Abstract | ||
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Neutrosophy studies the origin, nature, scope of neutralities, and their interactions with different ideational spectra. It is a new philosophy to extend the fuzzy logic and is the basis of neutrosophic logic, neutrosophic probability, neutrosophic set, and neutrosophic statistics. Image segmentation is a key step for image processing, pattern recognition, computer vision. Many existing methods for image description, classification, and recognition highly depend on the segmentation results. In this paper, neutrosophy is applied to image processing by defining a neutrosophic domain, which is described by three subsets T, I, and F. Then we employ watershed algorithm to perform segmentation of the image in the neutrosophic domain. The experiments show that the proposed method can get better results comparing with that obtained by the existing methods. |
Year | DOI | Venue |
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2010 | 10.1016/j.sigpro.2009.10.021 | Signal Processing |
Keywords | Field | DocType |
homogeneity,indeterminacy,neutrosophic logic,watershed method,image segmentation,image description,segmentation result,watershed,neutrosophy,neutrosophic approach,neutrosophic domain,existing method,image processing,neutrosophic set,neutrosophic statistic,neutrosophic probability,fuzzy logic,computer vision,pattern recognition | Mathematical optimization,Image description,Pattern recognition,Segmentation,Fuzzy logic,Image processing,Watershed,Image segmentation,Artificial intelligence,Contextual image classification,Mathematics,Neutrosophic set | Journal |
Volume | Issue | ISSN |
90 | 5 | Signal Processing |
Citations | PageRank | References |
41 | 1.98 | 16 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Ming Zhang | 1 | 73 | 5.37 |
Ling Zhang | 2 | 143 | 14.77 |
H. D. Cheng | 3 | 1900 | 138.13 |