TY - JOUR
T1 - Texture classification using a spatial-point process model
AU - Linnett, L. M.
AU - Carmichael, D. R.
AU - Clarke, S. J.
PY - 1995/2
Y1 - 1995/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0029252829&partnerID=8YFLogxK
U2 - 10.1049/ip-vis:19951678
DO - 10.1049/ip-vis:19951678
M3 - Article
VL - 142
SP - 1
EP - 6
JO - IEE Proceedings: Vision, Image and Signal Processing
JF - IEE Proceedings: Vision, Image and Signal Processing
IS - 1
ER -