131 research outputs found

    Hand Geometry Techniques: A Review

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    Volume 2 Issue 11 (November 2014

    A New Hand Based Biometric Modality & An Automated Authentication System

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    With increased adoption of smartphones, security has become important like never before. Smartphones store confidential information and carry out sensitive financial transactions. Biometric sensors such as fingerprint scanners are built in to smartphones to cater to security concerns. However, due to limited size of smartphone, miniaturised sensors are used to capture the biometric data from the user. Other hand based biometric modalities like hand veins and finger veins need specialised thermal/IR sensors which add to the overall cost of the system. In this paper, we introduce a new hand based biometric modality called Fistprint.  Fistprints can be captured using digital camera available in any smartphone. In this work, our contributions are: i) we propose a new non-touch and non-invasive hand based biometric modality called fistprint. Fistprint contains many distinctive elements such as fist shape, fist size, fingers shape and size, knuckles, finger nails, palm crease/wrinkle lines etc. ii) Prepare fistprint DB for the first time. We collected fistprint information of twenty individuals - both males and females aged from 23 years to 45 years of age. Four images of each hand fist (total 160 images) were taken for this purpose. iii) Propose Fistprint Automatic Authentication SysTem (FAAST). iv) Implement FAAST system on Samsung Galaxy smartphone running Android and server side on a windows machine and validate the effectiveness of the proposed modality. The experimental results show the effectiveness of fistprint as a biometric with GAR of 97.5 % at 1.0% FAR

    A Hand-Based Biometric Verification System Using Ant Colony Optimization

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    This paper presents a novel personal authentication system using hand-based biometrics, which utilizes internal (beneath the skin) structure of veins on the dorsal part of the hand and the outer shape of the hand. The hand-vein and the hand-shape images can be simultaneously acquired by using infrared thermal and digital camera respectively. A claimed identity is authenticated by integrating these two traits based on the score-level fusion in which four fusion rules are used for the integration. Before their fusion, each modality is evaluated individually in terms of error rates and weights are assigned according to their performance. In order to achieve an adaptive security in the proposed bimodal system, an optimal selection of fusion parameters is required. Hence, Ant Colony Optimization (ACO) is employed in the bimodal system to select the weights and also one out of the four fusion rules optimally for the adaptive fusion of the two modalities to meet the user defined security levels. The databases of hand-veins and the hand-shapes consisting of 150 users are acquired using the peg-free imaging setup. The experimental results show genuine acceptance rate (GAR) of 98% at false acceptance rate (FAR) of 0.001% and the system has the potential for any online personal authentication based application.

    A New Born Child Authentication System using Image Processing

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    The Missing, swapping, mixing, and illegal adoption of new born child is a global challenge and research done to solve this issue is minimal and least reported in the literature. As per our knowledge, there is no biometric system currently available that can be effectively used for new born child identification. The manual procedure of capturing inked footprints in practice for this purpose is limited for use inside hospitals and is not an effective solution for identification purposes. Hence, a new born child personal authentication system is proposed for this issue based on multi biometrics. The biometric traits considered are the footprint of the new born child and the fingerprint of the mother. An appropriate fusion scheme is implemented to overcome the drawbacks of a single modality. The experimental results are promising and prove to be an effective system

    Personal recognition using hand shape and texture

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    Author name used in this publication: Ajay Kumar2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

    Multimodal Biometrics for Person Authentication

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    Unimodal biometric systems have limited effectiveness in identifying people, mainly due to their susceptibility to changes in individual biometric features and presentation attacks. The identification of people using multimodal biometric systems attracts the attention of researchers due to their advantages, such as greater recognition efficiency and greater security compared to the unimodal biometric system. To break into the biometric multimodal system, the intruder would have to break into more than one unimodal biometric system. In multimodal biometric systems: The availability of many features means that the multimodal system becomes more reliable. A multimodal biometric system increases security and ensures confidentiality of user data. A multimodal biometric system realizes the merger of decisions taken under individual modalities. If one of the modalities is eliminated, the system can still ensure security, using the remaining. Multimodal systems provide information on the “liveness” of the sample being introduced. In a multimodal system, a fusion of feature vectors and/or decisions developed by each subsystem is carried out, and then the final decision on identification is made on the basis of the vector of features thus obtained. In this chapter, we consider a multimodal biometric system that uses three modalities: dorsal vein, palm print, and periocular

    New Mobile Phone and Webcam Hand Images Databases for Personal Authentication and Identification

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    AbstractIn this work we created two hand image databases, usingmobile phone cameras and webcams. Themajor goal of these databases is to build upon aperson's authentication/identification using hand biometrics,decreasing the need for expensive hand scanners. Both databases consist of 3000 hand images, 3 sessions x 5 images (per person)x 200 persons, and are available to freely download. The test protocol is defined for both databases; simple experiments were conducted using the same protocol. The results were encouraging for most of the persons (accuracy was greater than 80%), except for those who rotated their hands in an exaggerated manner in all directions
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