A spectral reflectance representation for recognition and reproduction
Date
2012
Authors
Ratnasingam, Sivalogeswaran
Robles-Kelly, Antonio
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Abstract
In this paper we present a method to recover a spectra representation for reproduction and recognition on multispectral imagery. To do this, we commence by viewing the spectra in the image as a mixture which can be expressed in terms of the sample mean and a set of basis vectors and weights. This treatment leads to an MAP approach where the sample means is given by the centers yielded by the application of the k-means clustering algorithm and the basis vectors are the eigenvectors of the corresponding covariance matrix. We compute the weights making use of a linear programming approach. We illustrate the utility of the method for purposes of skin recognition and spectra reconsruction.
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Keywords: Basis vector; K-Means clustering algorithm; MAP approach; Multi-spectral imagery; Sample means; Skin recognition; Spectral reflectances; Covariance matrix; Remote sensing; Pattern recognition
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Proceedings - International Conference on Pattern Recognition
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Conference paper
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2037-12-31
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