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Proceedings Paper

Obscured Object Recognition For An ATR Application
Author(s): G. Eichmann; M. Jankowski; S. Basu; M. Stojancic; L. Roytman
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Paper Abstract

A common and mainly unsolved problem in image processing is occlusion. Occlusion occurs when one or more objects obstruct the sensor's view. In this paper, three methods; a neural network, a superresolving non-parametric predictor and an Extended-Post Context-free Grammar syntactic pattern recognizer are used to generate the missing data. To illustrate these methods, their application to the reconstruction of obscured Roman characters are presented.

Paper Details

Date Published: 5 September 1989
PDF: 8 pages
Proc. SPIE 1099, Advances in Image Compression and Automatic Target Recognition, (5 September 1989); doi: 10.1117/12.960454
Show Author Affiliations
G. Eichmann, The City College of CUNY (United States)
M. Jankowski, The City College of CUNY (United States)
S. Basu, The City College of CUNY (United States)
M. Stojancic, The City College of CUNY (United States)
L. Roytman, The City College of CUNY (United States)


Published in SPIE Proceedings Vol. 1099:
Advances in Image Compression and Automatic Target Recognition
Andrew G. Tescher, Editor(s)

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