A Robust Local Model for Segmentation Based on Coefficient of Variation
Volume 5 Issue 1 2011
Download| Author(s): | Ocenasek Pavel, Hranac Jakub |
|---|---|
| Abstract | Many image segmentation models work efficiently when segmenting images with prominent edges and regions but often we need to segment images with low contrast, unilluminated objects, inhomogeneity problems and images with overlapping region of almost homogeneous intensities. In fact these mentioned images pose challenges to the existing models. In this paper, we proposed a new variational model for image segmentation, based on a robust local statistical information. In contrast with the existing models, the experimental results validate that the new proposed model is robust in terms of accurate detection in such tough images. |
| Keywords | Segmentation, Level Set, Functional Minimization, Coefficient of Variation (CoV ), Total Variation. |
| Year | 2011 |
| Volume | 5 |
| 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/5.1/4.pdf | Page | 30-39 |