Wang, Li and Bhalerao, Abhir (2002) Detecting branching structures using local Gaussian models. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)

Preview

PDF WRAP_cs-rr-385.pdf - Other - Requires a PDF viewer. Download (433Kb) | Preview

Request Changes to record.

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:	Report
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH):	Image processing -- Digital techniques, Diagnostic imaging, Blood-vessels
Series Name:	Department of Computer Science research report
Publisher:	University of Warwick. Department of Computer Science
Official Date:	26 November 2002
Dates:	Date Event 26 November 2002 Published
Number:	Number 385
Number of Pages:	23
DOI:	CS-RR-385
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Status:	Peer Reviewed
Publication Status:	Unpublished
Funder:	Engineering and Physical Sciences Research Council (EPSRC)
Grant number:	GR/M82899 (EPSRC)
Related URLs:	Organisation

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads