Name
Title | ||
|---|---|---|
A Selective Segmentation Model Using Dual-Level Set Functions and Local Spatial Distance |
Abstract | ||
|---|---|---|
Selective image segmentation is one of the most significant subjects in medical imaging and real-world applications. We present a robust selective segmentation model based on local spatial distance utilizing a dual-level set variational formulation in this study. Our concept tries to partition all objects using a global level set function and the selected item using a different level set function (local). Our model combines the marker distance function, edge detection, local spatial distance, and active contour without edges into one. The new model is robust to noise and gives better performance for images having intensity in-homogeneity (background and foreground). Moreover, we observed that the proposed model captures objects which do not have uniform features. The experimental results show that our model is robust to noise and works better than the other existing models. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ACCESS.2022.3152785 | IEEE ACCESS |
Keywords | DocType | Volume |
Image segmentation, Mathematical models, Image edge detection, Computational modeling, Level set, Active contours, Motion segmentation, Euler-Lagrange equation, selective segmentation, level set function, local spatial distance, local similarity factor | Journal | 10 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 11 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Afzal Rahman | 1 | 0 | 0.34 |
| Haider Ali | 2 | 84 | 15.04 |
| Noor Badshah | 3 | 0 | 0.34 |
| Lavdie Rada | 4 | 0 | 0.34 |
| Ayaz Ali Khan | 5 | 0 | 0.34 |
| Hameed Hussain | 6 | 0 | 0.34 |
| Muhammad Zakarya | 7 | 0 | 0.68 |
| Aftab Ahmed | 8 | 0 | 0.68 |
| Izaz Ur Rahman | 9 | 0 | 0.68 |
| Mushtaq Raza | 10 | 0 | 1.01 |
| Muhammad Haleem | 11 | 0 | 0.68 |