A NEW ALGORITHM FOR UNSUPERVISED IMAGE SEGMENTATION BASED ON D-MRF MODEL AND ANOVA
A new algorithm for unsupervised image segmentation is proposed in this paper, which is based on the D-MRF model and ANOVA. Firstly, ANOVA is incorporated to determine the number of clusters combining with several statistics. Compared with models based on information criteria, ANOVA avoids the parameter estimation error, which reduces time consumption. Secondly, histogram is adopted to verify the validity of the new algorithm. Secondly, DMRF is adopted to setup modeling. Thirdly, based on MRF-MAP, image segmentation is realized through using ICM. In model fitting, DAEM is used to estimate parameters in image field; on the other hand, local entropy is simulated as parameters in label field. Finally, the validity and practicability of the new algorithm are verified by two experiments.
Image segmentation D-MRF model ANOVA
Haiyan Sun Wenwen Wang
LMIB of the Ministry of Education, School of Mathematics and Systems Science, Beihang University, Beijing
国际会议
北京
英文
754-758
2009-11-06（万方平台首次上网日期，不代表论文的发表时间）