Biometric recognition using fuzzy score level fusion

Multi-modal biometric recognition uses more than one biometric identifier to recognise a person. Identification based on multiple templates becomes an emerging need. Multi-modal biometric systems are expected to be more reliable due to the presence of multiple independent pieces of biometric traits. This paper proposes a new approach for biometric recognition using hand vein and finger vein images. Our proposed method employs hyper analytic wavelet transform and automatic thresholding techniques to extract features from the images of hand. Once the veins are extracted the location and width are stored in the database. Here score level fusion based on fuzzy logic is utilised for recognition. This approach is tested on the finger vein and hand vein databases which is containing 500 samples from 100 users. The experimental results exhibits that the proposed method is comparable with the existing recognising methods.

[1]  L M Patnaik,et al.  Authentication of damaged hand vein patterns by modularization , 2009, TENCON 2009 - 2009 IEEE Region 10 Conference.

[2]  Yiding Wang,et al.  Hand-dorsa vein recognition based on partition Local Binary Pattern , 2010, IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS.

[3]  Hatim Aboalsamh.  Vein and Fingerprint Biometrics Authentication- Future Trends , 2009 .

[4]  Naoto Miura,et al.  Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles , 2007, MVA.

[5]  Naoto Miura,et al.  Feature Extraction of Finger-vein Patterns Based on Repeated Line Tracking and Its Application to Personal Identification , 2022 .

[6]  Jinfeng Yang,et al.  Finger-vein ROI localization and vein ridge enhancement , 2012, Pattern Recognit. Lett..

[7]  Bulent Sankur,et al.  Biometric Identification through Hand Vein Patterns , 2010, 2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics.

[8]  Xiaodong Gu,et al.  Palm-Dorsal Vein Recognition Method Based on Histogram of Local Gabor Phase XOR Pattern with Second Identification , 2013, J. Signal Process. Syst..

[9]  Slobodan Ribaric,et al.  A biometric identification system based on eigenpalm and eigenfinger features , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Ramachandra Raghavendra,et al.  Multimodal Biometrics: Analysis of Handvein & Palmprint Combination Used for Person Verification , 2010, 2010 3rd International Conference on Emerging Trends in Engineering and Technology.

[11]  Sepehr Damavandinejadmonfared,et al.  Finger Vein Recognition using PCA-based Methods , 2012 .

[12]  Miguel A. Ferrer,et al.  Combining hand biometric traits for personal identification , 2009, 43rd Annual 2009 International Carnahan Conference on Security Technology.

[13]  Arun Ross,et al.  Multimodal biometrics: An overview , 2004, 2004 12th European Signal Processing Conference.

[14]  Wenxin Li,et al.  Finger-Vein Authentication Based on Wide Line Detector and Pattern Normalization , 2010, 2010 20th International Conference on Pattern Recognition.

[15]  J.-M. Boucher,et al.  A New Implementation of the Hyperanalytic Wavelet Transform , 2007, 2007 International Symposium on Signals, Circuits and Systems.

[16]  Xukai Zou,et al.  Biometrics-Based Authentication: A New Approach , 2011, 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN).

[17]  San-yuan Zhang,et al.  Multimodal biometric identification system based on finger geometry, knuckle print and palm print , 2010, Pattern Recognit. Lett..

[18]  Thomas B. Moeslund,et al.  Low-Cost Hand Vein Pattern Recognition , 2011 .

[19]  D. Mulyono,et al.  A study of finger vein biometric for personal identification , 2008, 2008 International Symposium on Biometrics and Security Technologies.

[20]  Jian-Da Wu,et al.  Finger-vein pattern identification using SVM and neural network technique , 2011, Expert Syst. Appl..

[21]  Eui Chul Lee,et al.  New Finger Biometric Method Using Near Infrared Imaging , 2011, Sensors.

[22]  Jian-Da Wu,et al.  Finger-vein pattern identification using principal component analysis and the neural network technique , 2011, Expert Syst. Appl..

[23]  Xue Yuan.  Biometric verification using hand vein-patterns , 2010, 2010 IEEE International Conference on Wireless Communications, Networking and Information Security.

[24]  Naoto Miura,et al.  Automatic Feature Extraction from non-uniform Finger Vein Image and its Application to Personal Identification , 2002, MVA.

[25]  Qiang Li,et al.  Feature-Level Fusion of Hand Biometrics for Personal Verification Based on Kernel PCA , 2006, ICB.

[26]  Bulent Sankur,et al.  Hand vein biometry based on geometry and appearance methods , 2011 .

[27]  Miguel A. Ferrer,et al.  Automatic biometric identification system by hand geometry , 2003, IEEE 37th Annual 2003 International Carnahan Conference onSecurity Technology, 2003. Proceedings..

[28]  David Zhang,et al.  A Unified Framework for Contactless Hand Verification , 2011, IEEE Transactions on Information Forensics and Security.

[29]  R. K. Subramanian,et al.  Representation of Hand Dorsal Vein Features Using a Low Dimensional Representation Integrating Cholesky Decomposition , 2009, 2009 2nd International Congress on Image and Signal Processing.

[30]  Chin-Chuan Han.  A hand-based personal authentication using a coarse-to-fine strategy , 2004, Image Vis. Comput..