Classifying sets of attributed scattering centers using a hash coded database

Kerry E. Dungan; Lee C. Potter

doi:10.1117/12.855593

18 April 2010 Classifying sets of attributed scattering centers using a hash coded database

Kerry E. Dungan, Lee C. Potter

Proceedings Volume 7699, Algorithms for Synthetic Aperture Radar Imagery XVII; 76990Q (2010) https://doi.org/10.1117/12.855593
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

We present a fast, scalable method to simultaneously register and classify vehicles in circular synthetic aperture radar imagery. The method is robust to clutter, occlusions, and partial matches. Images are represented as a set of attributed scattering centers that are mapped to local sets, which are invariant to rigid transformations. Similarity between local sets is measured using a method called pyramid match hashing, which applies a pyramid match kernel to compare sets and a Hamming distance to compare hash codes generated from those sets. By preprocessing a database into a Hamming space, we are able to quickly find the nearest neighbor of a query among a large number of records. To demonstrate the algorithm, we simulated X-band scattering from ten civilian vehicles placed throughout a large scene, varying elevation angles in the 35 to 59 degree range. We achieved better than 98 percent classification performance. We also classified seven vehicles in a 2006 public release data collection with 100% success.

Citation Download Citation

Kerry E. Dungan and Lee C. Potter "Classifying sets of attributed scattering centers using a hash coded database", Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990Q (18 April 2010); https://doi.org/10.1117/12.855593

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