Detection filters and algorithm fusion for ATR

Author

Casasent, David ; Ye, Anqi

Author_Institution

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

6

Issue

1

fYear

1997

fDate

1/1/1997 12:00:00 AM

Firstpage

114

Lastpage

125

Abstract

Detection involves locating all candidate regions of interest (objects) in a scene independent of the object class with object distortions and contrast differences, etc., present. It is one of the most formidable problems in automatic target recognition, since it involves analysis of every local scene region. We consider new detection algorithms and the fusion of their outputs to reduce the probability of false alarm P_FA while maintaining high probability of detection P_D. Emphasis is given to detecting obscured targets in infrared imagery

Keywords

digital filters; image recognition; image segmentation; infrared imaging; object detection; object recognition; probability; ATR; algorithm fusion; automatic target recognition; contrast differences; detection algorithms; detection filters; detection probability; false alarm probability; fusion; infrared imagery; local scene region; object class; object distortions; obscured targets; Detection algorithms; Gabor filters; Image databases; Infrared detectors; Infrared imaging; Layout; Object detection; Pixel; Target recognition; Testing;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.552101

Filename

552101