DocumentCode :
3246549
Title :
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
Link To Document :
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