Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters

Among several palmprint recognition methods proposed recently, coding-based approaches using multi-spectral palmprint images are attractive owing to their high recognition rates. Aiming to further improve the performance of these approaches, this paper presents a novel multi-spectral palmprint recognition approach based on oriented multiscale log-Gabor filters. The proposed method aims to enhance the recognition performances by proposing novel solutions at three stages of the recognition process. Inspired by the bitwise competitive coding, the feature extraction employs a multi-resolution log-Gabor filtering where the final feature map is composed of the winning codes of the lowest filters’ bank response. The matching process employs a bitwise Hamming distance and Kullback–Leibler divergence as novel metrics to enable an efficient capture of the intra- and inter-similarities between palmprint feature maps. Finally, the decision stage is carried pout using a fusion of the scores generated from different spectral bands to reduce overlapping. In addition, a fusion of the feature maps through two proposed novel feature fusion techniques to allow us to eliminate the inherent redundancy of the features of neighboring spectral bands is also proposed. The experimental results obtained using the multi-spectral palmprint database MS-PolyU have shown that the proposed method achieves high accuracy in mono-spectral and multi-spectral recognition performances for both verification and identification modes; and also outperforms the state-of-the-art methods

Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters

Among several palmprint recognition methods proposed recently, coding-based approaches using multi-spectral palmprint images are attractive owing to their high recognition rates. Aiming to further improve the performance of these approaches, this paper presents a novel multi-spectral palmprint recognition approach based on oriented multiscale log-Gabor filters. The proposed method aims to enhance the recognition performances by proposing novel solutions at three stages of the recognition process. Inspired by the bitwise competitive coding, the feature extraction employs a multi-resolution log-Gabor filtering where the final feature map is composed of the winning codes of the lowest filters’ bank response. The matching process employs a bitwise Hamming distance and Kullback–Leibler divergence as novel metrics to enable an efficient capture of the intra- and inter-similarities between palmprint feature maps. Finally, the decision stage is carried pout using a fusion of the scores generated from different spectral bands to reduce overlapping. In addition, a fusion of the feature maps through two proposed novel feature fusion techniques to allow us to eliminate the inherent redundancy of the features of neighboring spectral bands is also proposed. The experimental results obtained using the multi-spectral palmprint database MS-PolyU have shown that the proposed method achieves high accuracy in mono-spectral and multi-spectral recognition performances for both verification and identification modes; and also outperforms the state-of-the-art methods

An improved palmprint recognition system using iris features

This paper presents a bimodal biometric recognition system based on the extracted features of the human palmprint and iris using a new graph-based approach termed Fisher locality preserving projections (FLPP). This new technique employs two graphs with the first being used to characterize the within-class compactness and the second dedicated to the augmentation of the between-class separability. By applying the FLPP, only the most discriminant and stable palmprint and iris features are retained. FLPP was implemented on the frequency domain by transforming the extracted region of interest extraction of both biometric modalities using Fourier transform. Subsequently, the palmprint and iris features vectors obtained are matched with their counterpart in the templates databases and the obtained scores are fused to produce a final decision. The proposed combination of palmprint and iris patterns has shown an excellent performance compared to unimodal palmprint biometric recognition. The system was evaluated on a database of 108 subjects and the experimental results show that our system performs very well and achieves a high accuracy expressed by an equal error rate of 0.00%

Authentication technology methods for E-Commerce applications in Nigeria — a case for biometric digital security contactless palm vein authentication

E-Commerce has become one of the most interesting and beneficial Internet-enabled systems for humanity. E-Commerce has served as an economic enabler and driver for developed countries because of the total adoption by their citizens. However, in Nigeria citizens have rejected E-Commerce due to a lack of trust and inadequate security. This research identifies several factors that lead to distrust of E-Commerce systems in Nigeria. These factors: perceived fear, security, perceived risk, trust, usability, perceived advantage, and use of web assurance seal services are very important for intention to adopt E-Commerce as an online transaction technology. This thesis uses a novel Design Fiction and E-Commerce website simulation methodology to show citizens how new and improved security in E-Commerce could increase those citizens' trust and thus increase their intention to adopt E-Commerce. The research surveys a broad demographic sample of citizens from Nigeria who completed a set of tasks associated with the novel Design Fiction and E-Commerce website simulation followed by a detailed questionnaire. The questionnaire, with associated items, was designed to answer the research questions and hypothesis based on the E-Commerce Adoption Model proposed in the thesis. This new E-Commerce Adoption model is based on the Technology Acceptance Model and uses to comparatively test Digital Signature, Finger Print Identification, and Contactless Palm Vein Authentication technologies in E-Commerce transactions. Results from the survey show that Contactless Palm Vein Authentication leads to greater trust in E-Commerce in Nigeria. The thesis research findings also indicate that new improved security authentication techniques are overdue. The research indicates that poor E-Commerce adoption in Nigeria is mainly due to a key identified factor, which is security. The conceptual model and trust model are developed for E-Commerce adoption in Nigeria. Therefore, it shows that citizens are willing to accept Contactless Palm Vein Authentication as a solution. In particular, the research results also show that there are strong relationships between all the identified factors and citizens’ intention to adopt E-Commerce in Nigeria thus rejecting all null hypotheses