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Figure 2 – uploaded by Seddik Djouadi

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Figure 2. Coupling between curve evolution may enlarge initialization problems. (a) Mul- tiphase Chan-Vese model. (b) Initialization. (c) Intermediate results after 12 iterations. (d) Segmentation results. (e)-(h) show the posi- tions of four parts of the evolving curves in (d).

Figure 2 Coupling between curve evolution may enlarge initialization problems. (a) Mul- tiphase Chan-Vese model. (b) Initialization. (c) Intermediate results after 12 iterations. (d) Segmentation results. (e)-(h) show the posi- tions of four parts of the evolving curves in (d).

Related Figures (3)

Figure 3. Comparison of the improved model with the previous model. (a) Original image (100 * 100). (61) Segmentation using the pre- vious model, 1 = 5000, CPU = 0.27s. (b2) Segmentation using the improved model, v = 5000, CPU = 0.33s. (c1) Segmentation using the previous model, v = 12000, CPU = 0.26s. (c2) Segmentation using the improved model, y = 12000, CPU = 0.27s. (d) Original image (300 * 300). (e1) Segmentation of (d) using the previous model, 1 = 18000, CPU = 2.69s. (e2) Segmentation of (d) using the improved model, v = 18000, CPU = 3.52s.
Figure 3. Comparison of the improved model with the previous model. (a) Original image (100 * 100). (61) Segmentation using the pre- vious model, 1 = 5000, CPU = 0.27s. (b2) Segmentation using the improved model, v = 5000, CPU = 0.33s. (c1) Segmentation using the previous model, v = 12000, CPU = 0.26s. (c2) Segmentation using the improved model, y = 12000, CPU = 0.27s. (d) Original image (300 * 300). (e1) Segmentation of (d) using the previous model, 1 = 18000, CPU = 2.69s. (e2) Segmentation of (d) using the improved model, v = 18000, CPU = 3.52s.
be focused on the dynamic selection of the parameter v and the parallel implementation of the proposed method. Figure 4. Experimental results for real im- ages. (a1)-(g1) are original images. The sizes are: (a1) (128 * 128), (b1) (255 * 266), (c1) (200 * 150), (d1) (300 * 225), (e1) (200 * 150), (f1) (200 * 150), (gi) (698 * 581). Other images are segmentation results for (a1)-(d1). Corre- sponding parameters are: (a2) v = 1200, CPU = 0.82s. (b2) v = 7000, CPU = 4.61s. (c2) v = 2500, CPU = 2.23s. (d2) v = 10000, CPU = 2.64s. (e2) v = 600, CPU = 1.82s.(e3) v = 700, CPU = 1.96s. (f2) » = 600, CPU = 0.93s.(f3) v = 1500, CPU = 0.91s. (g2) v = 3000, CPU = 27.16s.
be focused on the dynamic selection of the parameter v and the parallel implementation of the proposed method. Figure 4. Experimental results for real im- ages. (a1)-(g1) are original images. The sizes are: (a1) (128 * 128), (b1) (255 * 266), (c1) (200 * 150), (d1) (300 * 225), (e1) (200 * 150), (f1) (200 * 150), (gi) (698 * 581). Other images are segmentation results for (a1)-(d1). Corre- sponding parameters are: (a2) v = 1200, CPU = 0.82s. (b2) v = 7000, CPU = 4.61s. (c2) v = 2500, CPU = 2.23s. (d2) v = 10000, CPU = 2.64s. (e2) v = 600, CPU = 1.82s.(e3) v = 700, CPU = 1.96s. (f2) » = 600, CPU = 0.93s.(f3) v = 1500, CPU = 0.91s. (g2) v = 3000, CPU = 27.16s.
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Curve Evolution
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