Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/2079
Title: Human hand recognition using IPCA-ICA algorithm
Authors: Dagher, Issam 
Kobersy, William
Abi Nader, Wassim
Affiliations: Department of Computer Engineering 
Issue Date: 2007
Part of: EURASIP journal on advances in signal processing
Volume: 2007
Issue: 1
Start page: 1
End page: 7
Abstract: 
A human hand recognition system is introduced. First, a simple preprocessing technique which extracts the palm, the four fingers, and the thumb is introduced. Second, the eigenpalm, the eigenfingers, and the eigenthumb features are obtained using a fast incremental principal non-Gaussian directions analysis algorithm, called IPCA-ICA. This algorithm is based on merging sequentially the runs of two algorithms: the principal component analysis (PCA) and the independent component analysis (ICA) algorithms. It computes the principal components of a sequence of image vectors incrementally without estimating the covariance matrix (so covariance-free) and at the same time transforming these principal components to the independent directions that maximize the non-Gaussianity of the source. Third, a classification step in which each feature representation obtained in the previous phase is fed into a simple nearest neighbor classifier. The system was tested on a database of 20 people (100 hand images) and it is compared to other algorithms.
URI: https://scholarhub.balamand.edu.lb/handle/uob/2079
Ezproxy URL: Link to full text
Type: Journal Article
Appears in Collections:Department of Computer Engineering

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