Detecting missile-like flying target from a distance in sequence images

Xiaokun Li; Genshe Chen; Erik Blasch; Khanh Pham

doi:10.1117/12.777463

17 April 2008 Detecting missile-like flying target from a distance in sequence images

Xiaokun Li, Genshe Chen, Erik Blasch, Khanh Pham

Proceedings Volume 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII; 69680G (2008) https://doi.org/10.1117/12.777463
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Automatic target detection (ATD) systems using imaging sensors have played a critical role in site monitoring, surveillance, and object tracking. Although numerous research efforts and systems have been designed to quickly detect and recognize missile-like flying targets in cluttered environments, detection of flying targets from a long distance and large format imagery data is still a challenge. The accuracy of target detection and recognition will greatly affect the performance of the target tracking system. In this paper, we propose a novel framework to quickly detect missile-like flying targets in a time-efficient manner. The framework is based on a coarse-to-fine strategy and consists of five components executed in a sequential order: (1) A rapid clustering operation performs fast image segmentation; (2) based on the segmentation results of three neighboring image frames, motion analysis identifies the regions of interest which contain the flying targets; (3) a specially-designed double-threshholding operator precisely segments the moving targets from the regions of interest; (4) a binary connectivity filter enhances the detected targets and removes the target noise; and (5) a contour method analyzes the boundary of the detected targets for verification. To test the proposed approach, a state-of-the-art 3D modeling and animation software tool was used to simulate target flight and attack. Experimental results, obtained from the electro-optical (EO) images generated from the 3D simulations, illustrate a wide variety of target and clutter variability, and demonstrate the effectiveness and robustness of the proposed approach.

Citation Download Citation

Xiaokun Li, Genshe Chen, Erik Blasch, and Khanh Pham "Detecting missile-like flying target from a distance in sequence images", Proc. SPIE 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII, 69680G (17 April 2008); https://doi.org/10.1117/12.777463

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