TY - GEN
T1 - A spectral reflectance representation for recognition and reproduction
AU - Ratnasingam, Sivalogeswaran
AU - Robles-Kelly, Antonio
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84874581413&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 1900
EP - 1903
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -