Robust extended target detection using nonlinear morphological operations

Hai-Wen Chen; Chris Volpe; Michael Tarnowski; Stephen Snarski

doi:10.1117/12.850511

7 May 2010 Robust extended target detection using nonlinear morphological operations

Hai-Wen Chen, Chris Volpe, Michael Tarnowski, Stephen Snarski

Proceedings Volume 7694, Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR; 76941H (2010) https://doi.org/10.1117/12.850511
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The current bottleneck in wide area persistent surveillance missions is slow exploitation and analysis (real-time and forensic)by human analysts. We are currently developing an automated data exploitation system that can detect, track, and recognize targets and threats using computer vision. Here we present results from a newly developed target detection process. Depanding on target size, target detection can be divided in three detection classes: unresolved targets, small extended targets, and large extended targets. The Matched Filter (MF) method is currently a popular approach for unresolved target detection using IR focal plane arrays and EO (CCD) cameras and sensor detectors. The MF method is much more difficult to apply to to the extended target classes, since many different matched filters are needed to match the different target shapes and intensity profiles that can exist. The MF method does not adequately address non-fixed target shapes (e.g. walking or running human). We have developed an approach for robust target detection that can detect targets of different sizes and shapes (fixed/non-fixed) using a combination of image frame time-differencing, deep-thresholding, and target shape and size analysis with non-linear morphologial operations. Applications for gound vehicle detection under heavy urban background clutter will be presented.

Citation Download Citation

Hai-Wen Chen, Chris Volpe, Michael Tarnowski, and Stephen Snarski "Robust extended target detection using nonlinear morphological operations", Proc. SPIE 7694, Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR, 76941H (7 May 2010); https://doi.org/10.1117/12.850511

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