Experimental Results

Database Description

To evaluate our work, proposed algorithm is applied to two databases composed of 40 color retinal images (565×584 pixels) from DRIVE database [35] and 20 chosen color retinal images (720× 576 pixels) from STARE database [36] which are both publicly available. We rotated and translated each subject randomly in different orientations and directions five times to obtain 200 images from DRIVE database and ten times to obtain 200 retinal images from STARE database. To implement our proposed algorithm, we used MATLAB software (version 7.14, R2012a) on a PC with CPU, Intel Core i3 and 2MB RAM, in six experiments as in the following.

Experiment A

The first 30 retinal images of DRIVE database were taken as enrolled images and the last 10 images with five images for each subject were considered as query images.

Experiment B

The last 30 retinal images of DRIVE database were enrolled and the first 10 images plus five images for each subject were considered as query images.

Experiment C

The first 15 images plus the last 15 images of DRIVE database were considered as enrolled images and 10 rested images of DRIVE database with 5 images for each subject were taken as query images.

Experiment D

All 40 images of DRIVE database were considered as enrolled images and 200 translated and rotated images were entered as query images. Obviously, in this experiment none of query images is rejected.

Experiment E

The first 15 selected images of STARE database were taken as enrolled images and 200 rotated and translated images were considered as query images.

Experiment F

The last 15 images of STARE database were considered as enrolled images and 200 rotated and translated images were considered as query images.

Parameter Setting

To select and set the optimal parameters in the hierarchical matching structure, we examine some experiments with an experiment similar to experiment A with different rotation and translation values. In these experiments, the issues such as the selection of utilized feature order in the candidate selection stage, the number of the most similar candidate SRs among database ( ) that are determined by the candidate selection stage, the optimal selection of thresholds in the SR matching stage and decision making scenario should be determined. In the following, the results of these experiments will be described.

Date: 2016-04-22; view: 662