Patent ID: 7010167
Filing Date: 2006-03-07
Classification: G06K,G10L

Abstract:
1. A method of geometric linear discriminant analysis pattern recognition, comprising the steps of: (a) specifying a plurality of classes for distinguishing a plurality of objects in an observation space, each of said classes having a class label; (b) collecting data about said plurality of objects in said observation space, with each of said datum having at least one feature attribute; (c) extracting said feature attributes from said data for each of said classes; (d) generating at least one d-dimensional feature vector having at least one of said feature attributes, where d is equal to the number of said feature attributes for each of said classes; (e) pairing each of said d-dimensional feature vectors with one of said class labels; (f) choosing a p number, for reducing the number of said feature attributes in said d-dimensional feature vectors to p, where p is at least one and no more than d−1; (g) generating p, d-dimensional geometric discriminant vectors from a subset of said d-dimensional feature vectors; (h) generating a p×d geometric matrix from said d-dimensional geometric discriminant vectors; (i) generating at least one classifier from said p×d geometric matrix, each of said classifiers defining a decision rule for determining said class of one of said objects; (j) applying the decision rule from each of said classifiers for each of said d-dimensional feature vectors for generating said class label for one of said objects; and (k) determining a performance for each of said classifiers.