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- W3202594017 abstract "Biometric systems may be divided into 2 categories betting on the characteristics used. One category uses physical characteristics that area unit associated with the form and presence of the body and body components, like fingerprint, finger knuckles, face (2-D and 3-D), DNA, hand and palm pure mathematics, iris texture, and retinal vasculature. Systems belong to the second category use activity characteristics, like gait, handwriting, keyboard writing, and speech. Analysis in face recognition has endlessly been challenged by alien (head create, lighting conditions) and intrinsic (facial expression, aging) sources of variability. During this system is employed to several organizations and lots of applications for security purpose.Many approaches area unit face recognition exists, during this project, specialize in a comparative study of 3D face recognition beneath expression variations. First 3D face databases with expressions area unit listed, and therefore the most significant ones area unit conferred and their complexness is quantified victimisation principal part analysis, linear discriminate analysis and native binary patterns. The project to be real time enforced datasets to reason the assorted varieties of expressions. Pictures in terms of the popularity performance are evaluated with 3 completely different techniques (principal component analysis, linear discriminant analysis, and native binary patterns) on face recognition grand challenge and strait 3D face databases." @default.
- W3202594017 created "2021-10-11" @default.
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- W3202594017 date "2019-01-01" @default.
- W3202594017 modified "2023-09-27" @default.
- W3202594017 title "3D Security User Identification in Banking" @default.
- W3202594017 doi "https://doi.org/10.2139/ssrn.3385495" @default.
- W3202594017 hasPublicationYear "2019" @default.
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