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Diagnosis of Corneal Arcus Using Statistical Feature Extraction and Support Vector Machine

  • S. V. Mahesh KumarEmail author
  • R. Gunasundari
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 394)

Abstract

Corneal arcus is a white ring or arc deposited in the corneal region of the human eye. This corneal abnormality is significantly associated with the lipid disorders and atherosclerosis. In this paper, we proposed a computer-aided diagnosis system to detect the corneal arcus. The proposed method detects the corneal arcus using the statistical features extracted from the iris region of the eye image. The iris region is segmented from the other regions of the eye image using circular Hough transform (CHT). In order to achieve the better classification results, a morphological operation-based specular reflection removal and colour transformation-based enhancement methods are also developed in this paper. The proposed method was implemented and evaluated using the abnormal eye images from our own database and normal eye images collected from UBIRIS.v1 database. Our database contains the eye images with different grades of corneal arcus abnormality. The performance of our method was evaluated using the confusion matrix-based metrics. In the training phase, our method achieved a classification accuracy of 1. In the testing phase, our method achieved a classification accuracy of 0.96 with a positive predictive value 0.9791 and negative predictive value 0.9423.

Keywords

Corneal arcus Eye image Iris segmentation Statistical features Classification 

Notes

Acknowledgments

We would like to thank Dr. N. Ezhilvathani, HOD, Department of Ophthalmology, Indira Gandhi Medical College and Research Institute (IGMC&RI), Puducherry for her suggestions and support on the corneal arcus eye image collection for this work.

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of ECEPondicherry Engineering CollegePuducherryIndia

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