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Determining diabetes using iris recognition system

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Abstract

Iridology is a science which correlates the apparitions of iris to tissue weaknesses in the body. It merely reveals weaknesses, inflammation, or toxicity in organs or tissues. It also indicates weakness long before the symptoms appear. In this paper, support vector machine-based iris recognition system utilizing iridology has been used to determine diabetes. Features from eye image database of 40 people having healthy eye (normal) and having affected eye (diabetes) have been extracted by 2-D wavelet tree. The overall accuracy is obtained to be 87.50 % which reasonably demonstrates the effectiveness of the system.

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Acknowledgment

The authors would like to acknowledge GLA University, Mathura, India, for partially supporting this research. Authors would also like to acknowledge Dr. Arun Bansal, Dr. Poonam Agarwal, and all subjects who helped in developing the database.

Conflict of interest

The authors would like to declare that there is no conflict of interest.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, G.L.A. University, Mathura, Uttar Pradesh, India

    Atul Bansal

  2. Electrical and Instrumentation Engineering Department, Thapar University, Patiala, Punjab, India

    Ravinder Agarwal

  3. School of Mathematics and Computer Applications, Thapar University, Patiala, Punjab, India

    R. K. Sharma

Authors
  1. Atul Bansal
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  2. Ravinder Agarwal
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  3. R. K. Sharma
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Correspondence to Atul Bansal.

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Bansal, A., Agarwal, R. & Sharma, R.K. Determining diabetes using iris recognition system. Int J Diabetes Dev Ctries 35, 432–438 (2015). https://doi.org/10.1007/s13410-015-0296-1

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  • DOI: https://doi.org/10.1007/s13410-015-0296-1

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