Using biometrics authentication via fingerprint recognition in e-Exams in e-Learning environment

E-learning is a great opportunity for modern life. Notably, however, the tool needs to be coupled with efficient and reliable security mechanisms to ensure the medium can be established as a dependable one. Authentication of e-exam takers is of prime importance so that exams are given by fair means. A new approach shall be proposed so as to ensure that no unauthorised individuals are permitted to give the exams

Integrating shape and texture for hand verification

Author name used in this publication: Ajay KumarAuthor name used in this publication: David ZhangRefereed conference paper2004-2005 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Palmprint recognition using valley features

Author name used in this publication: David ZhangBiometrics Research Centre, Department of ComputingVersion of RecordPublishe

Android Based Palmprint Recognition System

This paper aims to build a palmprint recognition system based on Android. Line detection and non-overlapping blocks methods used on the design of palmprint recognition system. Normalized Euclidean distance was used to match the two feature vector. The similarity degrees was measured by the smallest value. The method was applied to the system can result an accuracy rate about 91,32% (FMR = 5,2%, FNMR = 3,68%, T = 0,265). System testing was done as much as 2500 times to the 50 participants with 3 reference images of each user. The factor that influenced on system accuracy was the process of image acquisition. Palmprint images was taken directly by using camera on the android smartphone device

Dermatoglyphic appraisal of multiple births women in Igbo-Ora and Ogbomosho, South west, Nigeria

The scientific study of epidermal ridges on the palms and toes is termed dermatoglyphics. Multiple births occur when more than one fetus results  from a single pregnancy. This study is aimed at determining the relationship if any between multiple births and palmar flexion creases. Two  hundred Igbo-Ora and one hundred Ogbomosho healthy and consenting adult female indigenes aged between 25-50 years were recruited and grouped into 4; group I consisted of multiple births women in Igbo-Ora; group II consisted of single births women in Igbo-Ora; group III consisted of multiple births women in Ogbomosho; and group IV consisted of single births women in Ogbomosho. A total of 600 palms (Igbo-Ora n=400; Ogbomosho n=200) comprising of both hands were used in the study. Palm prints samples were obtained by asking the participants to wash their hands, towel dry them, after which they were stained with stamp ink pad and prints made on A4 paper in duplicates. Palm print patterns of 105 (Igbo-Ora) and 50 (Ogbomosho) women with multiple births were compared with 95 (Igbo-Ora) and 50 (Ogbomosho) women with single births. The percentage number of primary, P and intersection, I of palmar creases with complete transverse creases, C (PIC) 300 bilaterally was significantly  greater (p < 0.005) in the hands of Igbo-Ora multiple births women (52.4 %) than their single births women (37.4%) while same trend was observed for Ogbomosho women although difference was statistically insignificant,(p > 0.005). In both Igbo-Ora and Ogbomosho women, PIC 310 bilaterally was found to be significantly higher (p < 0.05) in both hands of single births women than the multiple births women. Hence, dermatoglyphics can be said to have relationship with a woman’s tendency to giving birth to multiples. Keywords: Multiple births, dermatoglyphics, palmar flexion creases, Ogbomosho, Igbo-Or

Cross match-CHMM fusion for speaker adaptation of voice biometric

The most significant factor affecting automatic voice biometric performance is the variation in the signal characteristics, due to speaker-based variability, conversation-based variability and technology variability. These variations give great challenge in accurately modeling and verifying a speaker. To solve this variability effects, the cross match (CM) technique is proposed to provide a speaker model that can adapt to variability over periods of time. Using limited amount of enrollment utterances, a client barcode is generated and can be updated by cross matching the client barcode with new data. Furthermore, CM adds the dimension of multimodality at the fusion-level when the similarity score from CM can be fused with the score from the default speaker modeling. The scores need to be normalized before the fusion takes place. By fusing the CM with continuous Hidden Markov Model (CHMM), the new adapted model gave significant improvement in identification and verification task, where the equal error rate (EER) decreased from 6.51% to 1.23% in speaker identification and from 5.87% to 1.04% in speaker verification. EER also decreased over time (across five sessions) when the CM is applied. The best combination of normalization and fusion technique methods is piecewise-linear method and weighted sum

Sistem Pengenal Individu Berbasis Gabungan Palmprint dan Palm Geometry Menggunakan Pengukuran Geometris Palm dan Gabor Filter

Biometrics adalah salah satu bidang dalam computer science yang berkembang pesat belakangan ini. Dalam salah satu penerepannya, biometrics digunakan untuk mengidentifikasi citra dalam proses otentikasi. Karena alasan keandalan, jenis biometrics system yang sekarang banyak digunakan adalah yang multimodal. Kombinasi Palmprint dan palm geometry adalah kombinasi fitur yang dipilih untuk digunakan dalam penelitian ini. Kedua fitur memiliki keunggulan yaitu dapat diekstrak dari satu citra, sehingga memudahkan proses enrollment. Perhitungan performa akan dilakukan terhadap 600 citra palm dari dataset yang diambil dari database Casia Multispectral Palmprint yang berasal dari 100 user. Dari hasil pengujian didapatkan error rate sebesar 3.27% terhadap 600 citra palm yang menggunakan perbandingan data training dan testing 4:2, dengan menggunakan gabungan pengukuran geometris dengan menggunakan rasio dan konvolusi Gabor filter terhadap palmrpint dengan parameter orientasi 0°,30°,60°, 90°,120°,150° dan panjang gelombang 5,9,13,17 dengan bobot untuk masing-masing modal sebesar 0.6 dan 0.4. Kata Kunci: Multimodal Biometrics, Palmprint, Palm Geometry, Gabor Filter, Competitive Hand Valley Detectio

A New Hand Based Biometric Modality & An Automated Authentication System

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