ICTACT Journal on Image and Video Processing

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IRIS Detection For Biometric Pattern Identification Using Deep Learning


Affiliations
1 Department of Computer Science and Engineering, HKBK College of Engineering, India
2 Department of Computer Science and Engineering, Presidency University, India
3 Department of Computer Science, The Quaide Milleth College for Men, India
4 Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, Oman
     

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In this paper, we develop a liveness detection of iris present in the study to reduce various spoofing attacks using gray-level co-occurrence matrix (GLCM) and Deep Learning (DL). The input images of iris are been given to this technique for the extraction of texture and colour features with fine details. The details are fused finally and given to a DL classifier for the classification of liveness detection. The simulation is conducted to test the efficacy of the model and the results of simulation shows that the proposed method achieves higher level of accuracy than existing methods.

Keywords

Iris Detection, Pattern Identification, Liveness Detection, Biometric, Deep Learning
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  • IRIS Detection For Biometric Pattern Identification Using Deep Learning

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Authors

M. Ramkumar
Department of Computer Science and Engineering, HKBK College of Engineering, India
Amirtha Preeya
Department of Computer Science and Engineering, Presidency University, India
R. Manikandan
Department of Computer Science, The Quaide Milleth College for Men, India
T. Karthikeyan
Department of Electronics and Telecommunications Engineering, University of Technology and Applied Sciences, Oman

Abstract


In this paper, we develop a liveness detection of iris present in the study to reduce various spoofing attacks using gray-level co-occurrence matrix (GLCM) and Deep Learning (DL). The input images of iris are been given to this technique for the extraction of texture and colour features with fine details. The details are fused finally and given to a DL classifier for the classification of liveness detection. The simulation is conducted to test the efficacy of the model and the results of simulation shows that the proposed method achieves higher level of accuracy than existing methods.

Keywords


Iris Detection, Pattern Identification, Liveness Detection, Biometric, Deep Learning

References