Title :
An automated vessel segmentation algorithm in retinal images using 2D Gabor wavelet
Author :
Nazari, Peyman ; Pourghassem, H.
Author_Institution :
Dept. of Electr. Eng., Islamic Azad Univ., Isfahan, Iran
Abstract :
This paper proposes a novel method to extract blood vessels in retinal images. We also present a new effective preprocessing to reduce the effect of non-uniformly illumination using red and green channels of these images. The vessels finally have been extracted using 2D Gabor filter bank followed by thresholding on grayscale and thresholding based on structural properties of labeled vessel candidates, to extract large and thin vessels. The proposed algorithm is evaluated on DRIVE database, which is publically available. The results show that presented algorithm achieved accuracy rate of 94.81% along with True Positive Fraction (TPF) of 71.12% and False Positive Fraction (FPF) of 2.84%.
Keywords :
Gabor filters; blood vessels; channel bank filters; eye; feature extraction; filtering theory; image colour analysis; image segmentation; medical image processing; wavelet transforms; 2D Gabor filter bank; 2D Gabor wavelet; DRIVE database; automated vessel segmentation algorithm; blood vessel extraction; false positive fraction; grayscale thresholding; green channels; labeled vessel candidates; nonuniformly illumination effect reduction; red channels; retinal images; structural properties; true positive fraction; Biomedical imaging; Blood vessels; Databases; Gabor filters; Image segmentation; Lighting; Retina; 2D Gabor wavelet; blood vessel; optical disc; retinal image; thresholding;
Conference_Titel :
Machine Vision and Image Processing (MVIP), 2013 8th Iranian Conference on
Conference_Location :
Zanjan
Print_ISBN :
978-1-4673-6182-8
DOI :
10.1109/IranianMVIP.2013.6779967