Image Segmentation by Hierarchical Layered Oriented Image Foresting Transform Subject to Closeness Constraints

Autor(es)

Dolabela Santos, Luiz Felipe ; de Souza Kleine, Felipe Augusto ; Vechiatto Miranda, Paulo Andre

• Tipo de documento: Artigo Científico
• Fonte: DISCRETE GEOMETRY AND MATHEMATICAL MORPHOLOGY, DGMM 2024; v. 14605, p. 12-pg., 2024-01-01.

Resumo

In this work, we address the problem of image segmentation, subject to high-level constraints expected for the objects of interest. More specifically, we define closeness constraints to be used in conjunction with geometric constraints of inclusion in the Hierarchical Layered Oriented Image Foresting Transform (HLOIFT) algorithm. The proposed method can handle the segmentation of a hierarchy of objects with nested boundaries, each with its own expected boundary polarity constraint, making it possible to control the maximum distances (in a geodesic sense) between the successive nested boundaries. The method is demonstrated in the segmentation of nested objects in colored images with superior accuracy compared to its precursor methods and also when compared to some recent click-based methods. (AU)

• Processo FAPESP: 14/50937-1 - INCT 2014: da Internet do Futuro
• Beneficiário: Fabio Kon
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• 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