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Proceedings Paper

Adaptive classification for image segmentation and target recognition
Author(s): Bernhard Bargel; Karl-Heinz Bers; Klaus Jaeger; Gabriele Schwan
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Paper Abstract

This paper on adaptive image segmentation and classification describes research activities on statistical pattern recognition in combination with methods of object recognition by geometric matching of model and image structures. In addition, aspects of sensor fusion for airborne application systems like terminal missile guidance were considered using image sequences of multispectral data from real sensor systems and from computer simulations. The main aspect of the adaptive classification is the support of model-based structural image analysis by detection of image segments representing specific objects, e.g. forests, rivers and urban areas. The classifier, based on textural features, is automatically adapted to the changes of textural signatures during target approach by interpretation of the segmentation results of each actual frame of the image sequence.

Paper Details

Date Published: 25 July 2002
PDF: 11 pages
Proc. SPIE 4726, Automatic Target Recognition XII, (25 July 2002); doi: 10.1117/12.477031
Show Author Affiliations
Bernhard Bargel, FGAN-Forschungsinstitut fuer Optronik und Mustererkennung (Germany)
Karl-Heinz Bers, FGAN-Forschungsinstitut fuer Optronik und Mustererkennung (Germany)
Klaus Jaeger, FGAN-Forschungsinstitut fuer Optronik und Mustererkennung (Germany)
Gabriele Schwan, FGAN-Forschungsinstitut fuer Optronik und Mustererkennung (Germany)

Published in SPIE Proceedings Vol. 4726:
Automatic Target Recognition XII
Firooz A. Sadjadi, Editor(s)

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