Accession Number:

ADA333550

Title:

Automatic Target Recognition Using Wavelet-Based Vector Quantization

Descriptive Note:

Interim rept. Dec 1996-Jul 1997

Corporate Author:

ARMY RESEARCH LAB ADELPHI MD

Report Date:

1997-12-01

Pagination or Media Count:

43.0

Abstract:

An automatic target recognition classifier is described that uses a set of dedicated vector quantizers VQs in the wavelet domain. The background pixels in each input image are properly clipped out by a set of aspect windows. The extracted target area for each aspect window is then enlarged to a fixed size, after which a wavelet decomposition is used to split this region into several subbands. A dedicated VQ codebook is then generated for each subband of a particular target class at a specific range of aspects. Thus, each codebook consists of a set of feature templates that are iteratively adapted to represent a particular subband of a given target class at a specific range of aspects. These templates are then further trained by a modified learning vector quantization LVQ algorithm that enhances their discriminatory characteristics. Finally, a path selector was designed to speed up the recognition process at the expense of a tolerable degradation in the recognition rate.

Subject Categories:

  • Cybernetics
  • Infrared Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE