Detecting Branching Structures Using Local Gaussian Models
Wang, L. and Bhalerao, A.H. (2001) Detecting Branching Structures Using Local Gaussian Models. Technical Report. University of Warwick, Coventry, UK.
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Abstract
This report presents a method of detecting branching structure, such as blood vessels from retinal images, using a Gaussian Intensity model. Features are modelled with a Gaussian function parameterised by position, orientation and variance within some spatial window. Multiple features are modelled using a superposition of Gaussian models. A non-parametric classifier (k-means) is used to cluster components corresponding to each feature. Two different groups of images are used to test the methodology: artificial images and images of the human retina.
| Item Type: | Monograph (Technical Report) |
|---|---|
| Uncontrolled Keywords: | pcav hpsg image signal processing branch detection |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Faculty of Science > Computer Science |
| Depositing User: | Simon Hammond |
| Date Deposited: | 19 Jun 2011 20:47 |
| Last Modified: | 23 Feb 2012 09:09 |
| URI: | http://eprints.dcs.warwick.ac.uk/id/eprint/742 |
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