Certain investigation on iris image recognition using hybrid approach of Fourier transform and Bernstein polynomials

摘要

In the era of biometric research the recent developments in real time biometric world, iris recognition is considered as one of the most important approach used in person identification based biometric authentication. This approach is considered than the other biometric authentication methods such as behavioral biometrics which specially includes Keystroke, Speaker Recognition whereas the another side of biometric authentication is Physical biometrics which specially includes Fingerprint Recognition, Voice Recognition, Finger Geometry Recognition and Facial Recognition. From these considerations, the hybrid approach of Fourier transform and Bernstein polynomial for iris recognition has been proposed. The novelty of this proposed method results in improving the Accuracy, False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER) for the given iris image. In addition to this, Singular Value Decomposition (SVD) is used for iris image pre-processing. Circular Hough transform (CHT) and Canny edge detection (CED) are applied for iris image segmentation which segments the individual region of the input images. After the image is segmented, Fourier transform and Bernstein polynomial have been applied to extract the features from the segmented iris image, which is the most important step for obtaining the texture details, which are independent and uncorrelated even for identical pairs. Support Vector Machine (SVM) is used for image classification. Perhaps, Feature extraction and Classification of iris image are mainly based on the rich texture details present in iris image. Finally, our proposed system is applied on UBIRIS database and our research experiment provides better accuracy and recognition rates compared to the combined iris recognition techniques such as Fourier transform with SVM, Bernstein polynomial with SVM, Fourier transform with KSVM, Bernstein polynomial with KSVM and hybridization of Fourier and Bernstein polynomial with SVM. (C) 2017 Elsevier B.V. All rights reserved.