Title
Image segmentation by image foresting transform with non-smooth connectivity functions
Date Issued
01 December 2013
Access level
metadata only access
Resource Type
conference paper
Author(s)
University of Sao Paulo
Abstract
In the framework of the Image Foresting Transform (IFT), there is a class of connectivity functions that were vaguely explored, which corresponds to the non-smooth connectivity functions (NSCF). These functions are more adaptive to cope with the problems of field in homogeneity, which are common in MR images of 3 Tesla. In this work, we investigate the NSCF from the standpoint of theoretical and experimental aspects. We formally classify several non-smooth functions according to a proposed diagram representation. Then, we investigate some theoretical properties for some specific regions of the diagram. Our analysis reveals that many NSCFs are, in fact, the result of a sequence of optimizations, each of them involving a maximal set of elements, in a well-structured way. Our experimental results indicate that substantial improvements can be obtained by NSCFs in the 3D segmentation of MR images of 3 Tesla, when compared to smooth connectivity functions. © 2013 IEEE.
Start page
147
End page
154
Language
English
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones
Subjects
Scopus EID
2-s2.0-84891546702
Source
Brazilian Symposium of Computer Graphic and Image Processing
Resource of which it is part
Brazilian Symposium of Computer Graphic and Image Processing
ISSN of the container
15301834
ISBN of the container
9780769550992
Conference
6th Conference on Graphics, Patterns and Images, SIBGRAPI 20135 August 2013through 8 August 2013
Sources of information:
Directorio de Producción Científica
Scopus