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» Supervised Image Segmentation Using Markov Random Fields
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ICIP
2008
IEEE
15 years 6 months ago
MAP-MRF approach for binarization of degraded document image
We propose an algorithm for the binarization of document images degraded by uneven light distribution, based on the Markov Random Field modeling with Maximum A Posteriori probabil...
Jung Gap Kuk, Nam Ik Cho, Kyoung Mu Lee
ICPR
2006
IEEE
16 years 27 days ago
Robust Image Registration Based on Markov-Gibbs Appearance Model
A new approach to align an image of a textured object with a given prototype is proposed. Visual appearance of the images, after equalizing their signals, is modeled with a Markov...
Alaa E. Abdel-Hakim, Aly A. Farag, Ayman El-Baz, G...
SPIESR
2004
152views Database» more  SPIESR 2004»
15 years 1 months ago
Issues in managing image and video data
This paper presents an overview of our recent work on managing image and video data. The first half of the paper describes a representation for the semantic spatial layout of vide...
Shawn D. Newsam, Jelena Tesic, Lei Wang, B. S. Man...
ICIP
1998
IEEE
16 years 1 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
CVPR
2010
IEEE
15 years 5 months ago
Facial Point Detection using Boosted Regression and Graph Models
Finding fiducial facial points in any frame of a video showing rich naturalistic facial behaviour is an unsolved problem. Yet this is a crucial step for geometric-featurebased fa...
Michel Valstar, Brais Martinez, Xavier Binefa, Maj...