A box-counting fractal dimension for feature extraction in iris recognition

Author

Kraitong, Atilearn ; Huvanandana, Sanpachai ; Malisuwan, Sertapong

Author_Institution

Dept. of Comput. Educ., King Mongkut´´s Univ. of Technol. North, Bangkok, Thailand

fYear

2011

fDate

7-9 Dec. 2011

Firstpage

1

Lastpage

3

Abstract

Iris recognition is one of a popular Biometrics technique for identifying people. Normally, iris color and texture have been created since the first three months and they will be completed within one year. Iris will then remain unchanged until the end of one´s life. Both sides of the iris eyes are different. Moreover, the iris is unique and independent for genealogy even though in twins. Iris recognition has several sequence steps, pre-processing, features extractions, post-processing, and matching. In this paper, a box-counting fractal dimension and low-high pass filters have been used to extract iris features. This method can speed up a process by reducing a number of features. The experimental results show 91.22% matching accuracy with approximately 2.76 seconds for each matching.

Keywords

feature extraction; fractals; high-pass filters; image colour analysis; image matching; image texture; iris recognition; low-pass filters; biometrics technique; box-counting fractal dimension; feature extraction; iris color; iris recognition; iris texture; low-high pass filters; matching; people identification; postprocessing; preprocessing; Iris recognition; feature extraction; fractal dimension;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Signal Processing and Communications Systems (ISPACS), 2011 International Symposium on

Conference_Location

Chiang Mai

Print_ISBN

978-1-4577-2165-6

Type

conf

DOI

10.1109/ISPACS.2011.6146121

Filename

6146121