DocumentCode
3154419
Title
Iris localization via intensity gradient and recognition through bit planes
Author
Basit, A. ; Javed, M.Y.
Author_Institution
Nat. Univ. of Sci. & Technol. (NUST), Rawalpindi
fYear
2007
fDate
28-29 Dec. 2007
Firstpage
23
Lastpage
28
Abstract
Iris recognition is very hot topic in both research and practical applications. In this paper, a robust algorithm is proposed for iris localization and a very simple method is employed for feature extraction. Iris localization is the key step in iris recognition systems because all subsequent steps depend highly on its accuracy. The proposed algorithm utilizes important property of gradient of intensity level in the grey scale images (after converting the images into greyscale if not). Then iris is normalized into a dimensionless rectangular strip of size 128*512 pixels and different features are extracted based upon bit plane slicing of the strip to get binary iris code. ROC curves are also drawn for different features. Matching decision is based on accumulative sum of bitwise XOR of different iris codes. Experiments show that proposed localization algorithm is very effective. Results have been tabulated by evaluating the developed algorithm with 1000 eye images and recognition accuracy has reached up to 99.6%.
Keywords
biometrics (access control); gradient methods; image colour analysis; image recognition; binary iris code; bit planes; dimensionless rectangular strip; eye images; feature extraction; grey scale images; intensity gradient; iris localization; iris recognition systems; Biometrics; Educational institutions; Feature extraction; Humans; Image converters; Image resolution; Image segmentation; Iris recognition; Pigmentation; Strips; Biometrics; iris localization; iris recognition; iris segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision, 2007. ICMV 2007. International Conference on
Conference_Location
Islamabad
Print_ISBN
978-1-4244-1624-0
Electronic_ISBN
978-1-4244-1625-7
Type
conf
DOI
10.1109/ICMV.2007.4469267
Filename
4469267
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