Introduction to Multimodal Biometrics Using OpenCV

EasyChair Preprint 7634

Abstract

Biometrics is defined as analysis of people’s unique physical and behavior wise characteristics. Biometric systems are used for identification of entity, controlling the access and find the identity of the personals who are under observations. Some commonly used biometrics are face, iris, fingerprints. Recognition of identity with the help of biometrics offer a lot of potential advantage over methods with knowledge. Uni modal biometrics is a widely tested biometric system nowadays but there are many issues that has been encountered with the system using mono modal biometrics. An extension of it is multi modal biometrics is been developed which extracts the features of multiple biometrics and using algorithms work on it to produce a fused modal and identifies the authorized entity using algorithm from that fused modal. Technology is so much broad now that biometric systems are able to provide knowledge based as well as token based systems. Confidential data can be access by only those individuals who are accurately identified by the biometric system. The modal will be working on multi biometric system. This modal will try extract features from multiple biometrics and try to fuse them to form it single identifiable character. The modal will consist of new algorithms which will help it to match the identity

Keyphrases: Artificial Intelligence, Machine Learning., deep learning

@booklet{EasyChair:7634,
  author    = {Abhimanyu Kumar and Tarushi Singh},
  title     = {Introduction to Multimodal Biometrics Using OpenCV},
  howpublished = {EasyChair Preprint 7634},
  year      = {EasyChair, 2022}}