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Iris Feature Extraction for Personal Identification using Fast Wavelet Transform (FWT)

Abikoye Oluwakemi C. , Sadiku, J. S., Adewole Kayode S., , Jimoh Rasheed G. Published in Security

International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
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  1. Abikoye Oluwakemi C., Sadiku, J S., Adewole Kayode S. and Jimoh Rasheed G.. Article: Iris Feature Extraction for Personal Identification using Fast Wavelet Transform (FWT). International Journal of Applied Information Systems 6(9):1-6, March 2014. BibTeX

    	author = "Abikoye Oluwakemi C. and Sadiku and J. S. and Adewole Kayode S. and and Jimoh Rasheed G.",
    	title = "Article: Iris Feature Extraction for Personal Identification using Fast Wavelet Transform (FWT)",
    	journal = "International Journal of Applied Information Systems",
    	year = 2014,
    	volume = 6,
    	number = 9,
    	pages = "1-6",
    	month = "March",
    	note = "Published by Foundation of Computer Science, New York, USA"


Iris is the annular region of the eye bounded by the pupil and the sclera(white of the eye) on either side. The iris has many interlacing features such as stripes, freckles, coronas, radial furrow, crypts, zigzag collarette, rings etc collectively referred to as texture of the iris. This texture is well known to provide a signature that is unique to each subject. All these features are extracted using different algorithms i. e features extraction is the process of extracting information from the iris image. Iris feature extraction is the crucial stage of the whole iris recognition process for personal identification. This is a key process where the two dimensional image is converted to a set of mathematical parameters. The significant features of the iris must be encoded so that comparisons between templates can be made. In this study the feature of the iris is extracted using Fast Wavelet Transform (FWT). The algorithm is fast and has a low complexity rate. The system encodes the features to generate its iris feature codes.


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Iris identification, Feature extraction, Algorithm, FWT.