Adaptive classification for image segmentation and target recognition

Bernhard Bargel; Karl-Heinz Bers; Klaus Jaeger; Gabriele Schwan

doi:10.1117/12.477031

25 July 2002 Adaptive classification for image segmentation and target recognition

Bernhard Bargel, Karl-Heinz Bers, Klaus Jaeger, Gabriele Schwan

Proceedings Volume 4726, Automatic Target Recognition XII; (2002) https://doi.org/10.1117/12.477031
Event: AeroSense 2002, 2002, Orlando, FL, United States

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.

Citation Download Citation

Bernhard Bargel, Karl-Heinz Bers, Klaus Jaeger, and Gabriele Schwan "Adaptive classification for image segmentation and target recognition", Proc. SPIE 4726, Automatic Target Recognition XII, (25 July 2002); https://doi.org/10.1117/12.477031

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