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


Autoria(s): Miranda, Paulo A. V.; Falcao, Alexandre Xavier; Spina, Thiago V.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

21/10/2013

21/10/2013

2012

Resumo

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.

Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [09/16428-4, 07/52015-0, 09/11908-8, 11/01434-9]

Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)

Conselho Nacional de Desenvolvimento Cientiacute

Conselho Nacional de Desenvolvimento Cientiacute

fico e Tecnologico (CNPq) [481556/2009-5, 201732/2007-6, 302617/2007-8]

fico e Tecnologico (CNPq)

Identificador

IEEE TRANSACTIONS ON IMAGE PROCESSING, PISCATAWAY, v. 21, n. 6, supl. 4, Part 1, pp. 3042-3052, JUN, 2012

1057-7149

http://www.producao.usp.br/handle/BDPI/35254

10.1109/TIP.2012.2188034

http://dx.doi.org/10.1109/TIP.2012.2188034

Idioma(s)

eng

Publicador

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

PISCATAWAY

Relação

IEEE TRANSACTIONS ON IMAGE PROCESSING

Direitos

restrictedAccess

Copyright IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Palavras-Chave #GRAPH-CUT SEGMENTATION #GRAPH SEARCH ALGORITHMS #IMAGE FORESTING TRANSFORM (IFT) #WATERSHED TRANSFORM #RELATIVE FUZZY CONNECTEDNESS #LIVE-WIRE SEGMENTATION #ACTIVE SHAPE MODELS #INTERACTIVE SEGMENTATION #GRAPH CUTS #ALGORITHMS #COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE #ENGINEERING, ELECTRICAL & ELECTRONIC
Tipo

article

original article

publishedVersion