An Improved Level Set Method to Image Segmentation Based on Saliency

Yan Wang and Xianfa Xu
Volume: 15, No: 1, Page: 7 ~ 21, Year: 2019
Keywords: Canny Operator, Edge Energy, Level Set Method, Local Renyi Entropy, Saliency Map
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In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

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Cite this article
IEEE Style
Y. W. X. Xu, "An Improved Level Set Method to Image Segmentation Based on Saliency," Journal of Information Processing Systems, vol. 15, no. 1, pp. 7~21, 2019. DOI: 10.3745/JIPS.02.0105.

ACM Style
Yan Wang and Xianfa Xu. 2019. An Improved Level Set Method to Image Segmentation Based on Saliency, Journal of Information Processing Systems, 15, 1, (2019), 7~21. DOI: 10.3745/JIPS.02.0105.