Geometric Corner Extraction in Retinal Fundus Images

Geometric Corner Extraction in Retinal Fundus Images
Title:
Geometric Corner Extraction in Retinal Fundus Images
Other Titles:
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Keywords:
Publication Date:
26 August 2014
Citation:
Lee, J.A.; Beng Hai Lee; Guozhen Xu; Ee Ping Ong; Wong, D.W.K.; Jiang Liu; Tock Han Lim, "Geometric corner extraction in retinal fundus images," Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE , vol., no., pp.158,161, 26-30 Aug. 2014 doi: 10.1109/EMBC.2014.6943553
Abstract:
This paper presents a novel approach of finding corner features between retinal fundus images. Such images are relatively textureless and comprising uneven shades which render state-of-the-art approaches e.g., SIFT to be ineffective. Many of the detected features have low repeatability (<; 10%), especially when the viewing angle difference in the corresponding images is large. Our approach is based on the finding of blood vessels using a robust line fitting algorithm, and locating corner features based on the bends and intersections between the blood vessels. These corner features have proven to be superior to the state-of-the-art feature extraction methods (i.e. SIFT, SURF, Harris, Good Features To Track (GFTT) and FAST) with regard to repeatability and stability in our experiment. Overall in average, the approach has close to 10% more repeatable detected features than the second best in two corresponding retinal images in the experiment.
License type:
PublisherCopyrights
Funding Info:
Description:
ISSN:
1557-170X
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