Projectile Feature Point Recognition And Parameter Identification Based On Orthogonal Shadow Image Processin

Orthogonal shadow photography system is used to measure the motion of high-speed projectile in target track test It is an effective means to visually measure the(attitude)state.Through the interpretation of the projectile coordinates in the shadow images of each shadow camera station,it can accurately measure the velocity,attitude and related aerodynamic parameters in the projectile free flight test.With the rapid development of ammunition launch technology,higher requirements are put forward for the measurement accuracy and automatic processing degree of ballistic test.In order to reduce the random error caused by manually reading image coordinates and improve the system measurement accuracy and efficiency,it is necessary to improve the orthogonal shadow image processing method to realize the highprecision automatic interpretation of image data processing after target test.With the hardware conditions of target shadow camera station and spatial reference calibration system,a sub-pixel improved edge detection orthogonal shadow image automatic interpretation system based on pixel segmentation is proposed,which includes projectile edge information extraction,feature point recognition and image data interpretation.We use the improved edge detection algorithm to identify the pixel coordinates of feature points,combining with the static calibration image obtained by double field grid target reference system,the spatial coordinates of feature points are interpreted.Finally calculate the attitude angle and other parameters of projectile.This paper analyzes the edge characteristics of projectile shadow image,and describes in detail the implementation principle and image processing flow of sub-pixel improved edge detection algorithm.The experiment uses a high-precision resolution board to test and compare the traditional edge detection and improved methods,which results show that the sub-pixel improved edge detection algorithm has a great improvement compared with the traditional Canny or Roberts algorithms in continuous edge detection and equal spacing detection.In this paper,the principle,formula and process of projectile feature point recognition and interpretation are introduced.The static calibration is carried out in the double field grid carrier,the length of the standard part is calculated,and the accuracy of calibration and calibration is tested.The orthogonal shadow image of large caliber projectile obtained from the experiment is automatically recognized,and the processing flow is described.Combined with static calibration,the coordinate interpretation of feature points in shadow image is completed,and the accuracy of feature point recognition and interpretation is verified by calculating the projectile length.In this paper,the overall software design of the automatic interpretation system of projectile feature points is carried out,the functional modules of each system are developed based on MATLAB platform,and the visual operation interface is built.After the actual experimental test,the debugging flow chart of the experimental process is given.The sub-pixel improved edge detection orthogonal shadow image automatic interpretation system based on image segmentation realizes the automatic interpretation of feature point coordinates and the identification of projectile parameters,reduces the time of traditional manual interpretation image processing,and improves the average time of traditional interpretation from half an hour to minutes.At the same time,it avoids the random error of manually selecting feature points,improves the accuracy of shadow image processing and data interpretation,improves the projectile spatial coordinate accuracy from 0.5mm to 0.2mm,and reduces the error of target measurement system.