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124
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CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
15 years 4 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
ICPR
2000
IEEE
16 years 20 days ago
Color and/or Texture Segmentation Using Deterministic Relaxation and Fast Marching Algorithms
The segmentation of colored texture images is considered. Either luminance, color, and/or texture features could be used for segmentation. For luminance and color the classes are ...
Spyros Liapis, Eftychios Sifakis, George Tziritas
122
Voted
TIP
2002
179views more  TIP 2002»
14 years 11 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
VCIP
2003
238views Communications» more  VCIP 2003»
15 years 29 days ago
Texture segmentation based on features in wavelet domain for image retrieval
Texture is a fundamental feature which provides significant information for image classification, and is an important content used in content-based image retrieval (CBIR) system. ...
Ying Liu, Si Wu, Xiaofang Zhou
IBPRIA
2009
Springer
15 years 4 months ago
Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation
A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that...
Filiberto Pla, Gema Gracia, Pedro García-Se...