Research and Development of Palmprint Authentication System Based on Android Smartphones

Zhang, Xinman; Jing, Kunlei; Song, Guokun

doi:10.1155/2020/8846192

Cited by 5 publications

(2 citation statements)

References 32 publications

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“…Zhang et al [17] have investigated a study towards various techniques where smartphones have been used for the palmprint verification process. Another recent application-based study towards hand biometric has been carried out by Yang et al [18] towards user identification.…”

Section: Related Workmentioning

confidence: 99%

Novel Optimization of Identified Palm Geometry Using Image Segmentation

Mahalakshmi¹,

Sheela²

2022

Int. J. Onl. Eng.

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Segmentation is one of the essential steps towards the identification of any object in the domain of image processing. In the area of hand-based biometric which is mainly deployed for a user authentication system, segmentation plays a critical role. A review of existing studies shows that there is a very less amount potential contribution in this regard. Therefore, this manuscript presents a novel optimization scheme towards palm geometry recognition system where segmentation process is the prime highlights for classification of hand and background considering a case study of finger recognition. Further, the proposed scheme uses masking operation where the Region-of-Interest section of hand is subjected to segmentation. Further proposed system uses machine learning approach (convolution neural network and Siamese Neural Network) to further assist in optimizing the segmentation performance. The experimental outcome of the study shows proposed system offers better accuracy compared to the existing system.

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Section: Related Workmentioning

confidence: 99%

Novel Optimization of Identified Palm Geometry Using Image Segmentation

Mahalakshmi¹,

Sheela²

2022

Int. J. Onl. Eng.

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“…Zhang et al [29] had used a deep CNN to identify the palmprint in the biometric authentication system. Zhang et al [30] studied schemes in the context where smartphones based biometric authentication system that uses identification of palmprint.…”

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confidence: 99%

A hybrid learning scheme towards authenticating hand-geometry using multi-modal features

Shivabasappa

Sheela²

2023

IJECE

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<span lang="EN-US">Usage of hand geometry towards biometric-based authentication mechanism has been commercially practiced since last decade. However, there is a rising security problem being surfaced owing to the fluctuating features of hand-geometry during authentication mechanism. Review of existing research techniques exhibits the usage of singular features of hand-geometric along with sophisticated learning schemes where accuracy is accomplished at the higher cost of computational effort. Hence, the proposed study introduces a simplified analytical method which considers multi-modal features extracted from hand geometry which could further improve upon robust recognition system. For this purpose, the system considers implementing hybrid learning scheme using convolution neural network and Siamese algorithm where the former is used for feature extraction and latter is used for recognition of person on the basis of authenticated hand geometry. The main results show that proposed scheme offers 12.2% of improvement in accuracy compared to existing models exhibiting that with simpler amendment by inclusion of multi-modalities, accuracy can be significantly improve without computational burden.</span>

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Contactless Palmprint Recognition System: A Survey

et al. 2022

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Information systems in organizations traditionally require users to remember their secret pins (password), token, card number, or both to confirm their identities. However, the technological trend has been moving towards personal identification based on individual behavioural attributes (such as gaits, signature, and voice) or physiological (such as palmprint, fingerprint, face, iris, or ear). These attributes (biometrics) offer many advantages over knowledge and possession-based approaches. For example, palmprint images have rich, unique features for reliable human identification, and it has received significant attention due to their stability, reliability, uniqueness, and non-intrusiveness. This paper provides an overview and evaluation of contactless palmprint recognition system, the state-of-the-art performance of existing works, different types of "Region of Interest" (ROI) extraction algorithms, feature extraction, and matching algorithms. Finally, the findings obtained are presented and discussed.INDEX TERMS biometrics, information system, palmprint images, region of interest

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Research and Development of Palmprint Authentication System Based on Android Smartphones

Cited by 5 publications

References 32 publications

Novel Optimization of Identified Palm Geometry Using Image Segmentation

Novel Optimization of Identified Palm Geometry Using Image Segmentation

A hybrid learning scheme towards authenticating hand-geometry using multi-modal features

Contactless Palmprint Recognition System: A Survey

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