Cited by 1,008Medical Image Segmentation TechniquesAdvanced Vision and ImagingImage and Signal Denoising Methods

Using dynamic programming for solving variational problems in vision

Amini, A.A., Weymouth, T.E., Jain, R.C.·1990·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

Dynamic programming is discussed as an approach to solving variational problems in vision. Dynamic programming ensures global optimality of the solution, is numerically stable, and allows for hard constraints to be enforced on the behavior of the solution within a natural and straightforward structure. As a specific example of the approach's efficacy, applying dynamic programming to the energy-minimizing active contours is described. The optimization problem is set up as a discrete multistage decision process and is solved by a time-delayed discrete dynamic programming algorithm. A parallel procedure for decreasing computational costs is discussed.>

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Crossref · 10.1109/34.57681

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45 of 45 references verified0 citation errors · 0 not checkable

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Authors
Amini, A. A., Weymouth, T. E., & Jain, R. C.
Affiliations
University of Michigan (US)
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
1990
Volume
12
Issue
9
Pages
855-867
ISSN
0162-8828 (ISSN-L)
OpenAlex
W2131910503
Cited by
1,008
References
45
Citations by year
2026: 2 · 2025: 1 · 2024: 2 · 2023: 3 · 2022: 4 · 2021: 10 · 2020: 9 · 2019: 9 · 2018: 17 · 2017: 24 · 2016: 21 · 2015: 26 · 2014: 35 · 2013: 33 · 2012: 23
FWCI
9.53
Type
journal article
Language
en
Open access
closed
Locations
IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
Keywords
dynamic programming, variational problems, snakes, energy minimization, global optimality, hard constraints, multi-stage decision making, parallel computing, image segmentation

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