Loop-free snakes for highly irregular object shapes

Pattern Recognition Letters

Volumn 23, Issue 5, 2002, Pages 579-591

  Ji, Lilian ^a   Yan, Hong ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Deformable model; Segmentation; Self looping suppression; Snakes; Topological adaptability

Indexed keywords

COMPUTATION THEORY; IMAGE SEGMENTATION;

OBJECT SHAPE;

PATTERN RECOGNITION;

IMAGE ANALYSIS;

EID: 0036501617     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-8655(01)00134-9     Document Type: Article

References (17)

1. Geodesic active contours
2. On active contour models and balloons
3. Active region models for segmenting textures and colours
4. Attractable snakes based on the greedy algorithm for contour extraction
5. Robust topology-adapative snakes for image segmentation
6. Snakes: Active contour models
7. Statistical shape influence in geodesic active contours
8. Shape modeling with front propagation: A level set approach IEEE
9. T-snakes: Topologically adaptive snakes
10. Geodesic active regions for supervised texture segmentation
11. Image segmentation by reaction-diffusion bubbles
12. A new method for ROI extraction from motion affected MR images based on suppression of artifacts in the image background
13. A fast algorithm for active contours and curvature estimation
14. Segmented snake for contour detection
15. Snakes, shapes, and gradient vector flow
16. A statistical approach to snakes for bimodal and trimodal imagery
17. A contour detection method: Initialization and contour model