Improved Iris Recognition Using Eigen Values for Feature Extraction for Off Gaze Images

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 249)

Abstract

There are various Iris recognition and identification schemes known to produce exceptional results with very less errors and at times no errors at all but are patented. Many prominent researchers have given their schemes for either recognition of an Iris from an image and then identifying it from a set of available database so as to know who it belongs to. The Gabor filter is a preferred algorithm for feature extraction of Iris image but it has certain limitations, hence Principal Component Analysis (PCA) is used to overcome the limitations of the Gabor filter and provide a solution which achieves better results which are encouraging and provide a better solution to Gabor filters for Off Gaze images.

Keywords

Gabor Filter Principal Component Analysis Iris Recognition Iris Identification False Acceptance Rate False Rejection Rate Eigen Values Eigen Vectors 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Electronics & TelecommunicationSAOE, KondhwaPuneIndia
  2. 2.Department of Computer EngineeringAISSMS IOITPuneIndia

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