Minimum Likelihood Image Feature and Scale Detection Based on the Brownian Image Model
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Minimum Likelihood Image Feature and Scale Detection Based on the Brownian Image Model. / Pedersen, Kim Steenstrup; van Dorst, Pieter; Loog, Marco.
2006, Andet.Research output: Other contribution › Research
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TY - GEN
T1 - Minimum Likelihood Image Feature and Scale Detection Based on the Brownian Image Model
AU - Pedersen, Kim Steenstrup
AU - van Dorst, Pieter
AU - Loog, Marco
PY - 2006
Y1 - 2006
N2 - We present a novel approach to image feature and scale detection based on the fractional Brownian image model in which images are realisations of a Gaussian random process on the plane. Image features are points of interest usually sparsely distributed in images. We propose to detect such points and their intrinsic scale by detecting points in scale-space that locally minimises the likelihood under the model.
AB - We present a novel approach to image feature and scale detection based on the fractional Brownian image model in which images are realisations of a Gaussian random process on the plane. Image features are points of interest usually sparsely distributed in images. We propose to detect such points and their intrinsic scale by detecting points in scale-space that locally minimises the likelihood under the model.
M3 - Other contribution
ER -
ID: 4850836