Pupil and Iris Localization for Iris Recognition in Mobile Phones

Cho, Dal-Ho; Park, Kang Ryoung; Rhee, Dae Woong; Kim, Yanggon; Yang, Jonghoon

doi:10.1109/snpd-sawn.2006.58

Cited by 41 publications

(10 citation statements)

References 5 publications

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“…We firstly obtained a low-resolution iris image through an iris camera without a zoom lens, which can decrease the cost and size of the iris recognition system. After increasing the size of the input low-resolution iris image with bilinear interpolation, we detected the iris and pupil region using two circular edge detectors [26] [27]. Next, the parameter of the degradation function was determined according to the zoom factor of the image in terms of recognition accuracy.…”

Section: Overview Of the Methodsmentioning

confidence: 99%

Super-Resolution Iris Image Restoration using Single Image for Iris Recognition

Shin¹,

Kang²,

Park³

2010

KSII TIIS

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Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

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Section: Overview Of the Methodsmentioning

confidence: 99%

Super-Resolution Iris Image Restoration using Single Image for Iris Recognition

Shin¹,

Kang²,

Park³

2010

KSII TIIS

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“…Many of these systems are all-inclusive systems which include image acquisition, processing, and database hardware in the same device. Examples include the HIDE system used by the Army from L1 systems [11], or systems run on cellular phones and PDA's [12]. • PC-Based Systems -These systems use a PC for their data processing, and typically use add-on or plug-in hardware for image acquisition.…”

Section: Review Of Existing Iris Recognition Systemsmentioning

confidence: 99%

Low-cost mobile video-based iris recognition for small databases

Thomas

Muttineni

et al. 2009

SPIE Proceedings

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This paper presents a low-cost method for providing biometric verification for applications that do not require large database sizes. Existing portable iris recognition systems are typically self-contained and expensive. For some applications, low cost is more important than extremely discerning matching ability. In these instances, the proposed system could be implemented at low cost, with adequate matching performance for verification.Additionally, the proposed system could be used in conjunction with any image based biometric identification system. A prototype system was developed and tested on a small database, with promising preliminary results.

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“…In Tao and Veldhuis (2006) and Ijiri et al (2006) people are authenticated by the recognition of their face through the camera of a mobile phone. In ho Cho et al (2006Cho et al ( ) andjeong et al (2005 authentication is provided by means of iris scanning and in Shabeer and Suganthi (2007) the characteristic biometric features are the voice and the fingerprint. Moreover, in Clarke and Furnell (2007) users are recognized by keystroke analysis.…”

Section: Introductionmentioning

confidence: 99%

Score optimization and template updating in a biometric technique for authentication in mobiles based on gestures

Guerra-Casanova

Ávila

Sierra

et al. 2011

Journal of Systems and Software

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Keywords:Mobile authentication Template updating Gestures Biometrics Security Accelerometers This article focuses on the evaluation of a biometric technique based on the performance of an identifying gesture by holding a telephone with an embedded accelerometer in his/her hand. The acceleration signals obtained when users perform gestures are analyzed following a mathematical method based on global sequence alignment. In this article, eight different scores are proposed and evaluated in order to quantify the differences between gestures, obtaining an optimal EER result of 3.42% when analyzing a random set of 40 users of a database made up of 80 users with real attempts of falsification. Moreover, a temporal study of the technique is presented leeding to the need to update the template to adapt the manner in which users modify how they perform their identifying gesture over time. Six updating schemes have been assessed within a database of 22 users repeating their identifying gesture in 20 sessions over 4 months, concluding that the more often the template is updated the better and more stable performance the technique presents.

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Pupil and Iris Localization for Iris Recognition in Mobile Phones

Cited by 41 publications

References 5 publications

Super-Resolution Iris Image Restoration using Single Image for Iris Recognition

Super-Resolution Iris Image Restoration using Single Image for Iris Recognition

Low-cost mobile video-based iris recognition for small databases

Score optimization and template updating in a biometric technique for authentication in mobiles based on gestures

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