DocumentCode :
1695838
Title :
Missile tracking using knowledge-based adaptive thresholding
Author :
Haker, Steven ; Sapiro, Guillermo ; Tannenbaum, Allen ; Washburn, Don
Author_Institution :
Dept. of Radiol., Brigham & Women´´s Hosp., Boston, MA, USA
Volume :
1
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
786
Abstract :
We apply a knowledge-based segmentation method developed for still and video images to the problem of tracking missiles and high speed projectiles. Since we are only interested in segmenting a portion of the missile (namely, the nose cone), we use our segmentation procedure as a method of adapting thresholding. The key idea is to utilize a priori knowledge about the objects present in the image, e.g. missile and background, introduced via Bayes´ rule. Posterior probabilities obtained in this way are anisotropically smoothed, and the image segmentation is obtained via MAP classifications of the smoothed data. When segmenting sequences of images, the smoothed posterior probabilities of past frames are used as prior distributions in succeeding frames
Keywords :
Bayes methods; adaptive signal processing; image classification; image segmentation; image sequences; knowledge based systems; missiles; probability; target tracking; video signal processing; Bayes´ rule; MAP classifications; background; high speed projectiles; image segmentation; image sequences; knowledge-based adaptive thresholding; knowledge-based segmentation; missile tracking; nose cone; posterior probabilities; prior distributions; smoothed data; still images; video images; Anisotropic magnetoresistance; Atmosphere; Bayesian methods; Hospitals; Image segmentation; Missiles; Nose; Pixel; Projectiles; Radiology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.959163
Filename :
959163
Link To Document :
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