Face recognition using the Hausdorff-Voronoi Network (HAVNET) neural network

Usamah M.S. Altaf; Cihan H. Dagli

doi:10.1117/12.205199

6 April 1995 Face recognition using the Hausdorff-Voronoi Network (HAVNET) neural network

Usamah M.S. Altaf, Cihan H. Dagli

Proceedings Volume 2492, Applications and Science of Artificial Neural Networks; (1995) https://doi.org/10.1117/12.205199
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Usamah M.S. Altaf and Cihan H. Dagli "Face recognition using the Hausdorff-Voronoi Network (HAVNET) neural network", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); https://doi.org/10.1117/12.205199

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