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ICIP
2005
IEEE
14 years 10 months ago
A segmentation method using compound Markov random fields based on a general boundary model
Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
Jue Wu, Albert C. S. Chung
CVPR
2005
IEEE
14 years 10 months ago
Bayesian Image Segmentation Using Wavelet-Based Priors
This paper introduces a formulation which allows using wavelet-based priors for image segmentation. This formulation can be used in supervised, unsupervised, or semisupervised mod...
Mário A. T. Figueiredo
CVPR
2008
IEEE
14 years 10 months ago
From appearance to context-based recognition: Dense labeling in small images
Traditionally, object recognition is performed based solely on the appearance of the object. However, relevant information also exists in the scene surrounding the object. As supp...
Devi Parikh, C. Lawrence Zitnick, Tsuhan Chen
EUSFLAT
2001
183views Fuzzy Logic» more  EUSFLAT 2001»
13 years 10 months ago
On fuzzy rule-based algorithms for image segmentation using gray-level histogram analysis
One of the biggest problems in computer vision systems, analyzing images having high uncertainty/vagueness degree, is the treatment of such uncertainty. This problem is even clear...
Eduard Montseny, Pilar Sobrevilla
ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
13 years 6 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang