Comparative analysis of global hand appearance-based person recognition

Dutağacı, Helin; Sankur, B.; Yörük, Erdem

doi:10.1117/1.2890986

Cited by 64 publications

(64 citation statements)

References 53 publications

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“…The common appearancebased features are PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), ICA, NMF and their kernelized versions. In this work, we opted for the ICA and NMF variety based on our previous successful experience in face recognition [25] and hand shape recognition [26]. Other interesting classes of features could be local features tailored to hand images.…”

Section: Feature Extractionmentioning

confidence: 99%

Hand vein biometry based on geometry and appearance methods

2011

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Many biometric systems, such as face, fingerprint and iris have been studied extensively for personal verification and identification purposes. Biometric identification with vein patterns is a more recent approach that uses the vast network of blood vessels underneath a person's skin. These patterns in the hands are assumed to be unique to each individual and they do not change over time except in size. As veins are under the skin and have a wealth of differentiating features, an attempt to copy an identity is extremely difficult. These properties of uniqueness, stability and strong immunity to forgery of the vein patterns make it a potentially good biometric trait which offers greater security and reliable features for personal identification. In this study, we present a novel hand vein database and a biometric technique based on the statistical processing of the hand vein patterns. The BOSPHORUS hand vein database has been collected under realistic conditions in that subjects had to undergo the procedures of holding a bag, pressing an elastic ball and cooling with ice, all exercises that force changes in the vein patterns. The applied recognition techniques are a combination of geometric and appearance-based techniques and good identification performances have been obtained on the database. Index TermsVein biometry, Hand vein database, Infrared imaging, BOSPHORUS hand vein database

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Section: Feature Extractionmentioning

confidence: 99%

Hand vein biometry based on geometry and appearance methods

2011

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“…The databases were created for various purposes and they contain 2D images or video sequences, in some cases extended with the depth data acquired using a Kinect sensor or ToF cameras. The Bosphorus set [7] is used to evaluate biometric identification from hand shapes, hence the images come from many different individuals presenting a hand with extended digits. The Dexter 1 set was created to measure accuracy of fingertip tracking in video sequences.…”

Section: Data Setsmentioning

confidence: 99%

Hand landmarks detection and localization in color images

Grzejszczak

Kawulok

Gałuszka

2015

Multimed Tools Appl

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This paper introduces a new method for detecting and localizing hand landmarks in 2D color images. Location of the hand landmarks is an important source of information for recognizing hand gestures, effectively exploited in a number of recent methods which operate from the depth maps. However, this problem has not yet been satisfactorily solved for 2D color images. Here, we propose to analyze the skin-presence masks, as well as the directional image of a hand using the distance transform and template matching. This makes it possible to detect the landmarks located both at the contour and inside the hand masks. Moreover, we performed an extensive experimental study to compare the proposed method with a number of state-of-the-art algorithms. The obtained quantitative and qualitative results clearly indicate that our approach outperforms other methods, which may help improve the existing gesture recognition systems.

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“…Regarding shape-based recognition applied to other biometrics traits, we may find examples in hand [13,[25][26][27] and signature biometrics [28,29].…”

Section: Figmentioning

confidence: 99%

Feature exploration for biometric recognition using millimetre wave body images

Gonzalez-Sosa¹,

Vera-Rodríguez²,

Fiérrez³

et al. 2015

J Image Video Proc.

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The use of millimetre wave images has been proposed recently in the biometric field to overcome certain limitations when using images acquired at visible frequencies. Furthermore, the security community has started using millimetre wave screening scanners in order to detect concealed objects. We believe we can exploit the use of these devices by incorporating biometric functionalities. This paper proposes a biometric recognition system based on the information of the silhouette of the human body, which may be seen as a type of soft biometric trait. To this aim, we report experimental results on the BIOGIGA database with four feature extraction approaches (contour coordinates, shape contexts, Fourier descriptors and landmarks) and three classification methods (Euclidean distance, dynamic time warping and support vector machines). The best configuration of 1.33 % EER is achieved when using contour coordinates with dynamic time warping.

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Comparative analysis of global hand appearance-based person recognition

Cited by 64 publications

References 53 publications

Hand vein biometry based on geometry and appearance methods

Hand vein biometry based on geometry and appearance methods

Hand landmarks detection and localization in color images

Feature exploration for biometric recognition using millimetre wave body images

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