Active contours driven by local image fitting energy. (English) Zbl 1192.68624

Zhang, Kaihua; Song, Huihui; Zhang, Lei

Pattern Recognition 43, No. 4, 1199-1206 (2010).

Summary: 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.

MSC:

68T10	Pattern recognition, speech recognition
68U10	Computing methodologies for image processing

Keywords:

image segmentation; Chan-Vese (C-V) model; active contour models; LBF model

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