Share Email Print
cover

Proceedings Paper

Generalized hidden Markov models for land mine detection
Author(s): Paul D. Gader; Mihail Popescu
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper we describe a possible solution to the rigid Gaussian mixture problem of a continuous hidden Markov model (CHMM) in the context of landmine detection. The main idea of the solution is replacing the Gaussian representation of the feature distribution by a function that uses knowledge about real data distribution (sigmoidal in our case). The main advantage of this approach is that it is faster than the CHMM while maintaining the same performance, fact that can be critical in real-time systems. We use the CHMM as a benchmark for the performance of the newly developed algorithm.

Paper Details

Date Published: 13 August 2002
PDF: 7 pages
Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); doi: 10.1117/12.479106
Show Author Affiliations
Paul D. Gader, Univ. of Florida (United States)
Mihail Popescu, Univ. of Missouri/Columbia (United States)


Published in SPIE Proceedings Vol. 4742:
Detection and Remediation Technologies for Mines and Minelike Targets VII
J. Thomas Broach; Russell S Harmon; Gerald J. Dobeck, Editor(s)

© SPIE. Terms of Use
Back to Top