Systematic Digital Signal Processing Approach in Various Biometric Identification

K. P. Ajitha Gladis*, D. Sharmila**
* Department of Information Technology, C.S.I Institute of Technology, Thovalai, Tamil Nadu, India.
** Department of Computer Applications, Government Arts & Science College, Kanyakumari, Tamil Nadu, India.
Periodicity:July - December'2022
DOI : https://doi.org/10.26634/jdp.10.2.19290

Abstract

Biometrics are unique physical characteristics, such as fingerprints, that can be used for automatic recognition. Biometric identifiers are often classified as physiological characteristics associated with body shape. The goal is to capture a piece of biometric data from that person. It could be a photograph of their face, a recording of their voice, or a picture of their fingerprints. While there are numerous types of biometrics for authentication, the six most common are facial, voice, iris, near-field communication, palm or finger vein patterns, and Quick Response (QR) code. Biometrics is a subset of the larger field of human identification science. This paper explores computational approaches to speaker recognition, face recognition, speech recognition, and fingerprint recognition to assess the overall state of digital signal processing in biometrics.

Keywords

Digital Signal Processing, Biometric Identification, Face Recognition, Speech Recognition and Fingerprint.

How to Cite this Article?

Gladis, K. P. A., and Sharmila, D. (2022). Systematic Digital Signal Processing Approach in Various Biometric Identification. i-manager’s Journal on Digital Signal Processing, 10(2), 7-15. https://doi.org/10.26634/jdp.10.2.19290

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