adminBIOMETRICS
Biometrics refers to the measurement and analysis of unique physical or behavioral characteristics of an individual. In fact there are various traits present in humans, which can be used as biometric modalities. The biometric modalities fall under three types; physiological, behavioral and a combination of both physiological and behavioral modality. While under physiological modality are; finger print or recognition, hand and geometry recognition, facial recognition, iris recognition, hand print recognition, retinal scanning and DNA recognition. While under behavioral, we have gait, rhythm of typing keys, and signature recognition. Also as regards the combination of both modalities is voice recognition. In general these are the biometric modalities that have gain traction and widespread use today, such as; facial recognition, fingerprint scanning, iris scanning, voice recognition, handwriting analysis, DNA analysis, vein recognition, gait analysis (way of walking), and signature recognition.
These characteristics are used to identify, often for security, access control or identity verification purposes.
Facial recognition is an aspect of biometrics, that uses deep learning algorithms to; detect faces, analyze facial features, compare the analyzed features to those in a database or a specific individual’s face and verify or identify the individual based on the comparism.
Fingerprint scanning captures and analyze the unique patterns and ridges found on an individual finger tips, uses sensors or scanners to read and digitalize the finger print patterns, compares the scanned finger print to those in a database or a specific individuals fingerprint; verifies or identifies the individual based on the match.
Iris scanning captures and analyzes the unique patterns and characteristics of an individual iris, uses a specialized camera or sensor to take a high contrast image of the iris, extract specific features, such as the iris pattern, color and texture, compares the extracted features to those in a database or a specific individual iris profile, verifies or identifies the individual based on the match.
Voice recognition, captures and analyzes audio recordings of spoken words or phrases, uses machine learning algorithms to identify and interpret the spoken words into written text, verifies or identifies the speaker based on their unique characteristics.
Hand writing analysis, examines the physical characteristics of hand writing such as; letter formation, size and shape, slant and angle, pressure and strokes. Spacing and alignment, interprets these characteristics to real information about the writer.
DNA analysis examines the DNA molecules, which contains an individual’s genetic information, analyzes the DNA sequence, structure or function to identify specific genes, genetic variations or patterns, compares the analyzed DNA to known DNA samples, DNA databases, genetic markers or predisposition and Providing information on identity, genetic disorder, traits, and also for forensic evidence.
Vein recognition, uses near infrared light to capture images of the unique patterns of veins in an individual’s body, typically in the hand or fingers; analyzes the vein patterns including the shape, size and location of the vein; compares the analyzed patterns to those in a database or a specific individual’s vein profile; verifies or identifies the individual based on the match.
Gait analysis is the study and evaluation of an individual’s walking pattern, including the manner in which they walk, run or move their limbs. It involves analyzing various parameters such as; stride length, and with, cadence (steps per minute), velocity, acceleration and deceleration, posture and alignment, joint angles and movement, muscle activity and strengths.
Signature recognition, also known as signature verification or signature authentication; captures and analyzes the unique patterns and characteristics of an individual’s handwritten signature; use algorithms to extract specific features such as shape and size, stroke order and direction, pressure and speed, letter and word formation; compares the analyzed signature to a stored template or sample, verifies or authenticates the signature as genuine or forged.
The need to identity people in real time prior to authenticating them before the use of certain facilities like in banking and other financial transaction and in areas where privacy and security is of paramount importance requires the use of the relevant biometric technology to protect the system and data from unauthorized users.
The use of biometrics will however result in increased security, enhanced user experience, cost effective, better fraud prevention, increased efficiency, widespread use, and increased adoption because iof emerging trends.
Despite these overwhelming benefit, there are potential risk, may give birth to a surveillance state as captured in George Orwell’s Novell 1984, in which privacy is eroded thereby creating discrimination, security challenges as well as racial, national and global tension.
However to mitigate against these risk and to avoid this dystopian or bleak future, it is necessary to implement robust regulation and oversight mechanism, ensure transparency in biometric data collection and usage, prioritize privacy and security, encourage public debate and thus awareness, develop ethical guidelines for biometric technology development and deployment.
Despite all this apprehension, the benefit of a society run by biometrics as our guide post will result in immense benefit for all.
Sources;
- Biometrics realistic authentication :(c)2015. W.W.W.tuturialspoint.com; Tutorialspoint PVt Ltd.
- Handbook of biometrics by Anil Jain, Patrick Flynn, and Arun A.Ross.
- Biometric systems: technology, Design and performance evaluation by B. Vailler and B.M Gupta.
- Introduction to biometrics by Anil. Jain.
- Biometrics in identity documents by Claus Vielhauer and Jana Dittman.
