Graph-Based Segmentation with Local Band Constraints

Autor(es)

Braz, Caio de Moraes ; Miranda, Paulo A., V ; Ciesielski, Krzysztof Chris ; Cappabianco, Fabio A. M. ; Couprie, M ; Cousty, J ; Kenmochi, Y ; Mustafa, N

• Tipo de documento: Artigo Científico
• Fonte: DISCRETE GEOMETRY FOR COMPUTER IMAGERY, DGCI 2019; v. 11414, p. 12-pg., 2019-01-01.

Resumo

Shape constraints are potentially useful high-level priors for object segmentation, allowing the customization of the segmentation to a given target object. In this work, we present a novel shape constraint, named Local Band constraint (LB), for the generalized graph-cut framework, which in its limit case is strongly related to the Boundary Band constraint, preventing the generated segmentation to be irregular in relation to the level sets of a given reference cost map or template of shapes. The LB constraint is embedded in the graph construction with additional arcs defined by a translation-variant adjacency relation, making it easy to combine with other high-level constraints. The LB constraint demonstrates competitive results as compared to Geodesic Star Convexity, Boundary Band, and Hedgehog Shape Prior in Oriented Image Foresting Transform (OIFT) for various scenarios involving natural and medical images, with reduced sensibility to seed positioning. (AU)

• Processo FAPESP: 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo?
• Beneficiário: Alexandre Xavier Falcão
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 16/21591-5 - Desenvolvimento de métodos robustos para delineamento de bordas em imagens utilizando grafos
• Beneficiário: Fábio Augusto Menocci Cappabianco
• Modalidade de apoio: Auxílio à Pesquisa - Regular