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