Title
Oriented image foresting transform segmentation with connectivity constraints
Date Issued
03 August 2016
Access level
metadata only access
Resource Type
conference paper
Author(s)
Miranda P.
Cappabianco F.
University of São Paulo
Publisher(s)
IEEE Computer Society
Abstract
A new algorithm, named Connected Oriented Image Foresting Transform (COIFT), is proposed, which provides global optimum solutions according to a graph-cut measure, subject to high-level boundary constraints. COIFT incorporates the connectivity constraint in the Oriented Image Foresting Transform (OIFT), ensuring the generation of connected objects, and can also handle simultaneously the boundary polarity. While the connectivity constraint usually leads to NP-hard problems in other frameworks, such as the min-cut/max-flow algorithm, COIFT conserves the low complexity of the OIFT algorithm. Experiments show that COIFT can improve the segmentation of thin and elongated objects, for the same amount of user interaction.
Start page
2554
End page
2558
Volume
2016-August
Language
English
OCDE Knowledge area
Matemáticas Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-85006717874
Source
Proceedings - International Conference on Image Processing, ICIP
Resource of which it is part
Proceedings - International Conference on Image Processing, ICIP
ISSN of the container
15224880
ISBN of the container
978-146739961-6
Conference
23rd IEEE International Conference on Image Processing, ICIP 2016
Sponsor(s)
The Institute of Electrical and Electronics Engineers Signal Processing Society
Sources of information: Directorio de Producción Científica Scopus