Orbital invader detection method based on orbit visual characteristic spectrum
A technology of visual features and intrusions, applied in the fields of instruments, railway signals and security, character and pattern recognition, etc., can solve the problems of being easily affected by the surrounding environment, unable to be applied, and the template needs to be updated in real time.
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Embodiment 1
[0074] The present invention aims at the shortcomings of the existing track intruder detection system that can only detect at fixed points, is greatly affected by environmental changes, and has a slow detection speed, and in order to meet the characteristics of the small load of the UAV and the high real-time performance of the detection system, the track visual feature spectrum is proposed Theory and its construction method, and based on this theory, a feature matching intrusion detection method is proposed.
[0075] The processing flow of the track intruder detection method based on the track visual feature spectrum proposed by the embodiment of the present invention is as follows: figure 1 As shown, it mainly includes the following processing procedures:
[0076] (1) Constructing the visual feature spectrum of the track. The present invention defines the visual feature spectrum of the track as: extracting image features such as image rotation, brightness, viewing angle, cla...
Embodiment 2
[0131] figure 2 Schematic diagram of a sample orbital feature database constructed after a variety of affine transformations for images of a certain orbital interval segment, in which the rotating image library (a) is obtained by a camera at a fixed position by rotating itself; brightness changes and sharpness The changing image library (b) (d) is obtained by changing the camera's aperture and focal length; the viewing angle and scale changing image library (c) (e) is obtained from different viewing angles and different shooting distances at the same location The images are obtained separately; the compression ratio change image library (f) is obtained by JPEG2000 image compression standard after processing with different compression ratios. image 3 is the image for orbit positioning, where (a) is the original image of the orbit taken by the UAV, (b) is the gradient image obtained after calculating the Sobel gradient direction field and thresholding, (c) is the image after i...
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