Retina Recognition System Using Wavelet based Neural Network Algorithm
Palavras-chave:
Retina Recognition, Wavelet based Feature Extraction, Retinal Vessel Segmentation, Back-Propagation Neural Network, Local Minima ProblemResumo
This paper presents an approach of wavelet feature-based retina recognition system using back-propagation learning neural network algorithm. After acquiring the retinal image, at first vessels were segmented from the image. Then the feature extraction was carried out by analyzing the segmented retinal image using multiresolution analysis through the wavelet-based approach. Then extracted features were fed to the back-propagation learning neural network algorithm to create the learned template which was used for mapping with the unknown retina image. Digital Retinal Images for Vessel Extraction (DRIVE) retinal dataset has been used to measure the performance of the proposed system. Keywords: retina recognition, wavelet-based feature extraction, retinal vessel segmentation, back-propagation neural network, local minima problem Cite this Article Islam R. Retina Recognition System Using Wavelet Based Neural Network Algorithm. Current Trends in Signal Processing. 2015; 5(2): 35–39p.
Downloads
Publicado
Edição
Secção
Licença
Declaration and Copyright Transfer Form
(to be completed by authors)
I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.
· I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
· I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
· I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
· I/We also agree to the authorship of the article in the following order:
Author’s name
1. ________________
2. ________________
3. ________________
_______________
We Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal. |
