GENDER CLASSIFICATION FROM THE IRIS CODE USED FOR RECOGNITION

  • Mariya Christeena Vijini K M S
  • Kuzhaloli Shanmugan
Keywords: Recognition, LBP, SVM, rank features.

Abstract

In this paper, we present a new method for gender classification based on features of the iris texture selected by mutual information to improve gender classification of face images. The performance of the proposed approach has been investigated through extensive experiments performed on public database. We also showed improved results by fusion of texture features with best features selected independently from the left and right irises based on selection of features using rank feature selection method. The classification task has been achieved by using Support Vector Machine (SVM). We compared our method with existing gender classification methods based on texture feature with classifier being the same as SVM.

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Author Biographies

Mariya Christeena Vijini K M S

ETCE Department, Sathyabama University, TamilNadu.

Kuzhaloli Shanmugan

ETCE Department, Sathyabama University, TamilNadu.

References

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Published
2017-03-27
Section
Articles