Neural network and wavelet multiresolution system for human being detection

Souad Haddadi; Christine Fernandez-Maloigne

doi:10.1117/12.217640

1 September 1995 Neural network and wavelet multiresolution system for human being detection

Souad Haddadi, Christine Fernandez-Maloigne

Proceedings Volume 2569, Wavelet Applications in Signal and Image Processing III; (1995) https://doi.org/10.1117/12.217640
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

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.

Citation Download Citation

Souad Haddadi and Christine Fernandez-Maloigne "Neural network and wavelet multiresolution system for human being detection", Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); https://doi.org/10.1117/12.217640

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