A Markov random field image segmentation model using combined color and texture features

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2124, Issue , 2001, Pages 547-554

  Kato, Zoltan ^a   Pong, Ting Chuen ^b  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Image segmentation; Markov random field model

Indexed keywords

BAYESIAN NETWORKS; COLOR; COLOR IMAGE PROCESSING; COMBINATORIAL OPTIMIZATION; GABOR FILTERS; IMAGE ANALYSIS; IMAGE TEXTURE; MAGNETORHEOLOGICAL FLUIDS; MARKOV PROCESSES; PIXELS; SIMULATED ANNEALING; STRUCTURAL FRAMES; TEXTURES; WHITE NOISE;

ADDITIVE WHITE NOISE; BAYESIAN ESTIMATIONS; COLOR AND TEXTURE FEATURES; IMAGE SEGMENTATION MODEL; MARKOV RANDOM FIELD MODEL; MARKOV RANDOM FIELDS; NATURAL COLOR IMAGES; THEORETICAL FRAMEWORK;

IMAGE SEGMENTATION;

EID: 84947923186     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44692-3_66     Document Type: Conference Paper

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