Multi-Classifier Fusion and Nonparametric Decision for Landmine Detection

Award Information
Agency: Department of Defense
Branch: Army
Contract: W909MY-05-C-0011
Agency Tracking Number: A043-124-2060
Amount: $119,989.00
Phase: Phase I
Program: SBIR
Awards Year: 2005
Solitcitation Year: 2004
Solitcitation Topic Code: A04-124
Solitcitation Number: 2004.3
Small Business Information
1600 Providence Highway, Walpole, MA, 02081
Duns: 125933916
Hubzone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: Y
Principal Investigator
 Bo Ling
 President & CEO
 (508) 660-0328
Business Contact
 Bo Ling
Title: President & CEO
Phone: (508) 660-0328
Research Institution
Traditional techniques to detect and remove landmines are both dangerous and time consuming. Very little technology is currently employed in the real world for the detection of landmines. Metal detectors are effective against metal-based landmines, but many mines are plastic cased. Landmines are divided up into two broad classes: antitank (AT) mines, which are designed to impede the progress of or destroy vehicles, and antipersonnel (AP) mines, which are designed to kill and maim people. Landmine comes in a variety of shapes and sizes. They can be square, round, cylindrical, or bar shaped. The casing can be metal, plastic, or wood. These characteristics make the landmine detection challenging. An effective mine detection system should be capable of using all available thermal, spectral and spatial differences for discrimination. The main objective of this project is the development and implementation of a new landmine detection system with classifiers based on surface shapes, textures, comprehensive feature vectors and spectral structures. We propose to develop a set of new nonparametric hypothesis test schemes based on cluster trending analysis and randomness test. A new unsupervised neural network is proposed to cluster measurement data. All classifiers will be fused based on our LIM-based optimal fusion method.

* information listed above is at the time of submission.

Agency Micro-sites

US Flag An Official Website of the United States Government