Finger-knuckle-print: a new biometric identifier (2009)

by L Zhang, L Zhang, D Zhang
Venue:In Proc. IEEE Int. Conf. Image Process
Add To MetaCart
Results 1 - 10 of 17

Finger knuckleprint based recognition system using feature tracking

by G S Badrinath, Aditya Nigam, Phalguni Gupta - In Chinese Conference on Biometric Recognition (CCBR , 2011
"... Abstract. This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and rotation. The non-uniform brightness of the FKP due to relatively curvature surface is corrected and texture is enhanced. The ..."
Abstract - Cited by 11 (4 self) - Add to MetaCart
Abstract. This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and rotation. The non-uniform brightness of the FKP due to relatively curvature surface is corrected and texture is enhanced. The local features of the enhanced FKP are extracted using the scale invariant feature transform (SIFT) and the speeded up robust features (SURF). Corresponding features of the enrolled and the query FKPs are matched using nearest-neighbour-ratio method and then the derived SIFT and SURF matching scores are fused using weighted sum rule. The proposed system is evaluated using PolyU FKP database of 7920 images for both identification mode and verification mode. It is observed that the system performs with CRR of 100 % and EER of 0.215%. Further, it is evaluated against various scales and rotations of the query image and is found to be robust for query images downscaled upto 60 % and for any orientation of query image. 1
(Show Context)

Pattern Recognition

by Javier Galbally A, Chris Mccool B, Julian Fierrez A, Sebastien Marcel B, Javier Ortega-garcia A
"... This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or sel ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit:

On continuous user authentication via typing behavior

by Joseph Roth, Student Member, Xiaoming Liu, Dimitris Metaxas - IEEE Trans. Image Process , 2014
"... Abstract—We hypothesize that an individual computer user has a unique and consistent habitual pattern of hand movements, independent of the text, while typing on a keyboard. As a result, this paper proposes a novel biometric modality named “Typing Behavior (TB) ” for continuous user authentication. ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract—We hypothesize that an individual computer user has a unique and consistent habitual pattern of hand movements, independent of the text, while typing on a keyboard. As a result, this paper proposes a novel biometric modality named “Typing Behavior (TB) ” for continuous user authentication. Given a webcam pointing toward a keyboard, we develop real-time computer vision algorithms to automatically extract hand movement patterns from the video stream. Unlike the typical continuous biometrics such as keystroke dynamics (KD), TB provides reliable authentication with a short delay, while avoiding explicit key-logging. We collect a video database where 63 unique subjects type static text and free text for multiple sessions. For one typing video, the hands are segmented in each frame and a unique descriptor is extracted based on the shape and position of hands, as well as their temporal dynamics in the video sequence. We propose a novel approach, named bag of multi-dimensional phrases, to match the cross-feature and cross-temporal pattern between a gallery sequence and a probe sequence. The experimental results demonstrate superior performance of TB when compared to KD, which, together with our ultra-real-time demo system, warrant further investigation of this novel vision application and biometric modality. Index Terms—Continuous authentication, user authentication, biometrics, typing behavior, hand movements, bag of phrases, bag of multi-dimensional phrases, keystroke dynamics, keyboard. I.
(Show Context)

Reconstruction based Finger-Knuckle-Print Verification with Score Level Adaptive Binary Fusion

by Guangwei Gao , Lei Zhang , Jian Yang , Lin Zhang , David Zhang , 2013
"... Recently a new biometrics identifier, namely finger knuckle print (FKP), has been proposed for personal authentication with very interesting results. One of the advantages of FKP verification lies in its user friendliness in data collection. However, the user flexibility in positioning fingers also ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Recently a new biometrics identifier, namely finger knuckle print (FKP), has been proposed for personal authentication with very interesting results. One of the advantages of FKP verification lies in its user friendliness in data collection. However, the user flexibility in positioning fingers also leads to certain degree of pose variations in the collected query FKP images. The widely used Gabor filtering based Competitive Coding scheme is sensitive to such variations, resulting in many false rejections. We propose to alleviate this problem by reconstructing the query sample with a dictionary learned from the template samples in the gallery set. The reconstructed FKP image can reduce much the enlarged matching distance caused by finger pose variations; however, both the intra-class and inter-class distances will be reduced. We then propose a score level adaptive binary fusion rule to adaptively fuse the matching distances before and after reconstruction, aiming to reduce the false rejections without increasing much the false acceptances. Experimental results on the benchmark PolyU FKP database show that the proposed method significantly improves the FKP verification accuracy.
(Show Context)

Personal Recognition by Finger-Knuckle-Print Based on Log-Gabor Filter Response

by Abdallah Meraoumia, Salim Chitroub, Ahmed Bouridane
"... Abstract—Biometrics technique is an important and effective solution for automatic personal verification/identification. Re-cently, a novel hand-based biometric feature, Finger-Knuckle-Print (FKP), has attracted an increasing amount of attention. Like any other biometric identifiers, FKPs are believ ..."
Abstract - Add to MetaCart
Abstract—Biometrics technique is an important and effective solution for automatic personal verification/identification. Re-cently, a novel hand-based biometric feature, Finger-Knuckle-Print (FKP), has attracted an increasing amount of attention. Like any other biometric identifiers, FKPs are believed to have the critical properties of universality, uniqueness and permanence for personal recognition. This paper investigates a new approach for human FKP recognition using 1D Log-Gabor filter response. We employ 1D Log-Gabor wavelet to extract the information. Thus each finger is represented by a two finger codes (real and imaginary template). Those templates (finger codes) are compared with those in the database using Hamming distance. The experimental results showed that the designed system achieves an excellent recognition rate on the Hong Kong polytechnic university (PolyU) Finger-Knuckle-Print Database. The proposed technique is computationally effective with recognition rates of 99.71 % and 99.91 % for verification and identification, respectively.
(Show Context)

Egyptian Armed Forces

by Ola M. Aly, Gouda I. Salama, Tarek A. Mahmoud
"... Abstract—Multimodal biometric systems which fuse information from a number of biometrics, are gaining more attentions lately because they are able to overcome limitations in unimodal biometric systems. These systems are suited for high security applications. Most of the proposed multibiometric syste ..."
Abstract - Add to MetaCart
Abstract—Multimodal biometric systems which fuse information from a number of biometrics, are gaining more attentions lately because they are able to overcome limitations in unimodal biometric systems. These systems are suited for high security applications. Most of the proposed multibiometric systems offer one level of security. In this paper a new approach for adaptive combination of multiple biometrics has been proposed to ensure multiple levels of security. The score level fusion rule is adapted using (PSO) Particle Swarm Optimization to ensure the desired system performance corresponding to the desired level of security. The experimental results prove that the proposed multimodal biometric system is appropriate for applications that require different levels of security. Keywords—multibiometric; match score fusion; PSO; Irsi; Palmprint; Finger_Knuckle I.
(Show Context)

Finger-Knuckle-Print Based Recognition System using LBP and SURF

by Salil Kumar Verma, Maitreyee Dutta
"... Abstract — Finger knuckle bending produces a highly unique texture pattern and it can be used as a distinctive biometric identifier. This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and r ..."
Abstract - Add to MetaCart
Abstract — Finger knuckle bending produces a highly unique texture pattern and it can be used as a distinctive biometric identifier. This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and rotation. The non-uniform brightness of the FKP due to relatively curvature surface is corrected and texture is enhanced. The local features of the enhanced FKP are extracted using the LBP histogram and the speeded up robust features (SURF). Corresponding features of the enrolled and the query FKPs are matched using nearest-neighbour-ratio method and then the derived LBP and SURF matching scores are fused using weighted sum rule. The proposed system has been evaluated using PolyU FKP database of 7920 images for both identification mode and verification mode.Its parameters have been tuned to get optimum performance. LBP histograms was used for texture feature extraction of a FKP image. SURF has made the system robust against scale and rotation.

A HYBRID MODEL FOR HUMAN RECOGNITION SYSTEM USING HAND DORSUM GEOMETRY AND FINGER-KNUCKLE- PRINT

by B. Mathivanan, V. Palanisamy, S. Selvarajan
"... This study focuses on developing an efficient person identification and recognition system using hand based biometrics for secured access control. In most of the previous works on hand-based recognition methods, mostly, the importance was not given to the top side of the hand, which is used in this ..."
Abstract - Add to MetaCart
This study focuses on developing an efficient person identification and recognition system using hand based biometrics for secured access control. In most of the previous works on hand-based recognition methods, mostly, the importance was not given to the top side of the hand, which is used in this model. Iin our previous work we have developed a Hand based biometric recognition system using the palm side of the hand. In which, all features were extracted only from the palm side of the hand. Also, in some of the earlier works, the palm side of the hand was used for recognition purpose. The reason behind the selection of palm side of the hand is, it is very easy to capture using a simple scanning device and we can extract the shape based features as well as the palm print from the same image. In this study, we address a new hybrid model for biometrics based human recognition system using the dorsum of hand and the finger knuckle print. Dorsum of hand (backside of hand or topside of hand) is the opposite side of the palm side of the hand. In this study, we highlight some of the advantages of using dorsum of hand for modeling a biometrics based human recognition system. This study proposes a new hybrid model biometric system using Dorsum of Hand. Both the finger knuckle print and hand shape features are proposed to be extracted from the single hand image acquired from a top mounted camera setup. We use some unique features that improve the

An Efficient Hand Image Segmentation Algorithm for Hand Geometry based Biometrics Recognition System

by B. Mathivanan, Dr. V. Palanisamy, Dr. S. Selvarajan, Namakkal Rasipuram
"... In most of the previous works on hand-based recognition methods, mostly, the significance was not given to the side of the hand, which is used in the model. The palm side of the hand is generally used because, it is very easy to capture using a simple scanning device and we can extract the shape bas ..."
Abstract - Add to MetaCart
In most of the previous works on hand-based recognition methods, mostly, the significance was not given to the side of the hand, which is used in the model. The palm side of the hand is generally used because, it is very easy to capture using a simple scanning device and we can extract the shape based features as well as the palm print from the same image. Dorsum of hand (backside of hand or topside of hand) is the apposite side of the palm side of the hand. In this work, we highlight some of the advantages of using dorsum of hand for modeling a biometrics based human recognition system. Segmenting the hand image is the most important step in any hand geometry based recognition systems. We realized that the segmentation algorithm used for segmenting the palm side of the hand will not be suitable for segmenting the dorsum of hand. In this paper, we address a simple and fast method for segmenting the dorsum of hand image. The proposed method can be used in hand geometry based recognition algorithms which use the dorsum of hand as the input.

Geometric Finger Nail Matching using Fuzzy Measures

by Kavitha Jaba Malar R, Joseph Raj V
"... Abstract — This paper proposes a novel method, a Fuzzy Feature Match (FFM) based on a triangle feature set to match the fingernail. The fingernail is represented by the fuzzy feature set. The fuzzy features set similarity is used to analyze the similarity among fingerprints. Accordingly, a similarit ..."
Abstract - Add to MetaCart
Abstract — This paper proposes a novel method, a Fuzzy Feature Match (FFM) based on a triangle feature set to match the fingernail. The fingernail is represented by the fuzzy feature set. The fuzzy features set similarity is used to analyze the similarity among fingerprints. Accordingly, a similarity vector pair is defined to illustrate the similarities between two fingernails. The FFM method shows the similarity vector pair to a normalized value which quantifies the overall image to image similarity. The algorithm has been evaluated with kaniyakumari district people’s fingernail database. Experimental results confirm that the proposed FFM based on the triangle feature set is a reliable and effective algorithm for fingernail matching.