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Proceedings Paper

Neural network and wavelet multiresolution system for human being detection
Author(s): Souad Haddadi; Christine Fernandez-Maloigne
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Paper Abstract

Many applications, in robotics, require identification of human being. Using complex methods, based on model matching are too computationally expensive and not always justified. We propose a fast and simple method for identification of human being. This method takes profit of the learning capabilities of a neural network. The idea is to train a neural network on some images of persons. In order to reduce the amount of this data (images), we use wavelet multiresolution propriety analysis that allows to bring significant information content of image. This one thus is characterized by its approximation at a given resolution. After the training phase, the generalization capabilities of the network allow it to identify no-learned images. We describe here the proposed method, and we present experimental results obtained on a data base of 437 images.

Paper Details

Date Published: 1 September 1995
PDF: 8 pages
Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); doi: 10.1117/12.217640
Show Author Affiliations
Souad Haddadi, Univ. de Technologie de Compiegne (France)
Christine Fernandez-Maloigne, Univ. de Technologie de Compiegne (France)


Published in SPIE Proceedings Vol. 2569:
Wavelet Applications in Signal and Image Processing III
Andrew F. Laine; Michael A. Unser, Editor(s)

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