Curvelet Transform and Multi Structure Elements Morphology by Reconstruction based Retinal Image Analysis
Kamala Devi1. K, Agnes Anto2, K.John Peter3
1Kamala Devi.K,CSE, Vins Christian college of Engineering,Nagercoil,India
2Agnes Anto,CSE, Vins Christian college of Engineering, Nagercoil,India
3John Peter.K ,IT, Vins Christian college of Engineering Nagercoil,India
Manuscript received on April 04, 2013. | Revised Manuscript received on April 28, 2013. | Manuscript published on May 05, 2013. | PP: 548-553| Volume-3, Issue-2, May 2013. | Retrieval Number: C0711052312 /2012©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Curvelet transform is a multi scale transform that can represent the edges along curves much more efficiently.Retinal images play important roles in finding of some diseases in early stages, such as diabetes, which can be performed by comparison of the states of retinal blood vessels. Automated image processing has the potential to support in the early detection of diabetes, by detecting changes in blood vessel diameter and patterns in the retina. Proposed paper describes the development of segmentation methodology in the processing of retinal blood vessel images obtained using non-mydriatic color photography. Highly accurate identification of blood vessels for the purpose of studying changes in the vessel network that can be utilized for detecting blood vessel diameter changes associated with the path physiology of diabetes. There is a deficiency of missing some thin vessels is because of utilizing a simple thresholding method. My contribution is to implement a technique that will also be applicable for small length blood vessels.
Keywords: Blood vessel segmentation,curvelet transform,multistructure elements morphology, morphological operators by reconstruction,retinal image.