Robust Biometric System Using Palmprint for Personal Verification

Badrinath, G. S.; Gupta, Phalguni

doi:10.1007/978-3-642-01793-3_57

Cited by 24 publications

(15 citation statements)

References 16 publications

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“…The comparison of OLOF method with several other competing methods [3] suggests its superiority in several palm print biometric devices. We worked out the OLOF features as defined in [18].…”

Section: Palm Print Feature Extraction Methodsmentioning

confidence: 99%

On the Feasibility of Interoperable Schemes in Hand Biometrics

Morales

Gonzalez

Ferrer

2012

Sensors

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Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.

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Section: Palm Print Feature Extraction Methodsmentioning

confidence: 99%

On the Feasibility of Interoperable Schemes in Hand Biometrics

Morales

Gonzalez

Ferrer

2012

Sensors

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“…The comparison of OLOF method with several other competing methods [16] suggests its superiority in several palmprint biometric devices. We have worked out the OLOF features as defined in [19].…”

Section: B Palmprint Feature Extraction Methods Studiedmentioning

confidence: 99%

Looking for Hand Biometrics Interoperability

Gonzalez

Morales

Ferrer

et al. 2011

2011 International Conference on Hand-Based Biometrics

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Identification of people through hand based biometrics has been extensively researched by different scientific groups due to its simplicity, reliability, and acceptability. In fact, a great amount of proposal based on different procedures and acquisition devices has been published in the literature. However, the interoperability among them has been barely studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric systems. The experiments has been conducted on a database composed by 5400 hand images acquired with 6 different hand-shape biometric approaches including flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices including acquisitions on both sides of the hand. Our results suggest we are in the way to reach acceptable results of interoperability.

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“…Further, fisher linear discrimination is applied for dimension reduction 15 . Recent researches are focused on improving the quality of palmprint features against variations in position, rotation, scale, noise, translation, occlusion, and illumination 4,15,19,20 . To make a robust palmprint recognition system, two or more feature extraction techniques are essentially combined 15 .…”

Section: Literature Reviewmentioning

confidence: 99%

Occlusion Invariant Palmprint Recognition with ULBP Histograms

Tamrakar

Khanna

2015

Procedia Computer Science

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This work presents a palmprint recognition approach based on the local distribution of uniform patterns. Preprocessing segments palmprint region from foreground of image as well as aligns the palmprint along the line between tips of middle finger and mid of wrist. Palmprint texture has line and wrinkles like features which are a type of uniform patterns. Uniform LBP (ULBP) refers to the pattern of uniform appearance with limited discontinuities. ULBP histograms are used as features to handle occlusion upto 36%. Experiments are performed on 400 classes of the PolyU 2D, 600 classes of CASIA and 150 classes of IIITDMJ palmprint database. Correct identification rates of 99.6% for normal palmprints and 99% for randomly occluded palmprints are obtained on PolyU 2D database.

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Robust Biometric System Using Palmprint for Personal Verification

Cited by 24 publications

References 16 publications

On the Feasibility of Interoperable Schemes in Hand Biometrics

On the Feasibility of Interoperable Schemes in Hand Biometrics

Looking for Hand Biometrics Interoperability

Occlusion Invariant Palmprint Recognition with ULBP Histograms

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