Image pre-processing for classification (biometric identification) by a neural network
Anthony Vannelli, Steve Wagner, K. Vilalta McGarvey · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
For many image classification applications it is not adequate to take a simple feature extraction approach. A non-parametric approach directly applied to an image can easily result in a problem with a dimension, which can exceed 2^18. Practical application of a neural network classifier requires that some reduction of the image dimension be done prior to classification. This paper compares the performance of several approaches to the problem. Use of wavelets, principal components, and "image zones" are explored in various combinations. The techniques are compared on a specific biometric application.