Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models
Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models
复制标题
使用马尔可夫随机场和 Potts 模型通过模拟退火进行基于无监督纹理的图像分割
DOI：
10.1109/icpr.1998.711275
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发表时间：
1998
期刊：
影响因子：
--
通讯作者：
C. Yalabik
中科院分区：
文献类型：
--
作者：
M. Goktepe;V. Atalay;N. Yalabik;C. Yalabik
研究了由不同纹理组成的图像的无监督分割问题。粗分割是通过一个层次化的自组织映射实现的。该初始分割结果被输入模拟退火算法，其中使用最大似然技术估计区域和纹理参数。区域的几何形状被建模为波茨模型，而纹理被建模为马尔可夫随机场。在人工纹理图像上进行测试。
Unsupervised segmentation of images which are composed of various textures is investigated. A coarse segmentation is achieved through a hierarchical self organizing map. This initial segmentation result is fed into a simulated annealing algorithm in which region and texture parameters are estimated using a maximum likelihood technique. Region geometries are modeled as Potts model while textures are modeled as Markov random fields. Tests are performed on artificial textured images.