Effective Image Segmentation with Flexible ICM-Based Markov Random Fields in Distributed Systems of Personal Computers-Reference-Cited by-同舟云学术

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Effective Image Segmentation with Flexible ICM-Based Markov Random Fields in Distributed Systems of Personal Computers

Published:2000-08 Issue:4 Volume:6 Page:283-295
ISSN:1077-2014
Container-title:Real-Time Imaging
language:en
Short-container-title:Real-Time Imaging

Author:

Bruno Odemir Martinez,da Fontoura Costa Luciano

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing

Reference22 articles.

1. Poggio, T. Torrel, V. Koch, C. Computational vision and regularization theory, Nature, 317, 314, 319

2. Visual Reconstruction;Blake,1987

3. Variational Methods in Image Segmentation;Morel,1994

4. Markov Random Field Modeling in Computer Vision;Li,1995

5. Møller, J. Lectures on Markov random fields, Department of Theoretical Statistics, University of Aarhus

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Generalized ICM for image segmentation based on Tsallis statistics;Physica A: Statistical Mechanics and its Applications;2012-10

2. Application of probabilistic imaging techniques to real-time systems;Journal of Real-Time Image Processing;2006-03

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