The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.
Snakes, shapes, and gradient vector flow
Abstract
Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This paper presents a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. It differs fundamentally from traditional snake external forces in that it cannot be written as the negative gradient of a potential function, and the corresponding snake is formulated directly from a force balance condition rather than a variational formulation. Using several two-dimensional (2-D) examples and one three-dimensional (3-D) example, we show that GVF has a large capture range and is able to move snakes into boundary concavities.
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Cites
Kass, M., Witkin, A., & Terzopoulos, D. (1988) · International Journal of Computer Vision · doi:10.1007/bf00133570 · Cited by 17,330
Methods of Theoretical Physics
Morse, P. M., Feshbach, H., & Hill, E. L. (1954) · American Journal of Physics · doi:10.1119/1.1933765 · Cited by 13,197
Horn, B. K. P., & Schunck, B. G. (1981) · Artificial Intelligence · doi:10.1016/0004-3702(81)90024-2 · Cited by 10,312
Methods of Mathematical Physics
Courant, R., & Hilbert, D. R. (1989) · Wiley eBooks · doi:10.1002/9783527617210 · Cited by 8,151
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Fundamentals of digital image processing
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Caselles, V., Kimmel, R., & Sapiro, G. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007979827043 · Cited by 5,285
Methods of theoretical physics
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Fundamentals of digital image processing
(1989) · Computer Vision Graphics and Image Processing · doi:10.1016/0734-189x(89)90041-8 · Cited by 4,703
Shape modeling with front propagation: a level set approach
Malladi, R., Sethian, J. A., & Vemuri, B. C. (1995) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.368173 · Cited by 3,166
Flagged first, then by citations
1 of the 32 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- davatzikos, 1994, Convexity analysis of active contour models, Proc Conf Information Science and Systems, 581
- terzopoulos, 1992, Active Vision, 3
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Medical image segmentation with deformable models on graphics processing units
Alvarado, R., Tapia, J. J., & Rolón, J. C. (2014) · The Journal of Supercomputing · doi:10.1007/s11227-013-1042-4 · Cited by 10
Metadata
- Authors
- Xu, C., & Prince, J. L.
- Affiliations
- Johns Hopkins University (US)
- Venue
- IEEE Transactions on Image Processing
- Published
- 1998-03
- Volume
- 7
- Issue
- 3
- Pages
- 359-369
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2145803225
- Cited by
- 4,001
- References
- 32
- Citations by year
- 2026: 26 · 2025: 30 · 2024: 38 · 2023: 48 · 2022: 62 · 2021: 85 · 2020: 78 · 2019: 110 · 2018: 99 · 2017: 135 · 2016: 165 · 2015: 221 · 2014: 236 · 2013: 243 · 2012: 274
- FWCI
- 35.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Image Processing (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Object Detection Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Keywords
- snakes, gradient vector flow, external forces, edge maps, gradient diffusion, force balance, object boundary detection
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