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Proceedings Paper

Image preprocessing for classification (biometric identification) by a neural network
Author(s): Anthony R. Vannelli; Steve Wagner; Ken McGarvey
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Paper Abstract

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.

Paper Details

Date Published: 21 November 2002
PDF: 10 pages
Proc. SPIE 4790, Applications of Digital Image Processing XXV, (21 November 2002); doi: 10.1117/12.452435
Show Author Affiliations
Anthony R. Vannelli, Horizon Imaging, LLC (United States)
Steve Wagner, Horizon Imaging, LLC (United States)
Ken McGarvey, Horizon Imaging, LLC (United States)

Published in SPIE Proceedings Vol. 4790:
Applications of Digital Image Processing XXV
Andrew G. Tescher, Editor(s)

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