ICTACT Journal on Image and Video Processing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

CMBA- A Candid Multi-purpose Biometric Approach


Affiliations
1 Department of Computer Science, Muhammad Nawaz Sharif University of Engineering and Technology, Pakistan
2 College of Internet of Things Engineering, Hohai University, Changzhou Campus, China
     

   Subscribe/Renew Journal


All humans are born with unique physically identified body characteristics to other persons which remains unchanged throughout life. These characteristics are taken into account by the emerging technology to get recognized from person to person. The technology used by the traditional human identification system sometimes becomes inefficient when data or images received are not up to the acceptable quality mark or when a person has a face covered with mask-like during epidemic virus fistula. In order to overcome the human recognition challenges, a Candid Multi-purpose Biometric Approach (CMBA) has been proposed which can make human identification easier and approachable. The CMBA human recognition approach uses two uniquely identified modalities such as foot and iris. This approach shrewdly identifies and makes the bodacious recognition among humans and suggests the sagacious result which is foremost better than the traditional biometric system. The CMBA is offering opportunity to take more than two biometric features, by combining them to overcome unimodal biometric system limitations and to achieve optimal results. Using sagacious edge detector and Hough transformation technique, the Iris and foot part are segmented into easy and quick extraction voting system which produce succulent output. In fact, this technique is new in biometric identification era.

Keywords

Biometric System, Face Recognition, Modalities, Face Mask.
Subscription Login to verify subscription
User
Notifications
Font Size

  • A. Melamed, “2018 Biometric Predictions: Advanced Biometric Technologies Take Off”, Available at: https://www.biometricupdate.com/201801/2018-biometric-predictions-advanced-biometric-technologies-take-off, Accessed at 2018.

  • M2SYS, “False Rejection Rate,” Available at: https://www.m2sys.com/blog/important-biometric-terms-to-know/false-rejection-rate-what-does-it-mean-and-why-should-i-care/, Accessed at 2018.

  • S. Ashraf, S. Saleem and T. Ahmed, “Sagacious Communication Link Selection Mechanism for Underwater Wireless Sensors Network”, International Journal of Wireless and Microwave Technologies, Vol. 10, No. 4, pp. 22-33, 2020.

  • S. Ashraf, M. Gao, Z. Chen, S. Kamran and Z. Raza, “Efficient Node Monitoring Mechanism in WSN using Contikimac Protocol”, International Journal of Advanced Computer Science and Applications, Vol. 8, No. 11, pp. 1-13, 2017.

  • MSU Today, “Unlocking New Possibilities for Biometrics”, Available at: http://msutoday.msu.edu/feature/2018/unlocking-new-possibilities-for-biometrics, Accessed at 2020.

  • S. Ashraf, S. Saleem and T. Ahmed, “Sagacious Communication Link Selection Mechanism for Underwater Wireless Sensors Network”, International Journal of Wireless and Microwave Technologies, Vol. 10, No. 2, pp. 12-25, 2020.

  • M.N. Giannakos, K. Sharma, I.O. Pappas, V. Kostakos and E. Velloso, “Multimodal Data as a Means to Understand the Learning Experience”, International Journal of Information Management, Vol. 48, No. 2, pp. 108-119, 2019.

  • J. Pandya, “Hacking Our Identity: The Emerging Threats from Biometric Technology”, Available at: https://www.forbes.com/sites/cognitiveworld/2019/03/09/hacking-our-identity-the-emerging-threats-from-biometric-technology, Accessed on 2020.

  • N. Sarfraz, “Adermatoglyphia: Barriers to Biometric Identification and the Need for a Standardized Alternative”, Cureus, Vol. 11, No. 2, pp. 1-9, 2020.

  • F.G. Mohameed and Morooj K. Luaibi, “Facial Recognition Based on DWT-HOG-PCA Features with MLP Classifier”, Journal of Southwest Jiaotong University, Vol. 54, No. 6, pp. 1-14, 2019.

  • D. Gafurov, “Emerging Biometric Modalities: Challenges and Opportunities”, Springer, 2020.

  • R. Singh, “The essence of eigenvalues and eigenvectors in Machine Learning”, Available at: https://towardsdatascience.com/the-essence-of-eigenvalues-and-eigenvectors-in-machine-learning-f28c4727f56f, Accessed at 2019.

  • J.F. Doriguello and A. Montanaro, “Quantum Sketching Protocols for Hamming Distance and Beyond”, Physical Review A, Vol. 99, pp. 1-13, 2019.

  • A. Herbadji, Z. Akhtar, K. Siddique and M. Cheniti, “Combining Multiple Biometric Traits Using Asymmetric Aggregation Operators for Improved Person Recognition”, Symmetry, Vol. 12, No. 3, pp. 1-19, 2020.

  • S. Ashraf, Z.A. Arfeen, M.A. Khan and T. Ahmed, “SLM-OJ: Surrogate Learning Mechanism during Outbreak Juncture”, International Journal for Modern Trends in Science and Technology, Vol. 6, No. 5, pp. 162-167, 2020.

  • S. Ashraf, A. Raza, Z. Aslam, H. Naeem and T. Ahmed, “Underwater Resurrection Routing Synergy using Astucious Energy Pods”, Journal of Robotics and Control, Vol. 1, No. 5, pp. 1-12, 2020.

  • B. Ammour, L. Boubchir, T. Bouden and M. Ramdani, “Face-Iris Multimodal Biometric Identification System”, Electronics, Vol. 9, No. 1, pp. 85-94, 2020.

  • S. Ashraf, M. Gao, Z. Mingchen, T. Ahmed, A. Raza and H. Naeem, “USPF: Underwater Shrewd Packet Flooding Mechanism through Surrogate Holding Time”, Wireless Communications and Mobile Computing, Vol. 2020, pp. 1-12, 2020.

  • A. Mohammadi, N. Aghazadeh and S Rezapour, “Haar Wavelet Collocation Method for Solving Singular and Nonlinear Fractional Time-Dependent Emden-Fowler Equations with Initial and Boundary Conditions”, Mathematical Sciences, Vol. 13, pp. 255-265, 2019.

  • S. Ashraf, A. Ahmad, A. Yahya and T. Ahmed, “Underwater Routing Protocols: Analysis of Link Selection Challenges”, AIMS Electronics and Electronics Engineering, Vol. 4, No. 2, pp. 200-215, 2020.

  • I.S. Reed and X. Chen, “Reed-Solomon Codes”, Error Control Coding for Data Networks, Springer, pp. 233-284, 1999.

  • S. Ashraf and T. Ahmed, “Underwater Routing Protocols Analysis of Intrepid Link Selection Mechanism, Challenges and Strategies”, International Journal of Scientific Research in Computer Sciences and Engineering, Vol. 8, No. 2, pp. 1-9, 2020.

  • Log Gabor Filter, “Log Gabor Filter”, Available: https://en.wikipedia.org/w/index.php?title=Log_Gabor_filter&oldid=959860559, Accessed at 2020.

  • P. Kapoor, D. Lee, B. Kim and S. Lee, “Computation-Efficient Quantization Method for Deep Neural Networks”, Proceedings of International Conference on Learning Representations, pp. 1-8, 2018.

  • S. Ashraf, T. Ahmed, A. Raza and H. Naeem, “Design of Shrewd Underwater Routing Synergy Using Porous Energy Shells”, Smart Cities, Vol. 3, No. 1, pp. 74-92, 2020.

  • Bayometeric, “False Acceptance Rate and False Recognition Rate”, Available at: https://www.bayometric.com/false-acceptance-rate-far-false-recognition-rate-frr, Accessed at 2020.

  • False Rejection, “What is false rejection rate (FRR)? Webopedia Definition.” Available at: https://www.webopedia.com/TERM/F/false_rejection.html, Accessed at 2020.

  • S. Ashraf, T. Ahmed, S. Saleem and Z. Aslam, “Diverging Mysterious in Green Supply Chain Management”, Oriental Journal of Computer Science and Technology, Vol. 13, No. 1, pp. 22-28, 2020.


Abstract Views: 181

PDF Views: 0




  • CMBA- A Candid Multi-purpose Biometric Approach

Abstract Views: 181  |  PDF Views: 0

Authors

Sehrish Saleem
Department of Computer Science, Muhammad Nawaz Sharif University of Engineering and Technology, Pakistan
Shahzad Ashraf
College of Internet of Things Engineering, Hohai University, Changzhou Campus, China
Muhammad K. Basit
Department of Computer Science, Muhammad Nawaz Sharif University of Engineering and Technology, Pakistan

Abstract


All humans are born with unique physically identified body characteristics to other persons which remains unchanged throughout life. These characteristics are taken into account by the emerging technology to get recognized from person to person. The technology used by the traditional human identification system sometimes becomes inefficient when data or images received are not up to the acceptable quality mark or when a person has a face covered with mask-like during epidemic virus fistula. In order to overcome the human recognition challenges, a Candid Multi-purpose Biometric Approach (CMBA) has been proposed which can make human identification easier and approachable. The CMBA human recognition approach uses two uniquely identified modalities such as foot and iris. This approach shrewdly identifies and makes the bodacious recognition among humans and suggests the sagacious result which is foremost better than the traditional biometric system. The CMBA is offering opportunity to take more than two biometric features, by combining them to overcome unimodal biometric system limitations and to achieve optimal results. Using sagacious edge detector and Hough transformation technique, the Iris and foot part are segmented into easy and quick extraction voting system which produce succulent output. In fact, this technique is new in biometric identification era.

Keywords


Biometric System, Face Recognition, Modalities, Face Mask.

References