Patent ID: 8429153
Filing Date: 2013-04-23
Classification: G06F,G06K

Abstract:
1. A computer-implemented method of determining a similarity metric for use in classifying an unknown specimen having spectral data to a reference group of a plurality of different reference groups of a reference collection of specimens having spectral data of a spectral database and storing a trait of the unknown specimen in the spectral database, the method comprising: reducing a dimension of input spectral data of the spectral database of the reference collection using a data processor; storing a first input trait of the unknown specimen in memory; receiving an input selecting a similarity metric of a plurality of different similarity metrics to classify the unknown specimen to the reference group of the reference collection of specimens, wherein the similarity metric is selected as one of Manhattan, Canberra, similarity index, cosine and Euclidean distance; determining at least one similarity threshold value associated with the spectral data of the reference group of the reference collection via the data processor responsive to the selected similarity metric for classifying the unknown specimen to the reference group of the reference collection of specimens; and predicting a value of a second different trait of the unknown specimen by determining membership of the unknown specimen in the reference group of the reference collection of specimens, the spectral database storing the second different trait of the reference group of specimens for output once membership of the unknown specimen in the reference group is determined by the data processor.