Multimodal Biometric Identification system using Random Selection of Biometrics

International Journal of Electrical and Electronics Engineering
© 2023 by SSRG - IJEEE Journal
Volume 10 Issue 1
Year of Publication : 2023
Authors : Sampada Abhijit Dhole, Jayamala Kumar Patil, S. M. Jagdale, H. G. Govardhana Reddy, V. Dankan Gowda
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Sampada Abhijit Dhole, Jayamala Kumar Patil, S. M. Jagdale, H. G. Govardhana Reddy, V. Dankan Gowda, "Multimodal Biometric Identification system using Random Selection of Biometrics," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 1, pp. 63-73, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I1P106

Abstract:

Biometric systems employ their biometric features to identify people. Identification systems that solely employ one biometric modality would not be able to meet the demands of demanding biometric applications in terms of performance, acceptance, and uniqueness. The majority of unimodal biometrics systems have problems with concentrated data noise, variances within and across classes, non-universality, etc. Multimodal biometric systems, which may establish identity from many sources of information, can bypass some of these restrictions. Identifying a person using multimodal biometric technology is more accurate and dependable. Early integration tactics are anticipated to perform better than late integration strategies. In this paper, feature-level fusion using the random selection of biometrics is presented. Block variance features and contourlet transform features are used to carry out the feature-level fusion. LDA is used to reduce the feature vector's dimensions. When compared to alternative integration approaches and their unimodal cousin, integrating the contourlet transform features of two independently determined biometric qualities delivers a consistent gain in performance accuracy. In this work, we use a random selection of biometric traits to guarantee the presence of a real human being at the time of data collection. Only fingerprints, palm prints, and faces will be included in the random selection.

Keywords:

Hand geometry, Contourlet transform, Multimodal, Feature level fusion, Biometric.

References:

[1] Anil K. Jain, Arun ross, and Salil prabhakar, “An Introduction to Biometric Recognition,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, pp. 4 – 20, 2004. Crossref, https://doi.org/10.1109/TCSVT.2003.818349
[2] Ashish Mishra, “Multimodal Biometrics It Is: Need for Future Systems,” International Journal of Computer Applications, vol. 3, no. 4, pp. 28-33
[3] Ms.P.Jennifer, and Dr. A. Muthu Kumaravel, "An Iris Based Authentication System by Eye Localization,” International Journal of Biotech Trends and Technology (IJBTT), vol. 3, no. 4, pp. 9-12, 2013.
[4] Karki Maya, and Sethuselvis, “Multimodal Biometrics at Feature Level Fusion Using Texture Features,” International Journal of Biometrics and Bioinformatics (IJBB), vol. 7, no. 1, pp. 58-73, 2013.
[5] M. Arunkumar, and S. Valarmathy, “Palmprint and Face Based Multimodal Recognition Using PCO Dependent Feature Level Fusion,” Journal of Theoretical and Applied Information Technology, vol. 57, no. 3, pp. 337-346, 2013.
[6] Pooja G Nair, and Sneha R, "A Review: Facial Recognition Using Machine Learning," International Journal of Recent Engineering Science vol. 7, no. 3, pp. 85-89, 2020. Crossref, https://doi.org/10.14445/23497157/IJRES-V7I3P115
[7] Sneha A. Taksande, and Pushpanjali M. Chouragade, “Fusion Based Multimodal Biometrics Using Face and Palm Print at Various Levels,” International Journal of Scientific & Engineering Research, vol. 7, no. 2, pp. 106-109, 2016.
[8] Arun Jain, Surenderjangra, and Mehzabeenkaur, “Multimodal Biometric Identification Using Face and Palmprint,” International Journal of Advanced Research in Computer Science and Software Engineering, vol. 7, no. 5, pp. 11401144, 2017.
[9] Kalpana Chauhan, and Mrs. Mamta Yadav, "Automated Multi Face Identification,” International Journal of Computer & Organization Trends, vol. 7, no. 5, pp. 5-7, 2017.
[10] Praveen Kumarnayak, and Devesh narayan, “Multimodal Biometric Face and Fingerprint Recognition Using Adaptive Principal Component Analysis and Multilayer Perception,” International Journal of Research in Computer and Communication Technology, vol. 2, no. 6, pp. 313-321, 2013. 
[11] Shiraz Anwar, and Surinder, “Multimodal Biometrics Identification Using Face and Palm-Print,” International Journal of Advanced Research in Engineering Technology & Science, vol. 4, no. 5, pp. 45-50, 2017.
[12] Raman Kumar, and Satnam Singh, "Face Recognition Using Principle Component Analysis for Biometric Security System,” International Journal of Computer & Organization Trends, vol. 3, no. 4, pp. 38-40, 2013.
[13] V Dankan Gowda, “Signal Analysis and Filtering Using One Dimensional Hilbert Transform,” Journal of Physics: Conference Series, vol. 1706, no. 1, 2020. Crossref, https://doi.org/10.1088/1742-6596/1706/1/012107
[14] Avinash Sharma et al., "Extraction of Fetal ECG Using ANFIS and the Undecimated-Wavelet Transform," 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT), 2022, pp. 1-5, Crossref, https://doi.org/10.1109/GCAT55367.2022.9972078
[15] Utkarsh Chouhan, and H N Verma, "Blood Vessel Segmentation for IRIS in Unconstrained Environments Using Moment Method," SSRG International Journal of Computer Science and Engineering, vol. 5, no. 8, pp. 8-14, 2018. Crossref, https://doi.org/10.14445/23488387/IJCSE-V5I8P103
[16] Navdeep, and Surinder, “A Novel Multi-Model Biometric Fusion Approach Using Palm-Print & Face Biometric,” International Journal of Latest Trends in Engineering and Technology, vol. 8, no. 3, pp. 240-247, 2017.
[17] Varsha H. Patil et al., “An Efficient Secure Multimodal Biometric Fusion Using Palm Print and Face Image,” International Journal of Applied Engineering Research, vol. 11, no. 10, pp.7147-7150, 2016.
[18] Deepak Singh, and Mr. Mohan Rao Mamdikar, "Identify a Person From Iris Pattern Using GLCM Features and Machine Learning Techniques," SSRG International Journal of Computer Science and Engineering, vol. 7, no. 9, pp. 25-29, 2020. Crossref, https://doi.org/10.14445/23488387/IJCSE-V7I9P105
[19] Ranjeet Suryawanshi et al., “Enhanced Diagnostic Methods for Identifying Anomalies in Imaging of Skin Lesions,” International Journal of Electrical and Electronics Research (IJEER), vol. 10, no. 4, pp. 1077-1085, 2022. Crossref, https://doi.org/10.37391/IJEER.100452
[20] Avinash Sharma et al., “Vector Space Modelling-Based Intelligent Binary Image Encryption for Secure Communication,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 25, no. 4, pp. 1157-1171, 2022. Crossref, https://doi.org/10.1080/09720529.2022.2075090
[21] Gatheejathul Kubra.J, and Rajesh.P, "Iris Recognition and Its Protection Overtone Using Cryptographic Hash Function," SSRG International Journal of Computer Science and Engineering, vol. 3, no. 5, pp. 1-9, 2016. Crossref, https://doi.org/10.14445/23488387/IJCSE-V3I5P101
[22] K. Tripathi, “A Comparative Study of Biometric Technologies With Reference to Human Interface,” International Journal of Computer Applications, vol. 14, no. 5, pp. 10–15, 2011. Crossref, https://doi.org/10.5120/1842-2493
[23] Aarti Hemant Tirmare et al., “A Morphological Change in Leaves-Based Image Processing Approach for Detecting Plant Diseases,” International Journal of Electrical and Electronics Research (IJEER), vol. 10, no. 4, pp. 1013-1020, 2022. Crossref, https://doi.org/10.37391/IJEER.100443.
[24] Opeyemi Oyelesi, and Akingbade Kayode Francis, "Face Recognition for Access Control Using PCA Algorithm," SSRG International Journal of VLSI & Signal Processing, vol. 4, no. 2, pp. 22-27, 2017. Crossref, https://doi.org/10.14445/23942584/IJVSP-V4I3P105
[25] R. Gagan, and S. Lalitha, “Elliptical Sector Based DCT Feature Extraction for Iris Recognition,” 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), pp. 1–5, 2020. Crossref, https://doi.org/10.1109/ICECCT.2015.7226026
[26] Ajay. P et al., "Intelligent Breast Abnormality Framework for Detection and Evaluation of Breast Abnormal Parameters," 2022 International Conference on Edge Computing and Applications (ICECAA), 2022, pp. 1503-1508, Crossref, https://doi.org/10.1109/ICECAA55415.2022.9936206.
[27] Anamika Baradiya, and Vinay Jain, "Speech and Speaker Recognition Technology Using MFCC and SVM," SSRG International Journal of Electronics and Communication Engineering, vol. 2, no. 5, pp. 6-9, 2015. Crossref, https://doi.org/10.14445/23488549/IJECE-V2I5P105
[28] R. S. Gejji et al., “Understanding the Subject-Specific Effects of Pupil Dilation on Iris Recognition in the NIR Spectrum,” 2015 IEEE International Symposium on Technologies for Homeland Security (HST), pp. 1–6, 2015. Crossref, https://doi.org/10.1109/THS.2015.7225317
[29] DankanGowda V et al., “A Novel Method of Data Compression Using ROI for Biomedical 2D Images,” Measurement: Sensors, vol. 24, 2022, Crossref, https://doi.org/10.1016/j.measen.2022.100439
[30] Anjali Soni, and Prashant Jain, "Iris Recognition Using Four Level HAAR Wavelet Transform: A Literature Review," SSRG International Journal of Electronics and Communication Engineering, vol. 3, no. 6, pp. 14-18, 2016. Crossref, https://doi.org/10.14445/23488549/IJECE-V3I6P106
[31] Madhavi Gudavalli et al., “Multimodal Biometrics-Sources, Architecture and Fusion Techniques: An Overview,” 2012 International Symposium on Biometrics and Security Technologies, pp. 27–34, 2012. Crossref, https://doi.org/10.1109/ISBAST.2012.24
[32] Fabio Calefato et al., “Mobile Speech Translation for Multilingual Requirements Meetings: A Preliminary Study,” 2014 IEEE 9th International Conference on Global Software Engineering, pp. 145–152, 2014. Crossref, https://doi.org/10.1109/ICGSE.2014.10
[33] Zeng Wei et al., “A New Inertial Sensorbased Gait Recognition Method via Deterministic Learning,” 2015 34th Chinese Control Conference (CCC), pp. 3908–3913, 2019. Crossref, https://doi.org/10.1109/ChiCC.2015.7260243
[34] Mohamad El-Abed et al., “A Study of Users’ Acceptance Satisfaction Biometric Systems,” 44th Annual 2010 IEEE International Carnahan Conference on Security Technology, 2010. Crossref, https://doi.org/10.1109/CCST.2010.5678678
[35] Saiyed Umer, Bibhas Chandra Dhara, and Bhabatosh Chanda, “Face Recognition Using Fusion of Feature Learning Techniques,” Measurement, vol. 146, pp. 43–54, 2019. Crossref, https://doi.org/10.1016/j.measurement.2019.06.008