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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

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Miranda, Paulo A. V. [1] ; Falcao, Alexandre Xavier [2] ; Spina, Thiago V. [2]
Total Authors: 3
[1] Univ Sao Paulo, Inst Math & Stat IME, BR-05508090 Sao Paulo - Brazil
[2] Univ Estadual Campinas, Inst Comp, Dept Informat Syst, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: IEEE Transactions on Image Processing; v. 21, n. 6, p. 3042-3052, JUN 2012.
Web of Science Citations: 24

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths. (AU)

FAPESP's process: 11/01434-9 - Interactive segmentation of objects in digital video using graphs and fuzzy models of content knowledge
Grantee:Thiago Vallin Spina
Support type: Scholarships in Brazil - Doctorate (Direct)
FAPESP's process: 07/52015-0 - Approximation methods for visual computing
Grantee:Jorge Stolfi
Support type: Research Projects - Thematic Grants
FAPESP's process: 09/11908-8 - User-steered editing of natural images based on the image foresting transform
Grantee:Thiago Vallin Spina
Support type: Scholarships in Brazil - Master
FAPESP's process: 09/16428-4 - Segmentation of human brain structures from magnetic resonance images of multiple modalities
Grantee:Paulo André Vechiatto de Miranda
Support type: Scholarships in Brazil - Post-Doctorate