A new approach to target recognition for LADAR data

Author

Pal, Nikhil R. ; Cahoon, Tobias C. ; Bezdek, Jim C. ; Pal, Kuhu

Author_Institution

Dept. of Comput. Sci., West Florida Univ., Pensacola, FL, USA

Volume

9

Issue

1

fYear

2001

fDate

2/1/2001 12:00:00 AM

Firstpage

44

Lastpage

52

Abstract

We discuss target detection in LADAR intensity images. Thirteen features, eleven of which come from an asymmetric co-occurrence matrix, are extracted from region-of-interest windows in each image. Two methods of feature selection are applied to the extracted vectors. Random selection leads to a pair of selected features for a nearest-neighbor rule (1-nn) detector. Extended backpropagation leads to six selected features using a modified multilayered perceptron (MLP) network. The 1-nn detector achieves a test-error rate of about 16% at a false-alarm rate of 8%. The MLP has a test-error rate of about 12% with a false-alarm rate of 6%

Keywords

backpropagation; feature extraction; matrix algebra; multilayer perceptrons; optical radar; radar imaging; radar target recognition; LADAR data; backpropagation; cooccurrence matrix; feature extraction; multilayered perceptron; nearest-neighbor rule; random selection; target detection; Computer science; Detectors; Inspection; Laser radar; Layout; Object detection; Pixel; Target recognition; Testing; Vehicles;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/91.917113

Filename

917113