Grey-level hit-or-miss transforms—part II : application to angiographic image processing

Naegel, Benoît (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Passat, Nicolas (LSIIT, UMR 7005 CNRS-ULP (Laboratoire des Sciences de l’Image, de l’Informatique et de la Télédétection), Illkirch Cedex, France ; Institut Gaspard Monge, Laboratoire A2SI (Algorithmique et Architecture des Systèmes Informatiques), Groupe ESIEE, Cité Descartes, Noisy-le-Grand Cedex, France) ; Ronse, Christian (LSIIT, UMR 7005 CNRS-ULP (Laboratoire des Sciences de l’Image, de l’Informatique et de la Télédétection), Illkirch Cedex, France)

The hit-or-miss transform (HMT) is a fundamental operation on binary images, widely used since 40 years. As it is not increasing, its extension to grey-level images is not straightforward, and very few authors have considered it. Moreover, despite its potential usefulness, very few applications of the grey-level HMT have been proposed until now. Part I of this paper [B. Naegel, N. Passat, C. Ronse, Grey-level hit-or-miss transforms—part I: unified theory. Pattern Recogn., in press doi:10.1016/j.patcog.2006.06.004] was devoted to the description of a theory enabling to unify the main definitions of the grey-level HMT, mainly proposed by Ronse and Soille, respectively. Part II of this paper, developed hereafter, deals with the applicative potential of the grey-level HMT, illustrated by its use for vessel segmentation from 3D angiographic data. Different HMT-based segmentation methods are then described and analysed, leading to concrete analysis techniques for brain and liver vessels, but also providing algorithmic strategies which could further be used for many other kinds of image processing applications.


Keywords:
Article Type:
scientifique
Faculty:
Ingénierie et Architecture
School:
HEPIA - Genève
Institute:
inSTI - Institut des Sciences et Technologies industrielles
Date:
2007-02
Pagination:
11 p.
Published in:
Pattern Recognition
Numeration (vol. no.):
2007, vol. 40, no. 2, pp. 648-658
DOI:
ISSN:
0031-3203
Appears in Collection:

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 Record created 2020-04-24, last modified 2020-05-29

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