IEEE Trans Image Process - Riverbed: a novel user-steered image segmentation method based on optimum boundary tracking.

Tópicos

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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.

Resumo Limpo

paper present optimum userst boundari track approach imag segment simul behavior water flow riverb riverb approach devis use imag forest transform neverexploit connect function analyz properti deriv imag graph discuss theoret relat popular method live wire graph cut sever experi show riverb can signific reduc number user interact anchor point compar live wire object complex shape paper also includ discuss combin differ method order take advantag complementari strength

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