A New Hand Image Database Simultaneously Acquired in Visible, Near-Infrared and Thermal Spectrums

Faundez-Zanuy, Marcos; Mekyska, Jiří; Font-Aragones, X.

doi:10.1007/s12559-013-9230-3

Cited by 31 publications

(16 citation statements)

References 17 publications

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“…2 when translation of 2 is applied to query image. Algorithm was also tested on bosphorous hand vein dataset [10], vein pattern dataset by CIE biometrics, thermal images in [II] by wang and Liu, thermal focus image dataset by SP lab [12] [13]. Our algorithm was able to run properly on all of these images without any major changes.…”

Section: Testing Resultsmentioning

confidence: 99%

Vein biometric security using irreversible curve fitting accounting for minimum storage

Agarwal

Maheshwari

Yadav

2014

2014 International Conference on Signal Propagation and Computer Technology (ICSPCT 2014)

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Vein biometric is hidden so provides more secrecy as compared to other biometric traits. The paper presents a novel approach in vein biometric system that accounts for minimum data storage but still keeping up with maximum information. A new strategy is presented for template generation and storage. Polynomial curve fitting process has been applied on thinned vein pattern to output most uniform best approximation vein curves. Matching has been done on basis of Hausdorff distance. Obtained experimental results are encouraging and have been claiming 0% FAR and 0% FRR. The amount of storage needed for template data has been reduced greatly. The data stored is irreversible to generate the template again even when no template encryption scheme has been used that provides attack resistance to the system.

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Section: Testing Resultsmentioning

confidence: 99%

Vein biometric security using irreversible curve fitting accounting for minimum storage

Agarwal

Maheshwari

Yadav

2014

2014 International Conference on Signal Propagation and Computer Technology (ICSPCT 2014)

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“…In our study, we chose seven different texture descriptors (GABOR, HOG, GLCM, SSF, DWT, WPT, and LBP) and three multiclass classifiers (LDA, ESVM, KNN) for supervised identification of humans from their hand vein images. A database of infrared (IR) dorsal hand vein images, which were captured via an ETIP 7320 P-Series Infrared Camera is chosen for our study [9].…”

Section: A Overview Of Identification Systemmentioning

confidence: 99%

“…In our experiment, a public dataset was chosen, namely Technocampus Hand Image Database [9]. We chose this dataset as it maintains uniform conditions for hand regions, and images have sufficient resolution.…”

Section: Experimental Evaluationmentioning

confidence: 99%

Texture Based Vein Biometrics for Human Identification: A Comparative Study

Bashar¹,

Murshed

2018

2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC)

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Hand vein biometric is an important modality for human authentication and liveness detection in many applications. Reliable feature extraction is vital to any biometric system. Over the past years, two major categories of vein features, namely vein structures and vein image textures, were proposed for hand dorsal vein based biometric identification. Of them, texture features seem important as it can combine skin microtextures along with vein properties. In this study, we have performed a comparative study to identify potential texture features and feature-classifier combination that produce efficient vein biometric systems. Seven texture features (HOG, GABOR, GLCM, SSF, DWT, WPT, and LBP) and three multiclass classifiers (LDA, ESVM, and KNN) were explored towards the supervised identification of human from vein images. An experiment with 400 infrared (IR) hand images from 40 adults indicates the superior performance of the histogram of oriented gradients (HOG) and simple local statistical feature (SSF) with LDA and ESVM classifiers in terms of average accuracy (> 90%), average Fscore (> 58%) and average specificity (>93%). The decision-level fusion of the LDA and ESVM classifier with single texture features showed improved performances (by 2.2 to 13.2% of average Fscore) over individual classifier for human identification with IR hand vein images.

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“…For experimental purposes two different databases were used: Technocampus hand Image Database (THID) [20,23,58] and also database GPDS [22,55,59] The Grupo de Procesado Digital de la señal, GPDS (Digital Signal Processing Group) with DPDS (División de Procesado Digital de la Señal) from Instituto para el Desarrollo Tecnológico y la Innovación en Comunicaciones IDeTIC, University of Las Palmas de Gran Canaria, Spain.…”

Section: Introductionunclassified

Hand contour classification using evolutionary algorithm

Moravec¹

2020

ITC

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A biometric identification of persons wchich utilize contour of a human hand belogs to still very interesting and still not totally explored areas and its accuracy and effectiveness depends on technical capabilities to some extent. Presented paper solves given problem using combination of different algorithms. A hand contour is used, topological description of the hand, evolutionary algorithm, algorithm linear regression to estimate the knuckles positions and for contours comparison is used an algorithm Iterative Closest Point (ICP) in its genuine shape. All 5 fingers is at computer classification fully moveable, thumb has 2 knuckles. Modern evolutionary optimizers enable markedly to cut down computational demands of the algorithm ICP. Experimental verification of proposed recipes were performed with use of two different databases named THID and GPDS with persons of both gender and different age (cca 20-65let) with total number of oeprons in individual database 104 and 94. Experimental results checked succesfuly suitability of use combination of methods ICP and evolutionary optimizer which is named as EPSDE for solving of the given task with algorithmic complexity O(N) and success rate give by coefficient THID:EER=0.38% and GPDS:EER=0.35% on real images.

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A New Hand Image Database Simultaneously Acquired in Visible, Near-Infrared and Thermal Spectrums

Cited by 31 publications

References 17 publications

Vein biometric security using irreversible curve fitting accounting for minimum storage

Vein biometric security using irreversible curve fitting accounting for minimum storage

Texture Based Vein Biometrics for Human Identification: A Comparative Study

Hand contour classification using evolutionary algorithm

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