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Detection of natural, variable objects

Award Information
Agency: Department of Defense
Branch: Army
Contract: N/A
Agency Tracking Number: 36799
Amount: $99,993.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 1997
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
5400 Port Royal Rd
Springfield, VA 22151
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 John L. Perry
 (703) 321-4540
Business Contact
Phone: () -
Research Institution

Detection of natural, variable objects requires general features that can be extracted from any image. Human vision is capable of segmenting images and recognizing objects in radiographs despite the summation of all objects in the inspection volume in the image plane. Thus, the features important in human perception provide a guide for automatic image processing. The initial features selected for evaluation are edges, defined by the wavelet transform and characterized by the Lipschitz exponent, and the fractal dimension, estimated by an efficient multiscale filter. Segmentation of the multiple parameter image, including spectroscopic absorption data, will then be effected using the Markov random field model and hierarchical agglomerative clustering algorithm of Panjwani and Healey. Military applications include internal inspection of munitions for manufacturing quality control, or possibly for treaty verification. Many security tasks require internal inspection for only generally defined objects, such as inspection for explosives of contraband. Commercial applications include inspection for ill-defined, high-resolution defects such as cracks and corrosion in sealed containers and plumbing. These image features can be used in the automated analysis of other types images.

* Information listed above is at the time of submission. *

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