Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-8655(00)00106-9
Title: Color image segmentation and parameter estimation in a markovian framework
Authors: Kato, Z. 
Pong, T.-C.
Chung-Mong Lee, J.
Keywords: Color
Markov random field
Parameter estimation
Pixel classification
Unsupervised image segmentation
Issue Date: 2001
Source: Kato, Z., Pong, T.-C., Chung-Mong Lee, J. (2001). Color image segmentation and parameter estimation in a markovian framework. Pattern Recognition Letters 22 (3-4) : 309-321. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-8655(00)00106-9
Abstract: An unsupervised color image segmentation algorithm is presented, using a Markov random field (MRF) pixel classification model. We propose a new method to estimate initial mean vectors effectively even if the histogram does not have clearly distinguishable peaks. The only parameter supplied by the user is the number of classes. © 2001 Elsevier Science B.V. All rights reserved.
Source Title: Pattern Recognition Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/38965
ISSN: 01678655
DOI: 10.1016/S0167-8655(00)00106-9
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