Name
Abstract | ||
|---|---|---|
Digital fundus photographs are often used to provide clinical diagnostic information about several pathologies such as diabetes, glaucoma, macular degeneration and vascular and neurologic disorders. To allow a precise analysis, digital fundus image quality should be assessed to evaluate if minimum requirements are present. Focus is one of the causes of low image quality. This paper describes a method that automatically classifies fundus images as focused or defocused. Various focus measures described in literature were tested and included in a feature vector for the classification step. A neural network classifier was used. HEI-MED and MESSIDOR image sets were utilized in the training and testing phase, respectively. All images were correctly classified by the proposed algorithm. |
Year | Venue | Keywords |
|---|---|---|
2014 | 2014 International Conference on Computer Vision Theory and Applications (VISAPP) | Digital Fundus Photography,Focus Measures,Image Processing |
Field | DocType | Volume |
Kernel (linear algebra),Computer vision,Feature vector,Pattern recognition,Computer science,Image processing,Image quality,Fundus (eye),Robustness (computer science),Artificial intelligence,Artificial neural network,Wavelet transform | Conference | 1 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diana Veiga | 1 | 15 | 5.75 |
| Carla Pereira | 2 | 40 | 3.74 |
| Manuel Ferreira | 3 | 63 | 7.20 |
| Luís Gonçalves | 4 | 45 | 6.19 |
| João Monteiro | 5 | 99 | 20.30 |