Abstract: A system and a method using image processing and pattern recognition techniques to substantially automatically analyze a captured image in order to accurately estimate a variety of microscopical properties of a prepared sample of a material in accordance with an established standard. Where the material is Portland cement concrete and the standard is ASTM C457-90, the analysis is operable to calculate estimates of sixteen characteristics to detect voids in the concrete, while discriminating against other components and features of the concrete. The preferred system broadly comprises a microscope; a high-precision stage; an image capturing mechanism; and a computing device. Analysis techniques applied to the image include color segmentation and recognition; shape feature segmentation and analysis; and intensity profile segmentation and recognition; the results of which are integrated to provide a final result wherefrom quality of the material may be determined.

Abstract: A multi-sensor system (10) for detecting the presence of objects on the surface of the ground or buried just under the surface, such as anti-personnel or anti-tank mines or the like. A remote sensor platform (12) has a plurality of metal detector sensors (22) and a plurality of short pulse radar sensors (24). The remote sensor platform (12) is remotely controlled from a processing and control unit (14) and signals from the remote sensor platform (12) are sent to the processing and control unit (14) where they are individually evaluated in separate data analysis subprocess steps (34, 36) to obtain a probability "score" for each of the pluralities of sensors (22, 24). These probability scores are combined in a fusion subprocess step (38) by comparing score sets to a probability table (130) which is derived based upon the historical incidence of object present conditions given that score set.