Forensic integrated search technology

A method comprising:

• providing a library having a plurality of sublibraries, wherein each sublibrary contains a plurality of reference data sets generated by a corresponding one of a plurality of spectroscopic data generating instruments associated with the sublibrary, and wherein each reference data set characterizes a corresponding known material;
• obtaining a plurality of test data sets characteristic of an unknown material, wherein each test data set is generated by one or more of the plurality of spectroscopic data generating instruments,
• for each test data set, searching each sublibrary associated with the spectroscopic data generating instrument used to generate said test data set, to thereby produce a corresponding set of scores for each searched sublibrary, wherein each score in said set of scores indicates a likelihood of a match between a corresponding one of said plurality of reference data sets in said searched sublibrary and said test data set;
• calculating a set of relative probability values for each searched sublibrary based on the corresponding set of scores for each searched sublibrary;
• fusing all relative probability values for each searched sublibrary to thereby produce a set of final probability values to be used in determining whether said unknown material is represented through a corresponding known material in the library.

A method comprising:

• providing a library having a plurality of sublibraries, wherein each sublibrary contains a plurality of reference data sets generated by a corresponding one of a plurality of spectroscopic data generating instruments associated with the sublibrary, and wherein each reference data set characterizes a corresponding known material, wherein one sublibrary comprises an image sublibrary containing a set of reference feature data, wherein each said set of reference feature data includes one or more of the following:
• particle size, color value, and morphology data;
• obtaining a plurality of test data sets characteristic of an unknown material, wherein each test data set is generated by one of the plurality of spectroscopic data generating instruments and one test data set comprises an image test data set generated by an image generating instrument
• extracting a set of test feature data from the image test data set, using a feature extraction algorithm, said test feature data comprising one or more of the following:
• particle size, color value, and morphology;
• for said test feature data, searching said image sublibrary to compare each set of reference feature data with said set of test feature data to thereby produce a set of scores, wherein each score in said set of scores indicates a likelihood of a match between a corresponding set of reference feature data in said searched image sublibrary and said set of test feature data;
• for each test data set, searching each sublibrary associated with the spectroscopic data generating instrument used to generate said test data set, to thereby produce a corresponding set of scores for each searched sublibrary, wherein each score in said set of scores indicates a likelihood of a match between a corresponding one of said plurality of reference data sets in said searched sublibrary and said test data set;
• calculating a set of relative probability values for each searched sublibrary based on the corresponding set of scores for each searched sublibrary and a set of relative probability values for the image sublibrary based on the corresponding set of scores for the image sublibrary;
• fusing all relative probability values for each searched sublibrary and search image sublibrary to thereby produce a set of final probability values to be used in determining whether said unknown material is represented through a corresponding known material characterized in the library;
• reporting the known material represented in the library having the highest final probability value, if the highest final probability value is greater than or equal to the minimum confidence value.

A system comprising:

• a library having a plurality of sublibraries, wherein each sublibrary contains a plurality of reference data sets generated by a corresponding one of a plurality of spectroscopic data generating instruments associated with the sublibrary, and wherein each reference data set characterizes a corresponding known material;
• a plurality of spectroscopic data generating instruments;
• a plurality of test data sets characteristic of an unknown material, wherein each test data set is generated by one or more of the plurality of spectroscopic data generating instruments,
• a processor for:
• searching each sublibrary associated with the spectroscopic data generating instrument used to generate said test data set, to thereby produce a corresponding set of scores for each searched sublibrary, wherein each score in said set of scores indicates a likelihood of a match between a corresponding one of said plurality of reference data sets in said searched sublibrary and said test data set;
• calculating a set of relative probability values for each searched sublibrary based on the corresponding set of scores for each searched sublibrary;
• and
• fusing all relative probability values for each searched sublibrary to thereby produce a set of final probability values to be used in determining whether said unknown material is represented through a corresponding known material characterized in the library.