Fast normalized cross-correlation based retinal recognition

Author

Rubaiyat, Abu Hasnat Mohammad ; Aich, Shubhra ; Toma, Tanjin Taher ; Mallik, Abidur Rahman ; Rafat-Al-Islam

Author_Institution

Samsung R&D Inst. Bangladesh (SRBD), Dhaka, Bangladesh

fYear

2014

Firstpage

358

Lastpage

361

Abstract

In this paper, a simple biometric scheme based on RGB retinal fundus images is proposed. First, prominent vasculature energy based feature vectors are constructed from RGB retinal fundus images to utilize the unique pattern of retinal vasculature. Next, fast normalized cross-correlation based feature matching is employed for person identification on publicly available DRIVE and STARE databases. This method excels recently published literatures with perfect recognition accuracy of 100% on STARE and accuracy of 99.77% on DRIVE databases. Its smaller dimension of feature vector and better recognition result make this method eligible for real-time person identification scheme.

Keywords

feature extraction; image matching; retinal recognition; RGB retinal fundus images; biometric scheme; fast-normalized cross-correlation based feature matching; fast-normalized cross-correlation based retinal recognition; publicly available DRIVE database; publicly available STARE database; real-time person identification scheme; retinal vasculature pattern; vasculature energy based feature vectors; Accuracy; Biomedical imaging; Databases; Feature extraction; Retina; Vectors; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (ICCIT), 2014 17th International Conference on

Type

conf

DOI

10.1109/ICCITechn.2014.7073086

Filename

7073086