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Proceedings Paper

Face recognition using the Hausdorff-Voronoi Network (HAVNET) neural network
Author(s): Usamah M.S. Altaf; Cihan H. Dagli
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Paper Abstract

Some cognitive tasks that are easy for humans are not so for computer systems. Face recognition is one of these tasks. A face recognition prototype model using the HAVNET neural network is implemented and tested. The applications of such a model are tremendous and demanding. The prototype model uses a neural network that behaves as a binary pattern classifier. The neural network used, HAVNET, utilizes the Hausdorff distance as a metric of similarity between patterns and it employs a learned version of the Voronoi surface to perform the comparison. Different human faces' images are used for training and testing the model. The recognition results as well as the different sensitive factors that affect the recognition process are discussed.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205199
Show Author Affiliations
Usamah M.S. Altaf, Univ. of Missouri/Rolla (United States)
Cihan H. Dagli, Univ. of Missouri/Rolla (United States)


Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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