Level Lines as Global Minimizers of Energy Functionals in Image Segmentation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Gradient Vector Flow Fast Geometric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparative study of image segmentation algorithms
SSIP'08 Proceedings of the 8th conference on Signal, Speech and image processing
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An energy model-based approach for estimating object boundaries is presented. We study a particular energy, which minimizer can be determined. The method estimates the unknown number of objects and draws object boundaries by selecting the "best" level lines computed from level sets of the original image. Unlike previous standard methods, the proposed method does not require iteration for minimizing the energy. In addition, our segmentation algorithm combines anisotropic diffusion-based regularization with level line selection to extract smooth object boundaries. Experimental results on 2D biomedical and meteorological images are reported.