This research paper investigates the use of the wavelet transform to extract spatially-invariant wavelet-based shape signatures for automatic target recognition (ATR). Target signatures based on shape information can be generally categorized as either contour-based or region-based. The wavelet-based shape signatures facilitate detection and localization of important edge and texture information aiding in discrimination between targets. To demonstrate the advantages of both edge and region information, we present an approach that combines region-based shape methods and the wavelet transform for generating target signatures. Our approach generates a rotationally invariant class of wavelet signatures based on the spatial ground pixel coverage of the target is determined from the region-of-interest (ROI) in the wavelet domain. This process results in a multiresolution representation of the target, and provides a hierarchical approach to target signature-matching. We demonstrate this methodology using signatures from aircraft targets utilizing the Angular Radial Transform (ART) as the region-based shape signature. Region-based signatures are shown more robust than contourbased signatures in the presence of noise and disconnected target regions providing greater confidence in target identification. Our research results show the value of combining the rotational invariance of the ART signatures with the localization and edge discrimination properties of the wavelet transform.

Date Published: 12 May 2010
PDF: 12 pages
Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76960T (12 May 2010); doi: 10.1117/12.850438

Published in SPIE Proceedings Vol. 7696:
Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI
Firooz A. Sadjadi; David P. Casasent; Steven L. Chodos; Abhijit Mahalanobis; William E. Thompson; Tien-Hsin Chao, Editor(s)