Paper Info
Title
Segmentation using the edge strength function as a shape prior within a local deformation model
Abstract
This paper presents a new image segmentation framework which employs a shape prior in the form of an edge strength function to introduce a higher-level influence on the segmentation process. We formulate segmentation as the minimization of three coupled functionals, respectively, defining three processes: prior-guided segmentation, shape feature extraction and local deformation estimation. Particularly, the shape feature extraction process is in charge of estimating an edge strength function from the evolving object region. The local deformation estimation process uses this function to determine a meaningful correspondence between a given prior and the evolving object region, and the deformation map estimated in return supervises the segmentation by enforcing the evolving object boundary towards the prior shape.
Year
DOI
Venue
2009
10.1109/ICIP.2009.5414504
ICIP
Keywords
Field
DocType
prior-based image segmentation,local deformation estimation,local deformation model,shape feature extraction,segmentation process,image segmentation,edge strength function,prior shape,object boundary,object region,estimation theory,shape feature extraction process,feature extraction,variational methods,edge detection,deformation map,prior-guided segmentation,registration,new image segmentation framework,level set,mathematical model,variational method,computational modeling,shape
Computer vision,Scale-space segmentation,Pattern recognition,Edge detection,Segmentation,Computer science,Level set,Segmentation-based object categorization,Image segmentation,Feature extraction,Artificial intelligence,Estimation theory
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-5655-0
978-1-4244-5655-0
3
PageRank 
References 
Authors
0.42
11
3
Name
Order
Citations
PageRank
Erkut Erdem157333.86
Sibel Tari216413.29
Luminita A. Vese35389302.64