Conventional security systems are often plagued by inherent flaws, leading to frequent security breaches. To address these vulnerabilities, automated biometric systems have emerged, leveraging individuals' physiological and behavioural traits for precise identification. Among these biometric modalities, iris-based authentication is a highly reliable, distinctive, and contactless method for user recognition. This research endeavours to enhance the accuracy of iris liveness detection by combining features extracted from the TSBTC n-Ary (Thepade’s Sorted Block Truncation Coding) method with those derived from the Triangle Thresholding method. Two distinct datasets, namely IIIT Delhi and Clarkson 2015, have been employed to evaluate the efficacy of these combined features. The study involves extracting features from three sources: TSBTC, TSBTC+Triangle, and Triangle methods. These features are subsequently input into the WEKA tool, which employs various classifiers to assess accuracy. The findings of this investigation reveal a notable increase in the accuracy of Iris Liveness Detection (ILD) by incorporating handcrafted techniques like TSBTC in conjunction with the Thresholding method. In essence, this research underscores the potential for improving the robustness of security systems by harnessing the synergy of distinct biometric methods, thereby mitigating the shortcomings of conventional security systems and fortifying the foundations of secure user authentication.


Biometrics, Iris Liveness Detection, TSBTC, Thresholding,


Download data is not yet available.


  1. S. Khade, S. Gite, S.D. Thepade, B. Pradhan, A. Alamri, Detection of iris presentation attacks using hybridizing discrete cosine transform and Haar transform with machine learning classifiers and ensembles. IEEE Access, 9 (2021) 169231–169249. https://doi.org/10.1109/ACCESS.2021.3138455
  2. J. Galbally, J. Ortiz-Lopez, J. Fierrez, J. Ortega-Garcia, (2012) Iris liveness detection based on quality related features. 2012 5th IAPR International Conference on Biometrics (ICB), New Delhi, India. https://doi.org/10.1109/icb.2012.6199819
  3. J. Daugman, Probing the Uniqueness and Randomness of IrisCodes: Results From 200 Billion Iris Pair Comparisons. in Proceedings of the IEEE, 94 (2006) 1927-1935. https://doi.org/10.1109/JPROC.2006.884092
  4. S. Khade, S. Ahirrao, S. Phansalkar, K. Kotecha, S. Gite, S.D.Thepade, Iris liveness detection for biometric authentication: A systematic literature review and Future Directions. Inventions, 6 (2021) 65. https://doi.org/10.3390/inventions6040065
  5. M. Abu-Zanona, Identifying humans based on biometric iris recognition using an interactive transfer learning framework. Information Sciences Letters, 12 (2023) 1115–1123. https://doi.org/10.18576/isl/1203033
  6. S. Khade, S. Gite, B. Pradhan, Iris liveness detection using multiple deep convolution networks. Big Data and Cognitive Computing, 6 (2022) 67. https://doi.org/10.3390/bdcc6020067
  7. Agarwal, A. Noore, M. Vatsa, R. Singh, Enhanced iris presentation attack detection via contraction-expansion CNN. Pattern Recognition Letters, 159 (2022) 61–69. https://doi.org/10.1016/j.patrec.2022.04.007
  8. S. Khade, S. Gite, S.D. Thepade, B. Pradhan, A. Alamri, Detection of iris presentation attacks using feature fusion of Thepade’s sorted block truncation coding with grey-level co-occurrence matrix features. Sensors, 21 (2021) 7408. https://doi.org/10.3390/s21217408
  9. H. Kekre, & S. Thepade, Image retrieval using augmented block truncation coding techniques. Proceedings of the International Conference on Advances in Computing, Communication and Control (2009) 384–390. https://doi.org/10.1145/1523103.1523180
  10. S. Sawalha, A. Awajan, Blank Background Image lossless Compression Technique. International Journal of Image Processing (IJIP), 8 (2014) 10.
  11. M. Choudhary, V. Tiwari, U. Venkanna, Identifying discriminatory feature-vectors for fusion-based Iris liveness detection. Journal of Ambient Intelligence and Humanized Computing, 14 (2022) 10605–10616. https://doi.org/10.1007/s12652-022-03712-4
  12. D. Yambay, B. Walczak, S.Schuckers, A.Czajka, (2017) Livdet-iris 2015-iris liveness detection competition2015. IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), New Delhi, India. https://doi.org/10.1109/isba.2017.7947701
  13. D. Yadav, N. Kohli, J. S. Doyle, R. Singh, M. Vatsa, K.W. Bowyer, Unravelling the effect of textured contact lenses on iris recognition. IEEE Transactions on Information Forensics and Security, 9 (2014) 851-862. https://doi.org/10.1109/tifs.2014.2313025
  14. N. Kohli, D. Yadav, M. Vatsa, R. Singh, (2013) Revisiting iris recognition with colour cosmetic contact lenses. 2013 International Conference on Biometrics (ICB), Madrid, Spain. https://doi.org/10.1109/icb.2013.6613021