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Retina Vessel Detection Using Fuzzy Ant Colony Algorithm
- Source :
- CRV
- Publication Year :
- 2010
- Publisher :
- IEEE, 2010.
-
Abstract
- Vessel extraction in retina images is a primary and important step in studying diseases including vasculature changes. In this paper, a fuzzy clustering method based on Ant Colony Algorithm, inspired by food-searching natural behavior of ants, is described. Features of color retina images are extracted by eigenvalues analysis of Hessian matrix and Gabor filter bank. Artificial ants in the image use these features for searching and clustering processes. Experiments and results of proposed algorithm show its good performance in vessel extraction. This algorithm is tested on DRIVE database and its results are compared with other works using the same database. The accuracy of our method is 0.933 versus 0.947 for a second observer.
- Subjects :
- Hessian matrix
Fuzzy clustering
Pixel
business.industry
Ant colony optimization algorithms
Feature extraction
MathematicsofComputing_NUMERICALANALYSIS
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
Filter bank
Fuzzy logic
symbols.namesake
symbols
Computer vision
Artificial intelligence
business
Cluster analysis
Mathematics
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2010 Canadian Conference on Computer and Robot Vision
- Accession number :
- edsair.doi...........80a89342766827af130bc612670086f9
- Full Text :
- https://doi.org/10.1109/crv.2010.38