Accession Number : ADA188828

Title :   Position, Scale, and Rotation Invariant Target Recognition Using Range Imagery.

Descriptive Note : Master's thesis,

Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING

Personal Author(s) : Troxel, Steven E

PDF Url : ADA188828

Report Date : Dec 1987

Pagination or Media Count : 137

Abstract : This thesis explores a new approach to the recognition of tactical targets using a multifunction laser radar sensor. Targets of interest were tanks, jeeps, and trucks. Doppler images were segmented and overlaided onto a relative range image. The resultant shapes were then transformed into a position, scale, and rotation invariant (PSRI) feature space. The classification processes used the correlation peak of the template PSRI space and the target PSRI space as features. Two classification methods were implemented: a classical distance measurement approach and a new biologically-based neural network multilayer perception architecture. Both methods demonstrated classification rates near 100% with a true rotation invariance demonstrated up to 20 degrees. Neural networks were shown to have a distinct advantage in a robust environment and when a figure of merit criteria was applied. A space domain correlation was developed using local normalization and multistage processing to locate and classify targets in high clutter and with partially occluded targets.

Descriptors :   *DOPPLER SYSTEMS, *OPTICAL RADAR, *TARGET RECOGNITION, ARCHITECTURE, CLASSIFICATION, CLUTTER, CORRELATION, DETECTORS, FIGURE OF MERIT, IMAGES, INVARIANCE, LAYERS, MEASUREMENT, MILITARY VEHICLES, MULTIPURPOSE, NEURAL NETS, NORMALIZING(STATISTICS), PEAK VALUES, PERCEPTION, PROCESSING, RANGE(DISTANCE), ROTATION, STAGING, TACTICAL WARFARE, TARGETS, THESES

Subject Categories : Active & Passive Radar Detection & Equipment

Distribution Statement : APPROVED FOR PUBLIC RELEASE