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Iris Recognition using Secant Lines Segments Histogram
http://hdl.handle.net/20.500.12678/0000004434
http://hdl.handle.net/20.500.12678/0000004434ef59c69a-873b-4f76-b2d7-46d313c04dd8
9d8d5560-c38e-4269-b2ac-48b285cabb57
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Iris Recognition using Secant Lines Segments Histogram.pdf (655 Kb)
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Article | ||||||
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Publication | ||||||
Title | ||||||
Title | Iris Recognition using Secant Lines Segments Histogram | |||||
Language | en_US | |||||
Publication date | 2016-02-25 | |||||
Authors | ||||||
Win, Ei Phyu | ||||||
Aye, Nyein | ||||||
Description | ||||||
Biometrics is a method for recognizing basedon physiological and behavioral characteristics. Irisrecognition is one of the robust biometrictechnologies used for authentication applications. Aniris recognition system is composed of segmentation,normalization, feature extraction and matching. Theperformance of iris recognition system depends onthe selection of iris features. Most commercial irisrecognition systems used patented algorithmsdeveloped by Daugman’s Gabor filter for featureextraction. These methods have large computation.To overcome this problem, a new effective method,Secant Lines Segments Histogram, is proposed forextracting features of iris. In this paper, HoughTransform is applied for localizing the iris region.The segmented iris is normalized using Daugman’sRubber Sheet Model. For extracting iris features,Secant Lines Segments Histogram is used. The twoiris feature vectors are matched using EuclideanDistance. The proposed iris recognition systemreduces the computation and time load for extractingfeatures of the iris. | ||||||
Keywords | ||||||
Daugman’s Gabor Filter, Secant Lines Segments Histogram | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/2367 | |||||
Journal articles | ||||||
Fourteenth International Conference On Computer Applications (ICCA 2016) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |