obtain a detection result;
the judging module is used for sending the position of the target aircraft in the sample picture to be detected to a designated terminal when the detection result is that the target aircraft exists in the sample picture to be detected;
the aerial target detection equipment comprises pre-installed video collection equipment and a monitoring terminal; the video collection and analysis module is specifically used for:
the video collection device collects aircraft video information, wherein the aircraft video information comprises a video stream;
the monitoring terminal decodes the video stream in real time to obtain a video frame image, decodes the video frame image to obtain an RGB image, converts the RGB image to obtain a gray scale image, and takes the gray scale image as the sample image to be detected;
the feature file generation module is specifically configured to:
importing the preset training set into the preset processor for data processing to obtain a sample description file; and importing the sample description file into the preset processor again for data processing to obtain the characteristic file.
4. An aircraft target recognition device according to claim 3, wherein the aircraft detection module is specifically configured to:
and importing the feature file into a Haar feature classifier to obtain a Haar feature classifier object, and detecting the sample picture to be detected by the Haar feature classifier object by adopting a detectMultiScale function to obtain a result of whether a target airplane exists in the sample picture to be detected.
5. An aircraft object identification device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the aircraft object identification method according to any one of claims 1 to 2 is implemented when the processor executes the computer program.
6. A computer readable storage medium storing a computer program, characterized in that the aircraft object identification method according to any one of claims 1 to 2 is implemented when the computer program is executed by a processor.
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| CN113534093B (en) * | 2021-08-13 | 2023-06-27 | 北京环境特性研究所 | Method for inverting number of propeller blades of aircraft target and target identification method |
| CN113837109A (en) * | 2021-09-27 | 2021-12-24 | 桂林长海发展有限责任公司 | Airplane landing effect evaluation method and device and storage medium |
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