Accession Number : ADA327472
Title : Adaptive Model Based ATR System.
Descriptive Note : Final rept. 30 Jun 93-30 Sep 96,
Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
Personal Author(s) : Ikeuchi, Katsushi ; Collins, Robert ; Shakunaga, Takeshi ; Ohba, Khotara ; Pomeleau, Dean
PDF Url : ADA327472
Report Date : SEP 1996
Pagination or Media Count : 55
Abstract : This project develops a SAR-ATR system that uses invariant histograms and deformable templates. An invariant histogram is a histogram of geometric invariants given by primitive feature sets. Deformable template matching examines the existence of an object by superimposing templates over potential energy fields derived from the image so that it generates the minimum deformation (deformation energy) and the best alignment of the template with features (potential energy). This system has two modes: off-line and on-line. In off-line mode, it generates a library for indexing and deformable templates for verification. In on-line mode, by calculating an invariant histogram from an input image, it performs the deformable templates, it determines the most likely pose and class of the target. We have demonstrated the effectiveness of these two techniques for robust SAR recognition using occluded and camouflaged target images. By analyzing the evaluation results, we have proposed three extensions of the system: dense sampling for robust recognition, partial view windows for robust indexing under occlusion, and photometric invariants for robust verification under camouflage. Some of these ideas have been evaluated; they are quite promising.
Descriptors : *TARGET RECOGNITION, *SYNTHETIC APERTURE RADAR, *HISTOGRAMS, EIGENVALUES, POTENTIAL ENERGY, ONLINE SYSTEMS, PHOTOMETRY, OFFLINE SYSTEMS, AUTOMATIC TRACKING.
Subject Categories : Statistics and Probability
Active & Passive Radar Detection & Equipment
Target Direction, Range and Position Finding
Distribution Statement : APPROVED FOR PUBLIC RELEASE