Local Binary Signed Pressure Force Function Based Variation Segmentation Model
Volume 9 Issue 1 2015
Download| Author(s): | Tariq Ali, Lutful Mabood, Haider Ali, Noor Badshah |
|---|---|
| Abstract | Global and local image information is crucial for accurate segmentation of images with intensity inhomogeneity, valuable minute details and multiple objects with various intensities. However, local information is not embedded in popular region-based active contour models, such as the Sign Pressure force (Spf) function based active contour model by K. Zhang et al. In this paper, we propose a region-based active contour model which is able to utilize together image information in local regions and global information. The major contribution of this paper is the introduction of a new local signed pressure force function, which enables the extraction of accurate local and global image information. Therefore, our model can be used to segment images with intensity inhomogeneity, minute valuable details and multiple objects with several intensities. Comparison tests show the advantages of our method in terms of robustness. |
| Keywords | Image segmentation, Level set method, Signed pressure force function, Local binary fitting terms. |
| Year | 2015 |
| Volume | 9 |
| Issue | 1 |
| Type | Research paper, manuscript, article |
| Journal Name | Journal of Information & Communication Technology | Publisher Name | ILMA University | Jel Classification | - | DOI | - | ISSN no (E, Electronic) | 2075-7239 | ISSN no (P, Print) | 2415-0169 | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Manuscript Processing | Blind Peer Reviewed | Format | Paper Link | https://jict.ilmauniversity.edu.pk/journal/jict/9.1/1.pdf | Page | 1-12 |