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1712450 Vol 7 · Issue 10 Download Paper

A Review On Biometric Authentication Using Adaptive Iris Features

K. Mani Raju Gattu Ramya Nagavelli Yogender Nath R. Prasanth Reddy

Subject area: Science,Engineering and Technology  ·  Area of research: Biometric Authentication

DOI: 10.64388/IREV7I10-1712450

Abstract

A person's fingerprint, palm print, palm vein, finger vein, retina, and iris are among the many biometric identities that are linked to them. For applications like authorisation systems, attendance systems, and others, people are recognised by their biological identities. Nearly every company with a medium-sized to big workforce has adopted biometric technology. A large number of small businesses with a sizable workforce are also implementing biometric solutions. Iris-based biometric systems are becoming more and more popular as stand-alone, hybrid, or combined biometrics with other authenticating entities. Accurate localisation of the iris characteristics from the ocular image gathered for training or testing is necessary for iris identification. Two demarcation circles are needed for iris extraction; the first circle marks the outer boundary, and the second circle marks the inner boundary by identifying the pupil's outer boundary. For precise localisation of the region of interest containing the iris feature, the angular shift mechanism can also be used to examine the movement of the iris in the provided image. The suggested method would identify the iris features with or without contact lenses using probabilistic classification based on the multi-class SVM. The suggested remedy is to enhance the current model for reliable performance.

Keywords

IRIS Recognition, Probabilistic Classification, Moved Feature Localization, Authorization Systems, Etc.

References

[1] Nandipati Sai Akash, Naveen Sai Bommina, Uppu Lokesh, Hussain Syed, Syed Umar, "Optimized Block Chain-Enabled Security Mechanism for IoT Using Ant Colony Optimization", International Journal on Recent and Innovation Trends in Computing and Communication, (2023), 11(10), 1226–1233.

[2] Habeeb, M. S., & Babu, T. R. (2022). Network intrusion detection system: a survey on artificial intelligence‐based techniques. Expert Systems, 39(9), e13066

[3] Naveen Sai Bommina, Nandipati Sai Akash, Uppu Lokesh, Dr. Hussain Syed, Dr. Syed Umar, "A Hybrid Optimization Framework for Enhancing IoT Security via AI-based Anomaly Detection", International Journal on Recent and Innovation Trends in Computing and Communication, (2023) ISSN: 2321-8169 Volume: 11 Issue: 3.

[4] C. W. Tan, and A. Kumar, "Accurate Iris Recognition at a Distance Using Stabilized Iris Encoding and Zernike Moments Phase Features."Image Processing, IEEE Transactions on 23, no. 9 (2014): 3962-3974.

[5] Mr. Dikshendra Daulat Sarpate, and Dr. B.G Nagaraja, "CONVOLUTION NEURAL NETWORK-BASED SPEECH EMOTION RECOGNITION USING MFCCS", International Journal of Communication Networks and Information Security, 2023/12/10

[6] J. S. Doyle, and K.W. Bowyer, "Robust Detection of Textured Contact Lenses in Iris Recognition Using BSIF." Access, IEEE 3 (2015): 1672- 1683.

[7] Uppu Lokesh , Naveen Sai Bommina , Nandipati Sai Akash , Dr. Hussain Syed , Dr. Syed Umar. (2021). Deep Reinforcement Learning with Genetic Algorithm Tuning for Intrusion Detection in IoT Systems. International Journal of Communication Networks and Information Security (IJCNIS), 13(3), 582–595.

[8] G. Gale, and S. S. Salankar, "A Review on Advance Methods Of Feature Extraction In Iris Recognition System." IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e- ISSN (2014): 2278-1676.

[9] L. Peihua, and M. Hongwei, "Iris recognition in non-ideal imaging conditions." Pattern Recognition Letters 33, no. 8 (2012): 1012-1018.

[10] Uppu Lokesh, Naveen Sai Bommina, Nandipati Sai Akash, Dr. Hussain Syed, Dr. Syed Umar, "Designing Energy-Efficient and Secure IoT Architectures Using Evolutionary Optimization Algorithms", International Journal of Applied Engineering & Technology, Vol. 4 No.2, September, 2022.

[11] Singh, A., Gupta, M., Raj, A., Gupta, S. K., & Habeeb, M. S. (2020, December). TWDM-PON: The Enhanced PON for Triple Play Services. In 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE) (pp. 1-5). IEEE.

[12] Naveen Sai Bommina , Nandipati Sai Akash, Uppu Lokesh , Dr. Hussain Syed , Dr. Syed Umar, "Multi-Objective Genetic Algorithms for Secure Routing and Data Privacy in IoT Networks", International Journal of Communication Networks and Information Security (IJCNIS), (2020), 12(3), 632–643.

[13] G. Santos, and E. Hoyle, "A fusion approach to unconstrained iris recognition." Pattern Recognition Letters 33, no. 8 (2012): 984-990.

[14] K.Y. Shin, G. P. Nam, D. S. Jeong, D. H. Cho, B. J. Kang, K. R. Park, and J. Kim, "New iris recognition method for noisy iris images." Pattern Recognition Letters 33, no. 8 (2012): 991-999.

[15] Nandipati Sai Akash, Naveen Sai Bommina, Uppu Lokesh, Hussain Syed, Syed Umar, "Optimized Block Chain-Enabled Security Mechanism for IoT Using Ant Colony Optimization", International Journal on Recent and Innovation Trends in Computing and Communication, (2023), 11(10), 1226–1233.

[16] Mr DD Sarpate, "Design of Dual Band Microstrip for satellite Applications", 2nd International Conference on Recent Innovations in Engineering & Technology 2020

[17] R. Szewczyk, K. Grabowski, M. Napieralska, W. Sankowski, M. Zubert, and A. Napieralski. "A reliable iris recognition algorithm based on reverse biorthogonal wavelet transforms."Pattern Recognition Letters 33, no. 8 (2012): 1019-1026.

[18] Naveen Sai Bommina , Nandipati Sai Akash, Uppu Lokesh , Dr. Hussain Syed , Dr. Syed Umar, "Privacy-Preserving Federated Learning for IoT Devices with Secure Model Optimization", International Journal of Communication Networks and Information Security (IJCNIS), (2021), 13(2), 396–405.

[19] W. Y. Han, W. K. Chen, Y. P. Lee, K. S. Wu, and J. C. Lee, "Iris Recognition based on Local Mean Decomposition. “ Appl. Math 8, no. 1L(2014):217-222.

[20] Usman, M., Zubair, M., Hussein, H. S., Wajid, M., Farrag, M., Ali, S. J., ... & Habeeb, M. S. (2021). Empirical mode decomposition for analysis and filtering of speech signals. IEEE Canadian Journal of Electrical and Computer Engineering, 44(3), 343-349.

[21] Naveen Sai Bommina, Uppu Lokesh, Nandipati Sai Akash, Dr. Hussain Syed, Dr. Syed Umar, "Optimized AI Models for Real -Time Cyberattack Detection in Smart Homes and Cities", International Journal of Applied Engineering & Technology, Vol. 4 No.1, June, 2022.

[22] Gupta, Rachit Kumar, Mandeep Kaur, and Jatinder Manhas. "Tissue level based deep learning framework for early detection of dysplasia in oral squamous epithelium." Journal of Multimedia Information System 6.2 (2019): 81-86.

[23] Umar, Syed, Bommina Naveen Sai, Nagineni Sai Lasya,Doppalapudi Asutosh, and LohithaRani. "Machine Learning based Sentiment Analysis of Product Reviews Using DeepEmbedding." Journal of Optoelectronics Laser 41, no. 6(2022): 108-113.

How to cite this paper

K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy "A Review On Biometric Authentication Using Adaptive Iris Features" Iconic Research And Engineering Journals Volume 7 Issue 10 2024 Page 622-628 https://doi.org/10.64388/IREV7I10-1712450
K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy "A Review On Biometric Authentication Using Adaptive Iris Features" Iconic Research And Engineering Journals, vol. 7, no. 10, Apr. 2024, doi: https://doi.org/10.64388/IREV7I10-1712450
K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy (2024). A Review On Biometric Authentication Using Adaptive Iris Features. Iconic Research And Engineering Journals, 7(10). doi: https://doi.org/10.64388/IREV7I10-1712450
K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy "A Review On Biometric Authentication Using Adaptive Iris Features" Iconic Research And Engineering Journals, vol. 7, no. 10, Apr. 2024. Crossref, https://doi.org/10.64388/IREV7I10-1712450
@article{1712450,
      author = {K. Mani Raju, Gattu Ramya, Nagavelli Yogender Nath, R. Prasanth Reddy},
      title = {A Review On Biometric Authentication Using Adaptive Iris Features},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {10},
      pages = {622-628},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712450.pdf},
      abstract = {A person's fingerprint, palm print, palm vein, finger vein, retina, and iris are among the many biometric identities that are linked to them. For applications like authorisation systems, attendance systems, and others, people are recognised by their biological identities. Nearly every company with a medium-sized to big workforce has adopted biometric technology. A large number of small businesses with a sizable workforce are also implementing biometric solutions. Iris-based biometric systems are becoming more and more popular as stand-alone, hybrid, or combined biometrics with other authenticating entities. Accurate localisation of the iris characteristics from the ocular image gathered for training or testing is necessary for iris identification. Two demarcation circles are needed for iris extraction; the first circle marks the outer boundary, and the second circle marks the inner boundary by identifying the pupil's outer boundary. For precise localisation of the region of interest containing the iris feature, the angular shift mechanism can also be used to examine the movement of the iris in the provided image. The suggested method would identify the iris features with or without contact lenses using probabilistic classification based on the multi-class SVM. The suggested remedy is to enhance the current model for reliable performance.},
      keywords = {IRIS Recognition, Probabilistic Classification, Moved Feature Localization, Authorization Systems, Etc.},
      month = {April},
      doi = {https://doi.org/10.64388/IREV7I10-1712450}
  }