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Proceedings Paper

Comparison of predetection and postdetection fusion for mine detection
Author(s): Ajith H. Gunatilaka; Brian A. Baertlein
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Paper Abstract

We present and compare methods for pre-detection and post- detection fusion of multi-sensor data. This study emphasis methods suitable for data that are non-commensurate and sampled at non-coincident points. Decision-level fusion is most convenient for such data, but this approach is sub- optimal in principle, since targets not detected by all sensor will not achieve the maximum benefits of fusion. A novel feature-level fusion algorithm for these conditions is described. The optimal forms of both decision-level and feature-level fusion are described, and some approximations are reviewed. Preliminary result for these two fusion techniques are presented for experimental data acquired by a metal detector, a ground-penetrating radar, and an IR camera.

Paper Details

Date Published: 2 August 1999
PDF: 12 pages
Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999); doi: 10.1117/12.357000
Show Author Affiliations
Ajith H. Gunatilaka, The Ohio State Univ. (United States)
Brian A. Baertlein, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 3710:
Detection and Remediation Technologies for Mines and Minelike Targets IV
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Regina E. Dugan, Editor(s)

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