Integrating Palmprint and Fingerprint for Identity Verification

Chin, Yong Jian; Ong, Thian Song; Goh, Michael Kah Ong; Hiew, Bee Yan

doi:10.1109/nss.2009.25

Cited by 24 publications

(13 citation statements)

References 9 publications

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“…Biometric techniques are usually divided into two groups depending on the characteristic used to identify a person, namely physical and behavioural [4]. Physical biometric techniques are based on a physical characteristic preserved in time that a user owns (iris [5], fingerprint [6], hand geometry [7], face [8]) whereas behavioural techniques are related to something that the user is able to repeat in an unique manner (handwriting signature [9], keystroke dynamics [10], gait [11]). In this article, we propose a biometric technique in which a person is authenticated by making his/her handwritten signature in the air (in-air signature) while holding a mobile phone.…”

Section: Introductionmentioning

confidence: 99%

Analysis of pattern recognition techniques for in-air signature biometrics

Bailador

Ávila

Guerra-Casanova

et al. 2011

Pattern Recognition

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Keywords:Biometrics Signature Accelerometer Hidden Markov models Bayes Dynamic time warpingAs a result of advances in mobile technology, new services which benefit from the ubiquity of these devices are appearing. Some of these services require the identification of the subject since they may access private user information. In this paper, we propose to identify each user by drawing his/her handwritten signature in the air (in-air signature). In order to assess the feasibility of an in-air signature as a biometric feature, we have analysed the performance of several well-known pattern recognition techniques-Hidden Markov Models, Bayes classifiers and dynamic time warping-to cope with this problem. Each technique has been tested in the identification of the signatures of 96 individuals. Furthermore, the robustness of each method against spoofing attacks has also been analysed using six impostors who attempted to emulate every signature. The best results in both experiments have been reached by using a technique based on dynamic time warping which carries out the recognition by calculating distances to an average template extracted from several training instances. Finally, a permanence analysis has been carried out in order to assess the stability of in-air signature over time.

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Section: Introductionmentioning

confidence: 99%

Analysis of pattern recognition techniques for in-air signature biometrics

Bailador

Ávila

Guerra-Casanova

et al. 2011

Pattern Recognition

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“…Gabor filters has been extensively studied in the literature to extract texture features from biometrics like fingerprint (Chin et al, 2009), palmprint recognition (Zheng and Sang, 2009;Huang et al, 2009), etc. The advantage with Gabor filters for palmprint is that, the extracted texture information includes principal lines, wrinkles, ridges, etc.…”

Section: D Gabor Filtermentioning

confidence: 99%

“…2D log-Gabor filter has been extensively studied to extract the texture features (Fan et al, 2008;Chin et al, 2009). It has the following form,…”

Section: D Log-gabor Filtermentioning

confidence: 99%

Intramodal palmprint recognition using texture feature

Latha¹,

Prasad²

2017

IJISDC

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Palmprint technology is a new branch of biometrics used to identify an individual. Palmprint has rich set of features like palm lines, wrinkles, minutiae points, texture, ridges, etc. Several line and texture extraction techniques for palmprint have been extensively studied. This paper presents an intramodal authentication system based on texture information extracted from the palmprint using the Haralick features, 2D-Gabor and 2D-log Gabor filters. An individual feature vector is computed for a palmprint using the extracted texture information of each filter type. Performance of the system using three feature types is evaluated individually. Finally, we combine the three feature types using feature level fusion to develop an intramodal palmprint recognition system. The experiments are evaluated on a standard benchmark database (PolyU Database), and the results shows that significant improvement in terms of recognition accuracy and error rates with the proposed intramodal recognition system compared to individual representations.

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“…Further, the computat from the extracted texture and matching of the palmpr discussed in section 3. Section 4 describes the propo riments and results from this work are presented in Sect ed in section 6. tion ensively studied in the literature to extract texture featu rprint [4], Palmprint recognition [5][6], etc. The advant mprint is that, the extracted texture information inclu dges, etc.…”

Section: D Gabor Filtermentioning

confidence: 99%

Palmprint Recognition Using Fusion of 2D-Gabor and 2D Log-Gabor Features

Prasad

Kavati

Adinarayana

2014

Communications in Computer and Information Science

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Abstract. Palmprint technology is a new branch of biometrics used to identify an individual. Palmprint has rich set of features like palm lines, wrinkles, minutiae points, texture, ridges etc. Several line and texture extraction techniques for palmprint have been extensively studied. This paper presents an intra-modal authentication system based on texture information extracted from the palmprint using the 2D-Gabor and 2D-Log Gabor filters. An individual feature vector is computed for a palmprint using the extracted texture information of each filter type. Performance of the system using two feature types is evaluated individually. Finally, we combine the two feature types using feature level fusion to develop an intra-modal palmprint recognition system. The experiments are evaluated on a standard benchmark database (PolyU Database), and the results shows that significant improvement in terms of recognition accuracy and error rates with the proposed intra-modal recognition system compared to individual representations.

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Integrating Palmprint and Fingerprint for Identity Verification

Cited by 24 publications

References 9 publications

Analysis of pattern recognition techniques for in-air signature biometrics

Analysis of pattern recognition techniques for in-air signature biometrics

Intramodal palmprint recognition using texture feature

Palmprint Recognition Using Fusion of 2D-Gabor and 2D Log-Gabor Features

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