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Implicit Active Contours Driven by Local and Global Image Fitting Energy for Image Segmentation and Target Localization
We propose a novel active contour model in a variational level set formulation for image segmentation and target localization. We combine a local image fitting term and a global image fitting term to drive the contour evolution. Our model can efficiently segment the images with intensity inhomogenei...
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Published in: | Journal of sensors 2013-01, Vol.2013 (2013), p.1-8 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We propose a novel active contour model in a variational level set formulation for image segmentation and target localization. We combine a local image fitting term and a global image fitting term to drive the contour evolution. Our model can efficiently segment the images with intensity inhomogeneity with the contour starting anywhere in the image. In its numerical implementation, an efficient numerical schema is used to ensure sufficient numerical accuracy. We validated its effectiveness in numerous synthetic images and real images, and the promising experimental results show its advantages in terms of accuracy, efficiency, and robustness. |
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ISSN: | 1687-725X 1687-7268 |
DOI: | 10.1155/2013/713536 |