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CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
13 years 9 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
2002
IEEE
14 years 6 months ago
Multicue MRF Image Segmentation: Combining Texture and Color Features
Herein, we propose a new Markov random field (MRF) image segmentation model which aims at combining color and texture features. The model has a multi-layer structure: Each feature...
Zoltan Kato, Ting-Chuen Pong, Song Guo Qiang
AIPR
2004
IEEE
13 years 9 months ago
An Image Retrieval System Using Multispectral Random Field Models, Color, and Geometric Features
This paper describes a novel color texture-based image retrieval system for the query of an image database to find similar images to a target image. The retrieval process involves...
Orlando J. Hernandez, Alireza Khotanzad
CVPR
2008
IEEE
14 years 7 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie
AIPR
2005
IEEE
13 years 11 months ago
Face Recognition Using Multispectral Random Field Texture Models, Color Content, and Biometric Features
Most of the available research on face recognition has been performed using gray scale imagery. This paper presents a novel two-pass face recognition system that uses a Multispect...
Orlando J. Hernandez, Mitchell S. Kleiman