Patent ID: 7218775

Claim:
A method for identifying or quantifying one or more characteristics of interest of unknown objects, comprising the steps of: A training of a single neural network model with a first and a second training set of known objects having known values for the one or more characteristics of interest by selecting known objects having known values for the one or more characteristics of interest; arranging the known objects into a spectrum according to increasing degree of expression of the one or more characteristics of interest; segregating the known objects into a first and a second training set corresponding to a predetermined state of the one or more characteristics of interest; imaging each of the first and second training sets to obtain an original digital image for each of the training sets; processing and analyzing the original digital image to generate data representative of one or more image parameters for each of the known objects; providing the data to neural network software to generate multiple candidate neural network models; and choosing an optimal neural network model from the multiple candidate neural network models; B validating the optimal neural network model by selecting more than one sample of the known objects having known values for the one or more characteristics of interest; imaging each sample to obtain an original digital image for each sample; processing and analyzing the digital image to generate data representative of one or more image parameters for each of the known objects; providing the data to the optimal neural network model to evaluate output data for accuracy and repeatability; and C analyzing unknown objects having unknown values of the one or more characteristics of interest, comprising the steps of: I imaging the unknown objects having unknown values of the one or more characteristics of interest against a background to obtain an original digital image, wherein the original digital image comprises pixels representing the unknown objects, the background and any debris; II processing the original digital image to identify, separate, and retain the pixels representing the unknown objects from the pixels representing the background and the pixels representing any debris, and to eliminate the background and any debris; III analyzing the pixels representing each of the unknown objects to generate data representative of one or more image parameters for each of the unknown objects; IV providing the data to a chosen flash code deployed from the candidate neural network model; V analyzing the data through the flash code; and VI receiving the output data from the flash code in a predetermined format, wherein the output data represents the unknown values of the one or more characteristics of interest of the unknown objects.