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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 1/2015

01.01.2015 | Original Paper

A self-adaptive matched filter for retinal blood vessel detection

verfasst von: Tapabrata Chakraborti, Dhiraj K. Jha, Ananda S. Chowdhury, Xiaoyi Jiang

Erschienen in: Machine Vision and Applications | Ausgabe 1/2015

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Abstract

Retinal fundus images are widely studied in medicine for the detection of certain pathologies such as diabetes and glaucoma, the two major reasons for blindness. In this paper, a self-adaptive matched filter for the detection of blood vessels in the retinal fundus images is proposed. In particular, a novel synergistic combination of the vesselness filter with high sensitivity and the matched filter with high specificity is obtained using orientation histogram. Experiments on the publicly available DRIVE database clearly show that the proposed strategy outperforms several existing methods. Comparable performance with some of the state-of-the-art methods has also been obtained on the STARE and CHASE databases.
Vorheriger Artikel Tracking the articulated motion of the human body with two RGBD cameras
Nächster Artikel An image inpainting method using pLSA-based search space estimation

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Metadaten
Titel
A self-adaptive matched filter for retinal blood vessel detection
verfasst von
Tapabrata Chakraborti
Dhiraj K. Jha
Ananda S. Chowdhury
Xiaoyi Jiang
Publikationsdatum
01.01.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 1/2015
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-014-0636-z

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