Segmentation of retinal blood vessels based on the second directional derivative and region growing

Autor:	M. E. Martinez-Perez, Kim H. Parker, Anil A. Bharath, Simon A. McG. Thom, Alun D. Hughes, Alice Stanton
Předmět:	business.industry Quantitative Biology::Tissues and Organs Pattern recognition Interval (mathematics) Image segmentation Directional derivative Intensity (physics) Region growing Computer vision Segmentation Artificial intelligence business Eigenvalues and eigenvectors Second derivative Mathematics
Zdroj:	Scopus-Elsevier ICIP (2)
Popis:	We present a method for the segmentation of blood vessels in retinal images based upon the second derivative of the intensity image which gives information about its topology and overcomes the problem of image intensity variations. The minimum eigenvalue and the magnitude of its gradient are used as features for a region growing procedure which is defined in two stages. For the first stage, growth is restricted to regions with low gradients, allowing vessels to grow where the values of the minimum eigenvalue lie within a wide interval and allowing rapid growth of background regions outside of the vessel boundaries. For the second stage, in which the borders between classes are defined, the algorithm grows vessel and background classes simultaneously without the gradient restriction.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecb064e6f3b734f2c1217f9174f692d3 http://www.scopus.com/inward/record.url?eid=2-s2.0-0033331528&partnerID=MN8TOARS Zobrazit plný text záznamu