Title :
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
fDate :
1/1/1997 12:00:00 AM
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 PFA while maintaining high probability of detection PD. 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;
Journal_Title :
Image Processing, IEEE Transactions on
