Biometric Person Identification System: A Multimodal Approach Employing Spectral Graph Characteristics of Hand Geometry and Palmprint

Angadi, S. A.; Hatture, Sanjeevakumar M.

doi:10.5815/ijisa.2016.03.06

Cited by 21 publications

(12 citation statements)

References 22 publications

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“…Currently, there are also multi-biometric systems that use a combination of multiple biometric characteristics. A palmprint [41][42][43][44][45] or bloodstream topography [46][47][48] is used in combination with hand geometry or silhouette. The topography of bloodstream is measured either on the palm or back of the hand when the whole hand is scanned.…”

Section: Current Methods In Hand-based Biometric Systemsmentioning

confidence: 99%

“…SVM aims to find a superstructure that divides the symptom space. SVM used Vinodkumar and Srikantaswamy as a classifier in a multibiometric system, where the biometric characteristics were hand geometry, fingerprints and palmprint [91]; however, they have also been used in many other hand-based multi-biometric systems [41,42,49,92].…”

Section: Defined Machine Learning As Follows: "A Computer Program Imentioning

confidence: 99%

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Hand-Based Biometric Recognition Technique – Survey

Prihodova¹,

Hub²

2020

Adv. sci. technol. eng. syst. j.

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In today's modern world, reliable automatic personal recognition is a crucial area of discussion, primarily because of the increased security risks. A large number of systems first require the recognition of a person before they can access their services. Biometric recognition can be used, which can be understood as automatic identification or automatic verification of persons based on physiological or behavioural characteristics. Examples of biometric characteristics may be the fingerprint, face, signature, hand geometry. There are many approaches, and each has its pros and cons. However, there is currently no current extensive research and evaluation of hand-based biometric systems. Given the userfriendliness of these systems and the needs of society, this article aims to compare different methods of biometric recognition based on hand, so that the article reduces the entry barrier into this area of research. Furthermore, the article aims to determine the research gap and suggest possible directions for research in the future.

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Section: Current Methods In Hand-based Biometric Systemsmentioning

confidence: 99%

Section: Defined Machine Learning As Follows: "A Computer Program Imentioning

confidence: 99%

Hand-Based Biometric Recognition Technique – Survey

Prihodova¹,

Hub²

2020

Adv. sci. technol. eng. syst. j.

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“…. Based on the data which has been used for personal verification, human hand reading technologies can be divided into three classifications (Angadi, and Hatture, 2016):…”

Section: Fig 7: Example Of Hand Scanningmentioning

confidence: 99%

Comparative Study of Computational Intelligence Paradigms for Intelligent Access Control Based on Biometrics Methodologies

Abdulrahman¹

2020

JMCMS

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Intelligent access control is one of the challenging tasks in the human identification, image analysis, and diagnoses disease and computer vision. The focus towards the intelligent access control has been increased in the last years due to its various, applications in different domains. For this reason, it was used intelligent access control to facilitate the task of identifying the human. The objective of this paper is to analyse and evaluate the seven techniques for the intelligent access control and advantage and disadvantage of each type. In addition, represents biometrics characteristics in general. The Biometric feature is used to determine human identity including the brain signals. Through this study, brain signals are the best among the techniques. In this study, we first presented a survey of the Computational intelligence techniques in biometrics. All previous studies used brain EEG signals. Where different algorithms were used to extract, the features. These feature applied for human identification. The Accuracy achieved was up to 97% according to the studies found in this research.

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“…Geometry features and palmprint features are extracted from depth images and intensity images, respectively, invariant to distance and perspective effects. In our previous work, the graph spectral properties of hand-geometry and palmprint biometric traits are combined at feature level to improve the performance of the biometric system [25].…”

Section: Review Of Related Workmentioning

confidence: 99%

Hand geometry based user identification using minimal edge connected hand image graph

Angadi

Hatture²

2018

IET Computer Vision

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In a previously reported work, the user's hand is represented as a weighted undirected complete connected graph and spectral properties of the graph are extracted and used as feature vectors. To reduce the complexity in representing the hand image as a complete connected graph and to achieve the higher identification rate, the hand image is sought to be represented as minimal edge connected graph. The experiments are conducted separately for 16 topologies of minimal edge connected graph selected empirically to investigate the performance of the hand-geometry system. The prominent edges of hand image graph are identified experimentally by computing the identification rate. In this study, an innovative peg-free handgeometry-based user identification system using spectral properties of a minimal edge connected graph representation of hand image is proposed. The multiclass support vector machine is employed for identification of the claimed user. The geometrical information embedded in the prominent edges will contribute to achieve better identification rate. The experimentation is carried on two databases, namely GPDS150 hand database and hand images of VTU-BEC-DB multimodal database. The minimal edge connected graph with 30 prominent edges of hand image graph achieves better identification with a faster rate.

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Biometric Person Identification System: A Multimodal Approach Employing Spectral Graph Characteristics of Hand Geometry and Palmprint

Cited by 21 publications

References 22 publications

Hand-Based Biometric Recognition Technique – Survey

Hand-Based Biometric Recognition Technique – Survey

Comparative Study of Computational Intelligence Paradigms for Intelligent Access Control Based on Biometrics Methodologies

Hand geometry based user identification using minimal edge connected hand image graph

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