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Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation
Open accessAbstract
Images are by nature fuzzy. Approaches to object information extraction from images should attempt to use this fact and retain fuzziness as realistically as possible. In past image segmentation research, the notion of “hanging togetherness” of image elements specified by their fuzzy connectedness has been lacking. We present a theory of fuzzy objects forn-dimensional digital spaces based on a notion of fuzzy connectedness of image elements. Although our definitions lead to problems of enormous combinatorial complexity, the theoretical results allow us to reduce this dramatically, leading us to practical algorithms for fuzzy object extraction. We present algorithms for extracting a specified fuzzy object and for identifying all fuzzy objects present in the image data. We demonstrate the utility of the theory and algorithms in image segmentation based on several practical examples all drawn from medical imaging.
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Cited by
An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation
Liew, A. W.-C., & Yan, H. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.816956 · Cited by 316
Kumar, A. (2000) · Neuropsychopharmacology · doi:10.1016/s0893-133x(99)00124-4 · Cited by 181
Interactive segmentation of image volumes with Live Surface
Armstrong, C. J., Price, B. L., & Barrett, W. A. (2007) · Computers & Graphics · doi:10.1016/j.cag.2006.11.015 · Cited by 53
Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step
Rueda, S., Knight, C. L., Papageorghiou, A. T., & Alison Noble, J. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.07.002 · Cited by 30
GPU accelerated fuzzy connected image segmentation by using CUDA
Zhuge, Y., Cao, Y., & Miller, R. W. (2009) · 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/iembs.2009.5333158 · Cited by 19
Metadata
- Authors
- Udupa, J. K., & Samarasekera, S.
- Venue
- Graphical Models and Image Processing
- Publisher
- Elsevier BV
- Published
- 1996-05
- Volume
- 58
- Issue
- 3
- Pages
- 246-261
- ISSN
- 1077-3169 (ISSN-L)
- OpenAlex
- W2113622874
- Cited by
- 839
- References
- 0
- FWCI
- 16.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Udupa, J. K., & Samarasekera, S. (1996). Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation. Graphical Models and Image Processing. https://doi.org/10.1006/gmip.1996.0021
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