Name
Abstract | ||
|---|---|---|
The algorithm proposed in this paper allows to segment the optic disc from a fundus image. The goal is to facilitate the early detection of certain pathologies and to fully automate the process so as to avoid specialist intervention. The method used for the extraction of the optic disc contour is based on a variant of the watershed transformation, the stochastic watershed. A principal component analysis (PCA) and a previous pre-processing, focused on mathematical morphology, are performed in order to prepare the image for segmentation. The purpose of using PCA is to obtain the grey-scale image that better represents the original RGB image. The implemented algorithm has been validated on a public database obtaining promising results. |
Year | Venue | Keywords |
|---|---|---|
2012 | Signal Processing Conference | edge detection,eye,feature extraction,image colour analysis,image segmentation,mathematical morphology,medical image processing,object detection,principal component analysis,PCA,RGB image,automatic optic disc detection,fundus image,grey-scale image,mathematical morphology,optic disc contour extraction,pathology early detection,principal component analysis,stochastic watershed,watershed transformation,Optic disc,optic nerve head,principal component analysis,stochastic watershed |
Field | DocType | ISSN |
Object detection,Computer vision,Pattern recognition,Computer science,Segmentation,Mathematical morphology,Edge detection,Optic disc,Feature extraction,Image segmentation,Artificial intelligence,Principal component analysis | Conference | 2219-5491 |
ISBN | Citations | PageRank |
978-1-4673-1068-0 | 3 | 0.41 |
References | Authors | |
12 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandra Morales | 1 | 16 | 4.16 |
| Naranjo, V. | 2 | 6 | 1.83 |
| Perez, D. | 3 | 3 | 0.41 |
| Navea, A. | 4 | 3 | 0.41 |
| Alcaniz | 5 | 3 | 0.75 |