The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 18, 2000

Filed:

Sep. 03, 1998
Applicant:
Inventors:

Nadav Horesh, Petah Tikva, IL;

Danny S Moshe, Kiryat Ono, IL;

Assignee:

Greenvision Systems Ltd., Tel Aviv, IL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K / ; G06K / ; G01N / ;
U.S. Cl.
CPC ...
382133 ; 382128 ; 382224 ; 2504611 ; 356318 ; 435-4 ;
Abstract

A method of analyzing particles for chemical or biological species. Spectral images of the particles are acquired. Targets are identified in the images and are classified according to morphology type and spectrum type. Each target is assigned a value of an extensive property. A descriptor vector is formed, each element of the descriptor vector being the sum of the extensive property values for one target class. The descriptor vector is transformed to a vector of mass concentrations of chemical species of interest, or of number concentrations of biological species of interest, using a relationship determined in a calibration procedure. In the calibration procedure, spectral images of calibration samples of known composition are acquired, and empirical morphology types and spectrum types are inferred from the spectral images. Targets are identified in the spectral images, classified according to morphology type and spectrum type, and assigned values of an extensive property. For each calibration sample, a calibration descriptor vector and a calibration concentration vector is formed. A collective relationship between the calibration descriptor vectors and the calibration concentration vectors is found, either by multivariate analysis or by training a neural network.


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