Gengsheng Li, Guojun Liu, Wentao Ma. Adaptive Image Segmentation Based on Region Information Coupling[J]. Laser & Optoelectronics Progress, 2022, 59(2): 0210013

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- Laser & Optoelectronics Progress
- Vol. 59, Issue 2, 0210013 (2022)

Fig. 1. Original image and preprocessed image. (a) Original image; (b) prepropcessed image

Fig. 2. Change curve of the weight function. (a) Weight function curve; (b) influence of parameter p on the weight function; (c) influence of parameter k on the weight function

Fig. 3. Segmentation results of our model. (a) Blood vessel image; (b) synthetic image

Fig. 4. Segmentation results of different initial contours. (a) Initial contour; (b) segmentation result of 10 iterations; (c) segmentation result of 20 iterations

Fig. 5. Segmentation result of our model on the synthetic image. (a) Image 1; (b) image 2; (c) image 3

Fig. 6. Segmentation results of blood vessel images with different Gaussian noise. (a) Noisy image; (b) segmentation result
![Segmentation results of different models. (a) Initial contour; (b) LBF model; (c) model in Ref. [21]; (d) our model](/Images/icon/loading.gif)
Fig. 7. Segmentation results of different models. (a) Initial contour; (b) LBF model; (c) model in Ref. [21]; (d) our model

Fig. 8. Segmentation results of natural images. (a) Original image; (b) segmentation result
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Table 1. JS and DSC values of different images
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Table 2. Evaluation of segmentation results of natural images
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Table 3. Number of iterations and time of our model

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