DocumentCode :
507321
Title :
Multiscale Cascade Segmentation of Deformable Image and Parameters Evaluation
Author :
Xiang, Long ; Tao, Zhang
Author_Institution :
Dept. of Electron. Inf. Eng., Hainan Univ., Haikou, China
Volume :
5
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
405
Lastpage :
409
Abstract :
Methods based on deformable model have been widely used in deformable image segmentation. The segmentation quality of this kind of methods strongly relies on its initialization. If the initiation isn´t accurate, the segmentation result will not be satisfactory. To solve this problem, we propose a new deformable image cascade segmentation method. In the method, the MSRF and SMAP will be used to estimate motion parameters of the background of image sequence. From the result of simulation, we can conclude that the segmentation method is satisfactory.
Keywords :
image segmentation; parameter estimation; deformable image segmentation; motion parameter estimation; multiscale cascade segmentation; parameter evaluation; Cameras; Deformable models; Educational institutions; Fuzzy systems; Image segmentation; Image sequences; Information science; Knowledge engineering; Motion estimation; Potential energy; Multiscale Random Field; cascade segmentation; global motion; snake model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.82
Filename :
5360588
Link To Document :
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