Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14686
Title: Active contours driven by local image fitting energy
Authors: Zhang, K
Song, H
Zhang, L 
Keywords: Active contour models
Chan-Vese (C-V) model
Image segmentation
LBF model
Issue Date: 2010
Publisher: Elsevier
Source: Pattern recognition, 2010, v. 43, no. 4, p. 1199-1206 How to cite?
Journal: Pattern recognition 
Abstract: A new region-based active contour model that embeds the image local information is proposed in this paper. By introducing the local image fitting (LIF) energy to extract the local image information, our model is able to segment images with intensity inhomogeneities. Moreover, a novel method based on Gaussian filtering for variational level set is proposed to regularize the level set function. It can not only ensure the smoothness of the level set function, but also eliminate the requirement of re-initialization, which is very computationally expensive. Experiments show that the proposed method achieves similar results to the LBF (local binary fitting) energy model but it is much more computationally efficient. In addition, our approach maintains the sub-pixel accuracy and boundary regularization properties.
URI: http://hdl.handle.net/10397/14686
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2009.10.010
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