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

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Author(s):	Dolabela Santos, Luiz Felipe ; de Souza Kleine, Felipe Augusto ; Vechiatto Miranda, Paulo Andre Total Authors: 3
Document type:	Journal article
Source:	DISCRETE GEOMETRY AND MATHEMATICAL MORPHOLOGY, DGMM 2024; v. 14605, p. 12-pg., 2024-01-01.
Abstract
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)

FAPESP's process:	14/50937-1 - INCT 2014: on the Internet of the Future
Grantee:	Fabio Kon
Support Opportunities:	Research Projects - Thematic Grants


FAPESP's process:	14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:	Alexandre Xavier Falcão
Support Opportunities:	Research Projects - Thematic Grants