An Automated Method for Computer Vision Analysis of Cannon-Launched Projectile Video

Abstract

This paper describes a cost effective automated methodology to analyze launch video of artillery projectiles. Image processing and computer vision techniques are used to segment and classify the projectile shape in each video frame. Within minutes of being fired, the initial position, velocity, and orientation history of the projectile in three-dimensional space is determined at the gun site. An overview of several standard methods used by the Army to characterize pitching and yawing motion of projectiles is included, as well as a discussion of the limitations of these methods. Results from real artillery testing using the automated video analysis method are validated through comparisons to results measured using conventional techniques.

Measurement of projectile’s in-bore yaw based on the optical lever principle

“…The presented research can be applied to the attitude measurement of in-bore projectile/rocket as well as the angular movements of gun barrel. The resulting angle datum from test can be used as initial conditions in six DOF trajectory simulation to predict the trajectory 6,7 ; to analyze epicyclic and tricyclic motions caused by mass asymmetry of the projectile, 9 factors contributing to gun jump, 15 gun/projectile interactions, 11,18,19 design and diagnosis of failures for fuses 21 ; to validate and improve the fidelity of simulation models, 10,23 and to provide a trustworthy measure for other angular measurement systems. 11 The research also lays a potential foundation to measure tiny pitch and yaw angles for general moving objects.…”

“…Therefore, great effort has been taken to measure it. The existing test method on projectile's attitude mainly consists of high speed photography, [4][5][6][7][8][9][10] onboard instrumentation, [10][11][12][13] and the optical level principle. [14][15][16][17][18][19][20][21][22][23][24][25] Due to the obscurity caused by the gun barrel, high speed photography is unable to measure the projectile's movement in the bore.…”

Automated Canopy and Payload Motion Estimation Using Vision Based Methods

“…Instead of using the color segmentation algorithm, an edge detection-based method is used as described in Ref. [19]. Instead of tracking only the single largest object, the two largest objects are identified.…”