Iris recognition based on score level fusion by using SVM

Park, Hyun-Ae; Park, Kang Ryoung

doi:10.1016/j.patrec.2007.05.017

Cited by 80 publications

(59 citation statements)

References 17 publications

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“…Figure 5 shows examples of the detected iris, eyelid and eyelash regions. Finally, iris codes are extracted from the segmented region using a 1-D Gabor filter [23]. Next, the matching score for iris recognition is calculated based on the Hamming distance (HD) between enrolled iris codes and the input ones.…”

Section: Iris Recognition Methodsmentioning

confidence: 99%

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Multimodal Biometric System Based on the Recognition of Face and Both Irises

Kim

Shin

Lee

et al. 2012

International Journal of Advanced Robotic Systems

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The performance of unimodal biometric systems (based on a single modality such as face or fingerprint) has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition.Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

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Section: Iris Recognition Methodsmentioning

confidence: 99%

“…The false rejection rate (FRR) is the error rate of rejecting a genuine person as an imposter. The EER is the error rate when the FAR is almost same as the FRR, which has been widely used to represent the accuracy of conventional biometric systems [1,7,23].…”

Section: Combining the Three Scores For The Recognition Of The Face Amentioning

confidence: 99%

Multimodal Biometric System Based on the Recognition of Face and Both Irises

Kim

Shin

Lee

et al. 2012

International Journal of Advanced Robotic Systems

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“…Here the target performance was directly optimized with respect to fusion classifier design. Park and Park [18] implemented Score level fusion for iris recognition achieved by using HD (Hamming distance) produced by a Gabor filter. Kittler et al [19] have developed a theoretical framework for consolidating the evidence obtained from multiple classifiers using schemes like the sum rule, product rule, max rule, min rule, median rule and majority voting.…”

Section: Literature Reviewmentioning

confidence: 99%

Score Level Fusion of Multimodal Biometrics based on Entropy Function

Haque¹,

Uddin²,

Grover³

2016

IJCA

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This paper presents the score level fusion of multimodal biometrics using Hanman-Anirban entropy function. Entropy function captures the uncertainty in the scores. The experimental results ascertain that Entropy based score level fusion outperforms over existing methods of score level fusion such as t-norms, sum and max. We have validated our claim on finger-knuckle-print (FKP) dataset consisting of left index, left middle, right index and right middle FKP. The features of FKPs are extracted using the Gabor Wavelet. The implementation is done using MATLAB and the performance of the proposed technique is evaluated using Receiver Operating characteristics (ROC) curve. The proposed score level fusion approach achieves significant improvement in the performance over the individual FKP. We obtain Genuine acceptance rate of 99% with FAR of 0.001 %.

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“…Next, the proposed algorithm used a conventional Gabor filter-based method [1,[17][18][19]29] and generated iris binary codes of 512 bytes (256 iris codes + 256 valid mask codes) per user. The valid mask codes represented whether or not the corresponding iris code was valid.…”

Section: Extracting Iris Codes and Recognitionmentioning

confidence: 99%

A novel portable iris recognition system and usability evaluation

Jang

Kang

Park

2010

Int. J. Control Autom. Syst.

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We propose a new portable iris recognition system. Because existing portable iris systems use customized embedded processing units, they are limited in ability to expand to other applications, and they have low processing power. To overcome such problems, we propose a new portable iris recognition system consisting of a conventional ultra-mobile personal computer (UMPC), a small universal serial bus (USB) iris camera, and near-infrared (NIR) light illuminators. In general, portable iris systems produce considerable optical blurring. Although auto-focusing motor-driven lenses can be used to overcome it, they are too bulky to be used in a small-sized portable iris system. Therefore, we adopt an iris image restoration algorithm which performs at real-time speed. And by using a conventional UMPC as a processing unit, our portable iris system is more extensible than previous systems. In general, the performance of iris recognition has been mainly evaluated based on the quantitative metrics such as EER (Equal Error Rate), ROC (Receiver Operational Characteristics) curve or recognition time. We propose a new performance measuring method based on qualitative metrics. That is usability evaluation including user acceptance, convenience, satisfaction and resistance.

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Iris recognition based on score level fusion by using SVM

Cited by 80 publications

References 17 publications

Multimodal Biometric System Based on the Recognition of Face and Both Irises

Multimodal Biometric System Based on the Recognition of Face and Both Irises

Score Level Fusion of Multimodal Biometrics based on Entropy Function

A novel portable iris recognition system and usability evaluation

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