A Biometric Fusion System of Face and Fingerprint for Enhanced Human Identification Using HOG-LBP Approach
Keywords:
Histogram of gradients, local Binary pattern, face and fingerprint fusion
Abstract
This paper presents a biometric fusion system of fingerprint and face images for Ergonomic-Based Enrolment and
Verification System. Features from fingerprints and faces are extracted to create a new biometric template with
enhanced performance and with an extra level of assurance for identification. A fusion scheme combines the
extracted Histogram of gradients (HOG) and local Binary Pattern (LBP) features from a subject’s fingerprint and face
images. Manhattan Distance is used to compare between the template in the database and the input data. The
difference between the database template and the input data determines the decision either to reject or accept.
Different "matching score thresholds" were set to evaluate the relationship between False Rejection Ratio and False
Acceptance Ratio which is a common measure to determine system performance level. From the experiments and
based on the characteristic nature of this HOG-LBP algorithm, a threshold between 75% and 80% is determined to
be moderate and close to the EER (Equal Error Rate) point, which is the intersection of the False Accept Rate (FAR)
and False Reject Rate (FRR). The system is robust enough to accommodate an increase in the threshold if a high level
of system confidence is required
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Rattani, A., Kisku, D. R., Bicego, M. and Tistarelli, M. (2007) "Feature Level Fusion of Face and Fingerprint
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Subbarayudu, V., Prasad, M. (2008). Multimodal Biometric System. In Emerging Trends in Engineering and
Technology. ICETET'08. First International Conference on (pp. 635-640). IEEE.
Taouche, C., Batouche, M. C., Berkane, M., Taleb-Ahmed, A. (2014). Multimodal biometric systems. In 2014
International Conference on Multimedia Computing and Systems (ICMCS) (pp. 301-308). IEEE.
Viola, P., Jones, M. (2001). Rapid object detection using a boosted cascade of simple features.
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CVPR 2001 (Vol. 1, pp. I-I). IEEE
Wayman, J., Jain, A., Maltoni, D., Maio, D. (2005). An introduction to biometric authentication systems.
In Biometric Systems (pp. 1-20). Springer, London.
society conference on computer vision and pattern recognition (cvpr'05) (vol. 1, pp. 886-893). IEEE.
Dhameliya, M. D., Chaudhari, J. P. (2013). A multimodal biometric recognition system based on fusion of
palmprint and fingerprint. International journal of Engineering trends and technology, 4(5), 1908-1911.
Fei L., Zhang B., Jia W., J. Wen and Zhang D (2020), "Feature Extraction for 3-D Palmprint Recognition:
A Survey," in IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 3, pp. 645-656.
Gupta, K., Walia, G.S., Sharma, K. (2020) Quality based adaptive score fusion approach for multimodal biometric
system. Appl Intell 50, 1086–1099.
Hicklin, A., Ulery, B., Watson, C. (2006). A brief introduction to biometric fusion. Study, Department of the Interior,
National Institute of Standards and Technology, Washington: NIST.
Jagadeesan, A., Duraiswamy, K. (2010). Secured cryptographic key generation from multimodal biometrics:
feature level fusion of fingerprint and iris. arXiv preprint arXiv:1003.1458.
Jain, A. K., Hong, L., Kulkarni, Y. (1999). A multimodal biometric system using fingerprint, face and
speech. In 2nd Int'l Conf. AVBPA (Vol. 10).
Kabir W., Ahmad M. O. and Swamy M. N. S (2018, August) "Normalization and Weighting Techniques Based on
Genuine-Impostor Score Fusion in Multi-Biometric Systems," in IEEE Transactions on Information Forensics
and Security, vol. 13, no. 8, pp. 1989-2000.
Lahane, P. U., Ganorkar, S. R. (2012). Fusion of Iris & Fingerprint Biometric for Security Purpose. International
Journal of Scientific & Engineering Research, 3(8), 1-5.
Lee, T. Z., Bong, D. B. (2016). Face and palmprint multimodal biometric system based on bit-plane
decomposition approach. In 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCETW) (pp. 1-2). IEEE.
Monwar, M. M., Gavrilova, M. L. (2009). Multimodal biometric system using rank-level fusion approach. IEEE
Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39(4), 867-878.
Nagaraja, S., Prabhakar, C. J. (2015). Low-level features for image retrieval based on extraction of directional
binary patterns and its oriented gradients histogram. Computer Applications: An International Journal
(CAIJ), 2(1).
Ojala, T., Pietikainen, M., Harwood, D. (1996). A comparative study of texture measures with classification based
on featured distributions. Pattern recognition, 29(1), 51-59.
Panchal, T., Singh, A. (2013). Multimodal biometric system. International Journal of Advanced Research in
Computer Science and Software Engineering, 3(5), 1360-1363.
Rahman M. Z., Rahman M. H. H and Majumdar M. M. R, (2019) "Distinguishing a Person by Face and Iris Using Fusion
Approach," 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka,
Bangladesh, pp. 1-5
Rane M. E. and. Deshpande P. P, (2018) "Multimodal Biometric Recognition System Using Feature Level Fusion,"
2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA),
Pune, India, pp. 1-5.
Rattani, A., Kisku, D. R., Bicego, M. and Tistarelli, M. (2007) "Feature Level Fusion of Face and Fingerprint
Biometrics," 2007 First IEEE International Conference on Biometrics: Theory, Applications,
and Systems, Crystal City, VA, pp. 1-6,
Ross, A., Jain, A. K. (2004). Multimodal Biometrics: an overview. In 2004 12th European Signal
Processing Conference (pp. 1221-1224). IEEE.
Sepasian, M., Balachandran, W., Mares, C. (2008). Image enhancement for fingerprint minutiae- based
algorithms using CLAHE, standard deviation analysis and sliding neighborhood. In Proceedings of the World
congress on Engineering and Computer Science (pp. 22-24).
Subbarayudu, V., Prasad, M. (2008). Multimodal Biometric System. In Emerging Trends in Engineering and
Technology. ICETET'08. First International Conference on (pp. 635-640). IEEE.
Taouche, C., Batouche, M. C., Berkane, M., Taleb-Ahmed, A. (2014). Multimodal biometric systems. In 2014
International Conference on Multimedia Computing and Systems (ICMCS) (pp. 301-308). IEEE.
Viola, P., Jones, M. (2001). Rapid object detection using a boosted cascade of simple features.
In Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition.
CVPR 2001 (Vol. 1, pp. I-I). IEEE
Wayman, J., Jain, A., Maltoni, D., Maio, D. (2005). An introduction to biometric authentication systems.
In Biometric Systems (pp. 1-20). Springer, London.
Published
2020-07-27
How to Cite
Popoola, O., & Lasisi, R. (2020). A Biometric Fusion System of Face and Fingerprint for Enhanced Human Identification Using HOG-LBP Approach. Journal of Engineering Research, 25(2), 197-202. Retrieved from http://jer.unilag.edu.ng/article/view/1002
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