Identifying Contours with Selective Local or Global Segmentation Using a Native Formulation and Level Set Method

Authors(2) :-Sonali Dayal, Apoorv Mishra

A novel region-based active contour model (ACM) is proposed in this paper. It is implemented with a special processing named Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) method, which first selectively penalizes the level set function to be binary, and then uses a Gaussian smoothing kernel to regularize it. The advantages of our method are as follows. First, a new region-based signed pressure force (SPF) function is proposed, which can efficiently stop the contours at weak or blurred edges. Second, the exterior and interior boundaries can be automatically detected with the initial contour being anywhere in the image. Third, the proposed ACM with SBGFRLS has the property of selective local or global segmentation. It can segment not only the desired object but also the other objects. Fourth, the level set function can be easily initialized with a binary function, which is more efficient to construct than the widely used signed distance function (SDF). The computational cost for traditional re-initialization can also be reduced. Finally, the proposed algorithm can be efficiently implemented by the simple finite difference scheme. Experiments on synthetic and real images demonstrate the advantages of the proposed method over geodesic active contours (GAC) and Chan–Vese (C–V) active contours in terms of both efficiency and accuracy.

Authors and Affiliations

Sonali Dayal
Department of Computer Science, Naraina Group of Institutions, Kanpur, Uttar Pradesh, India
Apoorv Mishra
Department of Computer Science, Naraina Group of Institutions, Kanpur, Uttar Pradesh, India

Active contours, Geodesic active contours, Chan–Vese model, Image segmentation, Level set method

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 2017-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 564-567
Manuscript Number : CSEIT1723203
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sonali Dayal, Apoorv Mishra, "Identifying Contours with Selective Local or Global Segmentation Using a Native Formulation and Level Set Method", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.564-567, May-June-2017.
Journal URL : http://ijsrcseit.com/CSEIT1723203

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