Palmprint recognition system on mobile devices with double-line-single-point assistance

Leng, Lu; Gao, Fumeng; Chen, Qi; Kim, Cheonshik

doi:10.1007/s00779-017-1105-2

Cited by 30 publications

(19 citation statements)

References 31 publications

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“…The valid frames are selected according to the finger gap judgement [14]. The finger gap is the sub-region of hand, i.e., the shaded rectangle in Figure 2…”

Section: Valid Frame Selectionmentioning

confidence: 99%

Video Palmprint Recognition System Based on Modified Double-line-single-point Assisted Placement

Wu¹,

Leng²

2021

J Multimed Inf Syst

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Palmprint has become a popular biometric modality; however, palmprint recognition has not been conducted in video media. Video palmprint recognition (VPR) has some advantages that are absent in image palmprint recognition. In VPR, the registration and recognition can be automatically implemented without users' manual manipulation. A good-quality image can be selected from the video frames or generated from the fusion of multiple video frames. VPR in contactless mode overcomes several problems caused by contact mode; however, contactless mode, especially mobile mode, encounters with several revere challenges. Double-line-single-point (DLSP) assisted placement technique can overcome the challenges as well as effectively reduce the localization error and computation complexity. This paper modifies DLSP technique to reduce the invalid area in the frames. In addition, the valid frames, in which users place their hands correctly, are selected according to finger gap judgement, and then some key frames, which have good quality, are selected from the valid frames as the gallery samples that are matched with the query samples for authentication decision. The VPR algorithm is conducted on the system designed and developed on mobile device.

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“…The valid frames are selected according to the finger gap judgement [14]. The finger gap is the sub-region of hand, i.e., the shaded rectangle in Figure 2…”

Section: Valid Frame Selectionmentioning

confidence: 99%

Video Palmprint Recognition System Based on Modified Double-line-single-point Assisted Placement

Wu¹,

Leng²

2021

J Multimed Inf Syst

Self Cite

View full text Add to dashboard Cite

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“…ere are also some examples of using palmprint biometrics in a mobile scenario [45][46][47]. It is clear that implementing a palmprint-based biometric system using a smartphone may be successful even though it carries some difficulties: complex background, changing illumination, hand pose variation, and last but not least a limited processing power [48].…”

Section: Related Workmentioning

confidence: 99%

Lightweight Verification Schema for Image-Based Palmprint Biometric Systems

Giełczyk

Choraś

Kozik

2019

Mobile Information Systems

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Palmprint biometrics is a promising modality that enables efficient human identification, also in a mobile scenario. In this paper, a novel approach to feature extraction for palmprint verification is presented. The features are extracted from hand geometry and palmprint texture and fused. The use of a fusion of features facilitates obtaining a higher accuracy and, at the same time, provides more robustness to intrusive factors like illumination, variation, or noise. The major contribution of this paper is the proposition and evaluation of a lightweight verification schema for biometric systems that improves the accuracy without increasing computational complexity which is a necessary requirement in real-life scenarios.

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“…Outline of the associated CA works using palmprint biometrics This work achieves the EER using simplified 2DPHC in the view of changeability is 0.484 and in the view of verification is 1.206. Leng et al (2018) has proposed novel assistant approach called double line single point (DLSP) to overcome the problems are there in palmprint authentication in the mobile environments such as diverse illuminations, gesture of hand, constrained hardware resource and complex background. The assistant approach incorporate two line portions and one point which assist individuals with placing their hands effectively and precisely and also complexity in computation is minimised and real-time performance is enhanced.…”

Section: Tablementioning

confidence: 99%

A survey on different continuous authentication systems

Ayeswarya

Norman

2019

IJBM

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There has been significant research in the provision of trustworthy initial login user authentication, however, there is still need for continuous authentication during a user session. Most mobile devices and computer systems authenticate a user only at the initial login session and do not take steps to recognise whether the present user is still the initial authorised user or an imposter pretending to be a valid user. Therefore, a system to check the identity of the user continuously throughout the whole session is necessary. To ensure the authenticity of the user during their whole login session, a continuous user authentication mechanism is required. In this paper, an overview of different continuous authentication methods is presented along with a discussion on the merits and demerits of the available approaches. This paper also discusses the understanding of the emerging necessities and open problems in continuous user authentication system.

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Palmprint recognition system on mobile devices with double-line-single-point assistance

Cited by 30 publications

References 31 publications

Video Palmprint Recognition System Based on Modified Double-line-single-point Assisted Placement

Video Palmprint Recognition System Based on Modified Double-line-single-point Assisted Placement

Lightweight Verification Schema for Image-Based Palmprint Biometric Systems

A survey on different continuous authentication systems

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