Real-Time Multimodal Biometric Authentication of Human Using Face Feature Analysis
作者机构：University of Petroleum and Energy StudiesDehradunIndia Lovely Professional UniversityIndia Government Bikram College of CommercePatiala147001PunjabIndia La Trobe UniversityMelbourneAustralia Sookmyung Women’s UniversitySeoul04310Korea
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2021年第69卷第10期
页 面：1-19页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Biometrics real-time multimodal biometrics real-time face recognition feature analysis
摘 要：As multimedia data sharing increases,data security in mobile devices and its mechanism can be seen as *** combines the physiological and behavioral qualities of an individual to validate their character in *** incorporate physiological attributes like a fingerprint,face,iris,palm print,finger knuckle print,Deoxyribonucleic Acid(DNA),and behavioral qualities like walk,voice,mark,or *** main goal of this paper is to design a robust framework for automatic face *** Invariant Feature Transform(SIFT)and Speeded-up Robust Features(SURF)are employed for face ***,we propose a modified Gabor Wavelet Transform for SIFT/SURF(GWT-SIFT/GWT-SURF)to increase the recognition accuracy of human *** proposed scheme is composed of three ***,the entropy of the image is removed using Discrete Wavelet Transform(DWT).Second,the computational complexity of the SIFT/SURF is ***,the accuracy is increased for authentication by the proposed GWT-SIFT/GWT-SURF algorithm.A comparative analysis of the proposed scheme is done on real-time Olivetti Research Laboratory(ORL)and Poznan University of Technology(PUT)*** compared to the traditional SIFT/SURF methods,we verify that the GWT-SIFT achieves the better accuracy of 99.32%and the better approach is the GWT-SURF as the run time of the GWT-SURF for 100 images is 3.4 seconds when compared to the GWT-SIFT which has a run time of 4.9 seconds for 100 images.
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