Hypothesis testing for landmine detection with EMI images

1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence

Volumn 1, Issue , 1998, Pages 237-240

  Collins, Leslie ^a   Gao, Ping ^a  

^a DUKE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLUTTER (INFORMATION THEORY); DATA REDUCTION; IMAGE ANALYSIS; IMAGE QUALITY; ORDNANCE; PROBABILITY; STATISTICAL METHODS;

ELECTROMAGNETIC INDUCTION (EMI) SENSORS; LANDMINE DETECTION SYSTEMS; STATISTICAL BAYESIAN METHODS;

SENSORS;

EID: 0031634928     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.1998.687490     Document Type: Conference Paper

References (7)

1. Baum, C.E., Low Frequency Near-Field Magnetic Scattering from Highly, but Not Perfectly Conducting Bodies. Phiolips Laboratory Interaction Note 499, 1993. November.
2. Sower, S.D. and S.P. Cave. Detection and Identification of Mines from Natural Magnetic and Electromagnetic Resonances, in SPIE. 1995. Orlando, FL.
3. Collins, L., et al. An improved decision- theoretic approach to the optimum detection of mine, in SPIE. 1997. Orlando, FL.
4. Gao, P. and L. Collins. Improved signal processing approaches for landmine detection, in SPIE. 1998. Orlando, FL.
5. Collins, L., P. Gao, and L. Carin, An Improved Bayesian Decision Theoretic Approach for Land Mine Detection. IEEE Trans. Geosc. Remote Sens., 1997. submitted.
6. George, V., et al, Background Data Collection Plan, . 1996, DARPA/Defense Science Office.
7. Gao, P. and L. Collins, A 2- Dimensional Generalized Likelihood Ratio Test for Land Mine Detection. Signal Processing Letters, 1998. submitted.