access icon free Method for using visible ocular vasculature for mobile biometrics

Securing personal information on handheld devices, especially smartphones, has gained a significant interest in recent years. Yet, most of the popular biometric modalities require additional hardware. To overcome this difficulty, the authors propose utilising the existing visible light cameras in mobile devices. Leveraging visible vascular patterns on whites of the eye, they develop a method for biometric authentication suitable for smartphones. They start their process by imaging and segmenting whites of the eyes, followed by image quality assessment. The authors’ stage 1 matcher is a three-step process that entails extracting interest points [Harris–Stephens, features from accelerated segment test, and speeded up robust features (SURF)], building features (SURF and fast retina keypoint) around those points, and match score generation using random sample consensus-based registration. Stage 2 matcher uses registered Gabor phase filtered images to generate orientation of local binary pattern features for its correlation-based match metric. A fusion of stage 1 and stage 2 match scores is calculated for the final decision. Using a dataset of 226 users, the authors’ results show equal error rates as low as 0.04% for long-term verification tests. The success of their framework is further validated on UBIRIS v1 database.

Inspec keywords: correlation theory; image registration; image matching; mobile computing; image filtering; smart phones; Gabor filters; biometrics (access control); random processes; video cameras; image fusion; feature extraction

Other keywords: random sample consensus-based registration; correlation-based match metric; image quality assessment; registered Gabor phase filtered image; mobile device; biometric authentication; visible light camera; feature extraction; handheld device; mobile biometrics; visible vascular pattern; local binary pattern feature orientation; image fusion; visible ocular vasculature; match score generation; smart phone; personal information security; UBIRIS v1 database

Subjects: Optical, image and video signal processing; Computer vision and image processing techniques; Other topics in statistics; Mobile, ubiquitous and pervasive computing; Other topics in statistics

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