Unsupervised Method for Retinal Vessel Segmentation Based on Gabor Wavelet and Multiscale Line Detector

IEEE Access

Cheng-Kai Lu¹  Tong Boon Tang¹  Syed Ayaz Ali Shah²  Muhammad Amir Khan²  Aamir Shahzad² 

[1] Centre for Intelligent Signal and Imaging Research, Universiti Teknologi Petronas, Seri Iskandar, Malaysia;Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad, Pakistan;

关键词: Blood vessel segmentation;    color retinal images;    Gabor wavelet;    line detector;    image processing;    unsupervised method;   

DOI  :  10.1109/ACCESS.2019.2954314

来源: DOAJ

【 摘 要 】

Eye and systemic diseases are known to manifest themselves in retinal vasculature. Segmentation of retinal vessel is one of the important steps in retinal image analysis. A simple unsupervised method based on Gabor wavelet and Multiscale Line Detector is proposed for retinal vessel segmentation. Vessels are enhanced by linear superposition of first scale Gabor wavelet image and complemented Green channel. Multiscale Line Detector is used to segment the blood vessels. Finally, a simple post processing scheme based on median filtering is deployed to remove false positives. The proposed scheme was evaluated with publicly available datasets called DRIVE, STARE and HRF, obtaining an accuracy of 0.9470, 0.9472, and 0.9559, and a sensitivity of 0.7421, 0.8004, and 0.7207, respectively. These results are comparable to the state-of-the-art methods, albeit with a simpler approach.

【 授权许可】

Unknown