Human recognition based on retinal images and using new similarity function

Abstract

This paper presents a new human recognition method based on features extracted from retinal images. The proposed method is composed of some steps including feature extraction, phase correlation technique, and feature matching for recognition. In the proposed method, Harris corner detector is used for feature extraction. Then, phase correlation technique is applied to estimate the rotation angle of head or eye movement in front of a retina fundus camera. Finally, a new similarity function is used to compute the similarity between features of different retina images. Experimental results on a database, including 480 retinal images obtained from 40 subjects of DRIVE dataset and 40 subjects from STARE dataset, demonstrated an average true recognition accuracy rate equal to 100% for the proposed method. The success rate and number of images used in the proposed method show the effectiveness of the proposed method in comparison to the counterpart methods.

Optic disc detection in high-resolution retinal fundus images by region growing

“…The resolutions of retinal fundus images are 2048*1336 and 3888*2592 pixels. They were captured by Topcon 50DX funduc camera (TRC-50IA, Japan) in Shahid Labbafi Nedjad imaging center of Iran [28][29][30][31]. Figure 3 illustrates that the proposed approach is accurate subjectively for four retinal fundus images.…”

Retinal Image Processing in Biometrics

“…Several research works rely on many different methods for automatic detection of the retinal vascular structure (vascular segmentation/Retinal vessel segmentation) in fundus camera images. Vascular segmentation allows the vessel detection, vascular branching points extraction and the measurement of parameters such as vessel diameter, bifurcation geometry and vascular tortuosity [17,18,19,20] (see figure 12).…”

Propose retina identification system based on the combination of SURF detector and BRISK descriptor

“…Also retinal patterns have very particular features, these features that taken from retina can recognize persons efficiently, even between genetically identical twins. The pattern will remain invariant during the person's life, except when a dangerous disease occurs within the eye [1].…”