Retracted: Innovative approach for multimodal fusion recognition based feature extraction using band‐limited phase‐only correlation and discrete orthonormal Stockwell transform

Biometrics is the bureau of science that helps to measure the individual's features by utilising their behavioural and physiological characteristics. Since years ago biometric technology are contemplated to be a unique tool for other security purposes. Inauspicious biometrics, Ear recognition,...

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Bibliographic Details
Main Authors: A. Kavipriya, A. Muthukumar
Format: Article
Language:English
Published: Wiley 2020-12-01
Series:IET Image Processing
Subjects:
Online Access:https://doi.org/10.1049/iet-ipr.2020.0145
Description
Summary:Biometrics is the bureau of science that helps to measure the individual's features by utilising their behavioural and physiological characteristics. Since years ago biometric technology are contemplated to be a unique tool for other security purposes. Inauspicious biometrics, Ear recognition, and Finger Knuckle Print have been enchanted as a booming analysis with interests among several researchers in modern periods. It has an ample range of private and other law enforcement applications. A combination of multiple human attributes is authenticated and considered to be a competent strategy in case of a multimodal Personal authentication system. In this paper extracting the local and global features via the structure of the time‐frequency domain has been studied. This proposed scheme exploits the analysis of dual biometric modalities i.e. Ear and Finger Knuckle Print which are carried out at the stage of feature‐level fusion. The feature Extraction two biometric patterns are obtained by generating the Local and Global feature information that helps in refining the alignment of dual biometric images in matching i.e. Discrete Orth normal Stockwell Transform‐Ear recognition and Band Limited phase‐only correlation with Finger Knuckle Print. Experiment results conducted with these FKP and EAR are demonstrated in improving recognition of efficient accuracy.
ISSN:1751-9659
1751-9667