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A Comparative Analysis Of Biometric Classification Technique

Electrical Electronics Engineering | Industrial Physics | Physics

A comparative analysis of biometric classification techniques involves an in-depth examination of various methodologies employed in the identification and verification of individuals based on unique physiological or behavioral characteristics. Biometric systems, leveraging features like fingerprints, iris patterns, and facial recognition, play a crucial role in enhancing security and streamlining authentication processes. The evaluation of these techniques encompasses scrutinizing their effectiveness, accuracy, and adaptability across diverse applications. Differentiating factors such as scalability, robustness, and computational efficiency become pivotal considerations in discerning the optimal biometric classification approach. Additionally, the exploration of advancements in machine learning and pattern recognition within the biometric domain further enriches the discourse, emphasizing the need for continual refinement and innovation in this dynamic field.

Biometrics is the use of a person’s unique physiological, behavioral, and morphological characteristic to provide positive personal identification. Traditionally the use of biometric devices has improved our ability to provide authenticated access to physical installations. Biometric systems that are currently available today examine fingerprints, handprints, iris and retina patterns, and face. Systems that are close to biometrics but are not classified as such are behavioral systems such as voice, signature and keystroke systems. They test patterns of behavior not parts of the body. Over the next few years, the use of biometrics will continue to grow and become much more commonplace.

Today the core technologies have evolved and the cost of the equipment is going down dramatically due to the integration and increasing processing power. Certain applications of biometric identification technology are now cost-effective, reliable and highly accurate. As a result, there is no technological or financial barrier for stepping from the pilot projects to widespread deployment. This paper is an attempt to highlights the biometric technologies in concern with human interface.

TABLE OF CONTENTS

COVER PAGE

TITLE PAGE

APPROVAL PAGE

DEDICATION

ACKNOWELDGEMENT

ABSTRACT

CHAPTER ONE

1.0      INTRODUCTION

1.1      BACKGROUND OF THE PROJECT

  • PROBLEM STATEMENT
  • AIM OF THE PROJECT
  • OBJECTIVE OF THE PROJECT
  • PURPOSE OF THE PROJECT
  • ADVANTAGES OF BIOMETRIC AUTHENTICATION
  • DISADVANTAGES OF BIOMETRIC AUTHENTICATION
  • RESEARCH QUESTIONS

CHAPTER TWO

LITERATURE REVIEW

  • OVERVIEW OF THE STUDY
  • REVIEW OF BIOMETRIC FUNCTIONALITY
  • HISTORICAL BACKGROUND OF BIOMETRIC
  • ISSUES AND CONCERNS OF BIOMETRICS

CHAPTER THREE

3.0     CONSTRUCTION METHODOLOGY

3.1      GENERAL BIOMETRIC BLOCK DIAGRAM

3.2     WORKING PRINCIPLE OF BIOMETRICS

3.3      DIFFERENCE BETWEEN IDENTIFICATION AND VERIFICATION

3.4 DIFFERENCE BETWEEN PHYSIOLOGICAL AND BEHAVIORAL

3.5 BIOMETRIC TECHNOLOGIES

3.6   COMMON BIOMETRIC FEATURES USED FOR AUTHENTICATION

CHAPTER FOUR

  • BIOMETRIC TESTING
  • PERFORMANCE METRICS FOR BIOMETRIC SYSTEMS
  • AREA OF BIOMETRIC APPLICATIONS

CHAPTER FIVE

  • CONCLUSION
  • REFERENCES

CHAPTER ONE

1.0                                                        INTRODUCTION

1.1                                           BACKGROUND OF THE STUDY

Biometrics refers to the automatic identification of a person based on his or her physiological or behavioral characteristics. This identification method is preferred over traditional methods involving passwords and personal identification numbers (PINs) for several reasons, including the person to be identified is required to be physically present at the point of identification and/or identification based on biometric techniques obviates the need to remember a password or carry a token. With the increased use of computers as vehicles of information technology, restricting access to sensitive/personal data is necessary. By replacing PINs, biometric techniques can potentially prevent unauthorized access to or fraudulent use of the following:

  1. ATMs
  2. Cellular phones
  3. Smart cards
  4. Desktop PCs
  5. Workstations
  6. Computer networks

PINs and passwords may be forgotten and token-based identification methods such as passports and driver’s licenses may be forged, stolen, or lost. Thus, biometric systems of identification are enjoying a new interest. Various types of biometric systems are being used for real-time identification.

The most popular are based on face recognition and fingerprint matching; however, other biometric systems use iris and retinal scans, speech, facial feature comparisons and facial thermograms, and hand geometry. [2] [10]

1.1                                      AIM OF THE STUDY

The main aim of this work is to highlight and discuss different types of biometric based on their function, operation, characteristic and their security accuracy level.

1.2                              OBJECTIVE OF THE STUDY

At the end of this work student involved shall be able to list, learn and understand different types of biometrics based on their function, operation, characteristic and their security accuracy level.

1.3                                 PURPOSE OF THE STUDY

The purpose of carrying out this study is to expose the ready on the most accuracy and economical type of biometric to use.

1.4                               STATEMENT OF PROBELM

Because of the insecurity and lives and property we notice everyday in our society, that an intruder can easily get access to someone house and went away with their property when no one is watching or live traiten agents can easily enter someone house and kill the owner of the house. Even in our public places we also discover that malpractices is everywhere such as in our politics today. There are a lot of malpractice such as in voters registration, when voters will go ahead and register more once in other for him or her to have the ability to vote more than once in the same of different polling unit. We see insecurity of lives and properties and malpractices everyday of our lives. However the invention of biometric is to secure lives and properties and to reduce crime and corruption.

1.5                            ADVANTAGES OF BIOMETRICS

  1. Biometric traits cannot be lost or forgotten (while passwords can).
  2. Biometric traits are difficult to copy, share and distribute (passwords can be announced in crackers‟ websites).
  3. They require the person being authenticated to be present at the time and point of authentication. [1]

1.6       DISADVANTAGES OF BIOMETRIC AUTHENTICATION

A biometric authentication system seems to be an excellent solution to authentication problems; however biometric authentication has some weaknesses:

 

  1. Education required: While an increasing number of available technologies are “plug and play”, they still require some user education. Users need to know how to position their finger, face, and To be clearly read. Additionally, implementers will need training on proper installation and maintenance of biometric systems.
  2. Expensive: While there are several models of fingerprint, voice, and signature verification available in the higher range, a majority of technologies are still closer to the $500 mark. Unless biometrics can get below the cost of password administration costs, business will get below the cost of password administration costs, business will not chose to
  • Affected by environment and disease: It is not the case that your fingerprints, face, or voice remain constant from day to day, small fluctuations (cold or moist hands for fingerprint scanners, different ambient lighting for face recognition, and background noise for voice authentication) can block the devices. Setting the sensitivity lower makes the product more forgiving but increases the odds of a false positive a faker logging on as someone else. Higher sensitivity means greater security, but it also means that an authorized user may be erroneously
  1. Harmful: The method of obtaining a retinal scan is personally invasive – a laser light (or other coherent light source) must be directed through the cornea of the eye and uses an infrared light source to highlight the biometric pattern. This can harm an individual’s eye. [2]

1.7                                  RESEARCH QUESTIONS

At the end of this study, students involved shall be able to answer the following question that is related to this work:

  1. What are examples of biometrics?
  2. What is biometric issue?
  • What is biometric process?
  1. What is a biometric census?
  2. What is the purpose of biometrics?
  3. Why do we use biometrics?
  • What are the benefits of biometrics?

Which of these are examples biometrics?

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Biometric Classification Technique:

Biometric classification techniques are methods used to identify and authenticate individuals based on their unique physiological or behavioral characteristics. These techniques have gained widespread adoption in various applications such as security systems, access control, identity verification, and forensic analysis. The primary goal of biometric classification is to accurately distinguish between different individuals by analyzing their distinct biometric traits. Let’s explore some common biometric classification techniques:

  1. Fingerprint Recognition: Fingerprint recognition is one of the oldest and most widely used biometric classification techniques. It involves capturing an individual’s fingerprint image and analyzing its unique ridge patterns, bifurcations, and minutiae points. Matching algorithms compare these features to a database of stored fingerprints to determine identity.
  2. Facial Recognition: Facial recognition technology analyzes the unique characteristics of a person’s face to verify or identify them. It involves capturing facial images or videos and extracting features such as the distance between the eyes, nose shape, and the contour of the face. Advanced algorithms then compare these features with stored templates to make a match.
  3. Iris Recognition: Iris recognition relies on the unique patterns found in the iris of the eye. It uses specialized cameras to capture high-resolution images of the iris and extracts features such as iris texture, crypts, and furrows. Pattern-matching algorithms then compare these features to stored templates for identification.
  4. Voice Recognition: Voice recognition, also known as speaker recognition, identifies individuals based on the characteristics of their voice. It involves capturing spoken words or phrases and analyzing various features such as pitch, frequency, and vocal tract length. Pattern-matching algorithms then compare these features to stored voiceprints to authenticate the speaker.
  5. Hand Geometry Recognition: Hand geometry recognition measures and analyzes the physical characteristics of an individual’s hand, including the size, shape, and proportions of the hand and fingers. It typically involves placing the hand on a scanner or sensor and capturing images or measurements for comparison with stored templates.
  6. Vein Pattern Recognition: Vein pattern recognition utilizes near-infrared light to capture images of the vein patterns beneath the skin’s surface, typically in the hand or finger. These patterns are unique to each individual and can be used for biometric identification and authentication.
  7. Gait Analysis: Gait analysis examines the unique way individuals walk or move. It involves capturing video footage of a person’s gait and extracting features such as stride length, cadence, and foot pressure patterns. Machine learning algorithms can then analyze these features to identify individuals based on their gait patterns.
  8. DNA Matching: DNA matching involves analyzing an individual’s unique genetic code to verify identity or establish relationships. While DNA analysis is primarily used in forensic investigations and paternity testing, it can also be considered a biometric classification technique due to the uniqueness of each person’s DNA.
  9. Electrocardiogram (ECG) Recognition: ECG recognition analyzes the unique electrical activity of an individual’s heart to verify their identity. It involves capturing ECG signals using specialized sensors and extracting features such as heart rate variability and waveform patterns for authentication purposes.
  10. Keystroke Dynamics: Keystroke dynamics measures the unique typing patterns of individuals, including the rhythm, speed, and pressure applied to keys. It involves capturing keystroke data during typing tasks and using statistical or machine learning techniques to distinguish between users based on their typing behavior.

These are just a few examples of biometric classification techniques, each with its advantages, limitations, and applications. As technology continues to advance, biometrics is expected to play an increasingly significant role in security, identity management, and personalization across various industries. However, it’s essential to address privacy concerns and ensure proper safeguards are in place to protect individuals’ biometric data from misuse or unauthorized access