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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- davatzikos, 1994, Convexity analysis of active contour models, Proc Conf Information Science and Systems, 581
- terzopoulos, 1992, Active Vision, 3
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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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