On Design of Discriminant Analysis Diagram for Error Based Pattern Recognition

Abstract

Discriminant analysis diagram (DAD) as a methodology for design of error based pattern recognition systems is presented. Recognition, i.e.verification, identification, and indexing of patterns is based on their intra-class errors when pattern classes used in training time are different than classes recognized in system exploiting time. The situation is typical for biometric identity verification. DAD is a labeled directed graph with the distinguished source node, sink node, and other nodes representing various discriminant features of recognized object. The edge label represents one of vector transformations: data centering, orthogonal projection onto linear subspace, vector component scaling, and orthogonal projection onto unit sphere. Linear subspaces are spanned over global, intra-class, and inter-class errors. A path from the source node to the sink node defines a basic discrimination scheme which is identified by sequential composition of subspace projections interleaved by scaling operations and single projection onto unit sphere. In the current state of development, DAD defines 24 different linear discriminant schemes for which there exist also nonlinear kernel forms. The proposed methodology is illustrated by a face verification system.