Abstract
A fast two-stage geometric active contour algorithm for image segmentation is developed. First, the Eikonal equation problem is quickly solved using an improved fast swee** method, and a criterion of local minimum of area gradient (LMAG) is presented to extract the optimal arrival time. Then, the final time function is passed as an initial state to an area and length minimizing flow model, which adjusts the interface more accurately and prevents it from leaking. For object with complete and salient edge, using the first stage only is able to obtain an ideal result, and this results in a time complexity of O(M), where M is the number of points in each coordinate direction. Both stages are needed for convoluted shapes, but the computation cost can be drastically reduced. Efficiency of the algorithm is verified in segmentation experiments of real images with different feature.
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**ao, Cy., Zhang, S. & Chen, Yz. Fast image segmentation based on a two-stage geometrical active contour. J. of Shanghai Univ. 9, 40–45 (2005). https://doi.org/10.1007/s11741-005-0102-2
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DOI: https://doi.org/10.1007/s11741-005-0102-2