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Nowadays, Iris recognition is a method of biometricverification of the person authentication process based on the human irisunique pattern, which is applied to control system for high level security. Itis a popular system for recognizing humans and essential to understand it. Theobjective of this method is to assign a unique subject for each iris image forauthentication of the person and provide an effective feature representation ofthe iris recognition with the image analysis. This paper proposed a new optimizationand recognition process of iris features selection by using proposed ModifiedADMM and Deep Learning Algorithm MADLA. For improving the performance of thesecurity with feature extraction, the proposed algorithm is designed and usedto extract the strong features identification of iris of the person with lesstime, better accuracy, improving performance in access control and in securitylevel. The evaluations of iris data are demonstrated the improvement of therecognition accuracy. In this proposed methodology, the recognition of the irisfeatures has been improved and it incorporates into the iris recognitionsystems.

KEYWORDS

GLCM, Deep Learning, Strong Features Extraction, MADMM, Iris Recognition

Cite this paper

Pravinthraja, S. and Umamaheswari, K. 2016 Optimized Features Extraction of IRIS Recognition by Using MADLA to Ensure Secure Authentication. Circuits and Systems, 7, 1927-1933. doi: 10.4236-cs.2016.78167.





Autor: S. Pravinthraja1*, K. Umamaheswari2

Fuente: http://www.scirp.org/



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