DocumentCode :
1064397
Title :
CPM: a deformable model for shape recovery and segmentation based on charged particles
Author :
Jalba, Andrei C. ; Wilkinson, Michael H F ; Roerdink, Jos B T M
Author_Institution :
Dept. of Math. & Comput. Sci., Groningen Univ., Netherlands
Volume :
26
Issue :
10
fYear :
2004
Firstpage :
1320
Lastpage :
1335
Abstract :
A novel, physically motivated deformable model for shape recovery and segmentation is presented. The model, referred to as the charged-particle model (CPM), is inspired by classical electrodynamics and is based on a simulation of charged particles moving in an electrostatic field. The charges are attracted towards the contours of the objects of interest by an electrostatic field, whose sources are computed based on the gradient-magnitude image. The electric field plays the same role as the potential forces in the snake model, while internal interactions are modeled by repulsive Coulomb forces. We demonstrate the flexibility and potential of the model in a wide variety of settings: shape recovery using manual initialization, automatic segmentation, and skeleton computation. We perform a comparative analysis of the proposed model with the active contour model and show that specific problems of the latter are surmounted by our model. The model is easily extendable to 3D and copes well with noisy images.
Keywords :
electric fields; electrodynamics; image reconstruction; image segmentation; active contour model; charged-particle model; deformable model; electrodynamics; electrostatic field; gradient-magnitude image; image segmentation; noisy images; repulsive Coulomb forces; shape recovery; skeleton computation; snake model; Active contours; Computational modeling; Deformable models; Electrodynamics; Electrostatics; Image segmentation; Noise shaping; Performance analysis; Shape; Skeleton; Coulomb force; Index Terms- Deformable model; charged-particle system; electrostatic field; segmentation; shape recovery; skeleton.; Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Models, Biological; Models, Statistical; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Stochastic Processes;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2004.84
Filename :
1323800
Link To Document :
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