A machine-vision system for iris recognition

Wildes, Richard P.; Asmuth, Jane C.; Green, Gilbert L.; Hsu, Sheng Teng; Kolczynski, R.J.; Matey, James R.; McBride, S. E.

doi:10.1007/bf01246633

Cited by 336 publications

(135 citation statements)

References 7 publications

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“…Various research groups such as [14][15][16][17][18][19][20][21][22][23][24][25][26], have proposed an iris recognition system based on iris normalization. The iris normalization step has become so popular in the research groups that it is being called Daugman's 'Rubber Sheet Model' after renowned researcher J.…”

Section: Related Workmentioning

confidence: 99%

Iris Recognition Using Ridgelets

Birgale¹,

Kokare²

2012

Journal of Information Processing Systems

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Abstract-Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.

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Section: Related Workmentioning

confidence: 99%

Iris Recognition Using Ridgelets

Birgale¹,

Kokare²

2012

Journal of Information Processing Systems

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“…al, 1998), Haar wavelet (Lim et. al, 2001) and Laplacian of Gaussian filters (Widles, 1996). In the proposed system, Masek's algorithm was used for feature encoding by convolving the normalized iris pattern with 1D Log-Gabor wavelets.…”

Section: Feature Extraction / Encodingmentioning

confidence: 99%

Iris recognition system by using support vector machines

Ali

Salami

Wahyudi

2008

2008 International Conference on Computer and Communication Engineering

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“…In 1987, Flom and Safir initially suggested the idea of automated iris recognition. Since then, several researchers have worked on iris representation and matching and have attained huge progress [6]. Boles and Boashash [7] worked out a zero-crossing representation of one-dimensional (1D) wavelet transform at different resolution levels of a concentric circle on an iris image to distinguish the consistency of the iris.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Isocentric Segmentor and Wavelet Rectangular Coder to Iris Segmentation and Recognition

Chirchi¹,

Waghmare²

2017

IJIES

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Abstract:In this paper, we propose a novel method for iris recognition system using enhanced isocentric segmentor (EISOS) and wavelet rectangular coder (WRC). At first, we locate the center of the eye within the area of the pupil on low resolution images using EISOS method. Once the iris region is successfully segmented, the next stage is to transform the iris region into the fixed dimensions. Then, we propose a novel feature vector generation method namely, wavelet rectangular coder (WRC). Finally, we recognize the iris image using fuzzy logic classifier to identify whether the iris image is present in the dataset or not. The iris recognition performance is measured using different dataset such as, CASIA, MMU and UBIRIS dataset. Experimental results indicate that the proposed method of EISOS+WRC based iris segmentation and recognition framework have outperformed by having better accuracy of 99.75% which is 94% and 93% for using existing approaches.

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A machine-vision system for iris recognition

Cited by 336 publications

References 7 publications

Iris Recognition Using Ridgelets

Iris Recognition Using Ridgelets

Iris recognition system by using support vector machines

Enhanced Isocentric Segmentor and Wavelet Rectangular Coder to Iris Segmentation and Recognition

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