Detection of buried objects by fusing dual-band infrared images
We have conducted experiments to demonstrate the enhanced detectability of buried land mines using sensor fusion techniques. Multiple sensors, including visible imagery, infrared imagery, and ground penetrating radar (GPR), have been used to acquire data on a number of buried mines and mine surrogates. Because the visible wavelength and GPR data are currently incomplete. This paper focuses on the fusion of two-band infrared images. We use feature-level fusion and supervised learning with the probabilistic neural network (PNN) to evaluate detection performance. The novelty of the work lies in the application of advanced target recognition algorithms, the fusion of dual-band infrared images and evaluation of the techniques using two real data sets.
- Research Organization:
- Lawrence Livermore National Lab., CA (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 10134642
- Report Number(s):
- UCRL-JC-114321; CONF-9311135-5; ON: DE94008286
- Resource Relation:
- Conference: Institute of Electrical and Electronic Engineers (IEEE) asilomar conference on signals, systems, and computers,Pacific Grove, CA (United States),1-3 Nov 1993; Other Information: PBD: Nov 1993
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
47 OTHER INSTRUMENTATION
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION
CHEMICAL EXPLOSIVES
DETECTION
INFRARED RADIATION
IMAGE PROCESSING
WEAPONS
UNDERGROUND
NEURAL NETWORKS
450100
440800
350300
CHEMICAL EXPLOSIONS AND EXPLOSIVES
MISCELLANEOUS INSTRUMENTATION
VERIFICATION