%0 Electronic Article
%A L.M. Linnett
%A D.R. Carmichael
%A S.J. Clarke
%K image texture classification
%K independent spatial Poisson processes
%K Bayesian statistical classifier
%K seafloor
%K data image classification
%K quantised image data
%K maximum likelihood discriminant function
%K sonar imaging
%K marine sediment
%K geophysical measurement technique
%K sidescan sonar image
%K Poisson model
%K texture image segmentation
%K seabed
%K spatial-point process model
%K marine geology
%K Gaussian white noise textures
%X A Bayesian statistical classifier for the segmentation of texture is presented, which models the quantised image data as a set of independent spatial Poisson processes. Two data sets are examined, namely Gaussian white noise textures, and textures contained in a sidescan sonar image of the seabed. The Poisson model is demonstrated to be applicable in both these cases, and a maximum likelihood discriminant function is developed. Finally, results are presented for the classification of both data sets.
%@ 1350-245X
%T Texture classification using a spatial-point process model
%B IEE Proceedings - Vision, Image and Signal Processing
%D February 1995
%V 142
%N 1
%P 1-6
%I
%U https://digital-library.theiet.org/;jsessionid=a625i5e0elr4n.x-iet-live-01content/journals/10.1049/ip-vis_19951678
%G EN