Iris Recognition in Mobile Phone Based on Adaptive Gabor Filter

Jeong, Dae Sik; Park, Hyun-Ae; Park, Kang Ryoung; Kim, Jaihie

doi:10.1007/11608288_61

Cited by 31 publications

(17 citation statements)

References 12 publications

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“…This may be mainly due to the highly constrained nature of iris recognition systems as well as the inability of existing smartphone cameras to produce adequate quality images for reliable iris recognition performance. One early work in this field shows a cold mirror with IR pass filter (750nm) attached on a Samsung SPH-S2300 camera-phone with 2048 × 1536 pixel CCD sensor and 3x optical zoom [14]. Later Cho, Park, and Rhee [13] improved the localization of pupil and iris regions for the same system.…”

Section: Review Of Related Researchmentioning

confidence: 99%

Evaluation of combined visible/NIR camera for iris authentication on smartphones

Thavalengal

Bigioi

Corcoran

2015

2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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PublicationDate 2015 Publication InformationThavalengal, S.; Bigioi, P.; Corcoran, P., "Evaluation of combined visible/NIR camera for iris authentication on smartphones," AbstractIris biometrics provide a mature and robust method of authentication, but are typically applied in a controlled environment and under constrained acquisition conditions. In this paper, the adaption of iris biometrics for unconstrained, hand-held use cases such as smartphones is investigated. A prototype optics-sensor combination is analysed in terms of its optical properties and iris imaging capabilities. The corresponding camera system with dual visible/NIR sensing capabilities and 4 Megapixel resolution is tested for suitability to implement iris recognition on smartphones. Recognition performance is analysed together with image quality comparisons. Preliminary results indicate that there are challenges to achieve reliable recognition performance in unconstrained use cases. Current optical systems are not diffraction limited, particularly at NIR wavelengths; pixel resolutions are close to the useful limits for iris recognition and acquisition conditions are challenging. Nevertheless, our findings indicate a similar camera module, with an improved optics and sensor, could combine biometric authentication with more conventional front-camera functions such as the capture of selfie images.

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Section: Review Of Related Researchmentioning

confidence: 99%

Evaluation of combined visible/NIR camera for iris authentication on smartphones

Thavalengal

Bigioi

Corcoran

2015

2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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“…This differs from its use on a typical smartphone with a single fixed camera, unconstrained eye positions and limited control of illumination conditions. Some studies have begun to appear that deal directly with the iris acquisition problems for mobile phones [15]- [18] but these do not consider the current state-of-art and tend to ignore optical and quality issues that are critical for successful iris region acquisition and iris segmentation.…”

Section: B Iris Technology -How Practical Is It?mentioning

confidence: 99%

Biometric technology and smartphones: A consideration of the practicalities of a broad adoption of biometrics and the likely impacts

Corcoran

Costache

2015

2015 IEEE International Symposium on Technology and Society (ISTAS)

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“…Biometrics complement or substitute the traditional methods which benefits from its features of safety, reliability and convenience. However, current biometric identification methods, such as face recognition [1], fingerprint identification [2], iris recognition [3] and handwritten signatures [4], have the drawbacks of requiring high cost of technology or specific hardware, or being affected by the surrounding environment easily. Meanwhile, the face, fingerprint, iris and signature are significant features that determine someone uniquely and cannot be changed or replaced anymore.…”

Section: Introductionmentioning

confidence: 99%

A Smart phone Identification Method Based on Gesture

Zhang

2016

ITM Web Conf.

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Abstract. In order to promote the practicality of smart phone identification based on gesture, we introduce weighted morphological characteristics and early termination of authentication into dynamic time warping (DTW) algorithm, which based on characteristic moving data captured by in-built accelerometer and gyroscopes, and put forward an effective identification algorithm (ME-DTW) for smartphone. The algorithm controls the contribution made by the difference between the latitudes to the total Euclidean distance by smartphone morphological characteristics. It also introduces restricted areas touch trigger gesture acquisition scheme and authentication gesture length selection scheme based on normal distribution, which effectively improve the identification accuracy and efficiency. Experimental results show that: when others imitate gestures attack false acceptance rate tends to 0%, the personal identification false rejection rate remained at 3.29%, which can meet most practical security needs

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Iris Recognition in Mobile Phone Based on Adaptive Gabor Filter

Cited by 31 publications

References 12 publications

Evaluation of combined visible/NIR camera for iris authentication on smartphones

Evaluation of combined visible/NIR camera for iris authentication on smartphones

Biometric technology and smartphones: A consideration of the practicalities of a broad adoption of biometrics and the likely impacts

A Smart phone Identification Method Based on Gesture

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