Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106407
Title: Nonlinear retinal image enhancement for vessel detection
Authors: Wang, Xiaohong
Jiang, Xudong
Keywords: Retinal Vessel Detection
Retinal Image
Engineering::Electrical and electronic engineering
Issue Date: 2017
Source: Wang, X., & Jiang, X. (2017). Nonlinear retinal image enhancement for vessel detection. Proceedings of SPIE - Ninth International Conference on Digital Image Processing, 10420, 104202M-. doi:10.1117/12.2281566
Series/Report no.: Proceedings of SPIE - Ninth International Conference on Digital Image Processing
Abstract: Retinal vessel detection is an essential part of the computer-aided diagnosis of eye diseases. Due to non-perfect imaging environment, retinal images often appear with intensity variations and artificial noises. This work proposes a two-step nonlinear retinal image enhancement to compensate for those imperfections of retinal images. The first step reduces intensity fluctuations of the image and the second step attenuates impulsive noise while preserving retinal vessels. Classification on the feature vector extracted from the enhanced retinal images is performed by using a linear SVM classifier. Experimental results demonstrate that the proposed method of two-step nonlinear image enhancement visibly improves the vessel detection performance, achieving better accuracy than that without enhancement process on the both DRIVE and STARE databases.
URI: https://hdl.handle.net/10356/106407
http://hdl.handle.net/10220/49625
ISSN: 0277-786X
DOI: 10.1117/12.2281566
Rights: © 2017 SPIE. All rights reserved. This paper was published in Proceedings of SPIE - Ninth International Conference on Digital Image Processing and is made available with permission of SPIE.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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