Fast Region-based Active Contour Model Driven by Local Signed Pressure Force
Azizi, Abdallah (University of Biskra (Algèria))
Elkourd, Kaouther (Preparatory School for Science & Techniques. Department of Physics (Algiers, Algèria))

Date:	2016
Abstract:	Intensity inhomogeneity is a well-known problem in image segmentation. In this paper, we present a new region-based active contour model for image segmentation which can handle intensity inhomogeneity problem. This model introduced a new region-based signed pressure force (SPF) function, which uses the local mean values provided by the local binary fitted (LBF) model. In addition, the proposed model utilizes a new regularization operation such as morphological opening and closing to regularize the level set function in the evolution process. Experimental results on synthetic and real images show that the proposed model gives satisfactory segmentation results as well as less sensitivity to the initial contour location and less time consuming compared to the LBF model.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Active contour models ; Image segmentation ; Intensity inhomogeneity ; Local image information ; Signed pressure force function
Published in:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 15 núm. 1 (2016) , p. 1-13 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v15-n01-azizi-elkourd
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/310372
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/v15-n01-azizi-elkourd
DOI: 10.5565/rev/elcvia.794

13 p, 1.4 MB

The record appears in these collections:
Articles > Published articles > ELCVIA
Articles > Research articles