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Multivariate texture discrimination using a principal geodesic classifier
2015
2015 IEEE International Conference on Image Processing (ICIP)
A new texture discrimination method is presented for classification and retrieval of colored textures represented in the wavelet domain. The interband correlation structure is modeled by multivariate probability models which constitute a Riemannian manifold. The presented method considers the shape of the class on the manifold by determining the principal geodesic of each class. The method, which we call principal geodesic classification, then determines the shortest distance from a test
doi:10.1109/icip.2015.7351465
dblp:conf/icip/ShabbirV15
fatcat:7ull6tjmlzhz7doazhxzebwgxu