Title
Personal Identification Based on Blood Vessels of Retinal Fundus Images
Abstract
Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9x 10(-5) % and 4.3 X 10(-5)%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.
Year
DOI
Venue
2008
10.1117/12.769330
PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Keywords
Field
DocType
retinal fundus image,identification,biometrics,blood vessel extraction,similarity
Computer vision,Similarity measure,False rejection rate,Reference image,Fundus (eye),Acceptance rate,Pixel,Artificial intelligence,Retinal,Biometrics,Mathematics
Conference
Volume
ISSN
Citations 
6914
0277-786X
5
PageRank 
References 
Authors
0.48
3
6
Name
Order
Citations
PageRank
Keisuke Fukuta150.48
Toshiaki Nakagawa2777.38
Yoshinori Hayashi3405.10
Y Hatanaka427624.77
Takeshi Hara563979.10
Hiroshi Fujita650.48