SlideShare une entreprise Scribd logo
1  sur  20
Fingerprint Recognition

Presented By:
Ranjit R, Banshpal
Outline
•
•
•
•
•
•
•
•

Introduction to biometrics
Fingerprint
What is Fingerprint Recognition?
Fingerprint recognition system
Advantages
Disadvantages
Applications
Conclusion
Biometrics
• Biometrics is the science and technology of
measuring and analyzing biological data
• Biometrics refers to technologies that
measure and analyze human body
characteristics, such as DNA, fingerprints,
eye retinas and irises, voice patterns ,facial
patterns and hand measurements, for
authentication purposes.
• The two categories of biometric identifiers
include :
 physiological characteristics.
 behavioral characteristics.
Physiological characteristics :
 Fingerprint
 face recognition
 DNA
 palm print
 hand geometry
 iris recognition(which has largely replaced retina)
 Odour /scent.

Behavioral characteristics :
 Gait
 voice
Fingerprint
• A fingerprint is the feature pattern of one
finger.
• It is the pattern of ridges and valleys (also
called furrows in the fingerprint literature)
on the surface of a fingertip.
• Each individual has unique fingerprints so
the uniqueness of a fingerprint is exclusively
determined by the local ridge characteristics
and their relationships
• These local ridge characteristics are not
evenly distributed.
Fig 1. A fingerprint image acquired by an Optical
Sensor
•
•

Fingerprints are distinguished by Minutiae, which are some abnormal
points on the ridges.
The two most prominent local ridge characteristics, called minutiae, are
1) ridge ending and
2) ridge bifurcation.
• A ridge ending is defined as the point
where a ridge ends abruptly.
• A ridge bifurcation is defined as the point
where
a ridge forks or diverges into branch
ridges.

Fig 2.ridge and valley
What is Fingerprint Recognition?
• Fingerprint recognition (sometimes
referred to as dactyloscopy) is the process
of comparing questioned and known
fingerprint against another fingerprint to
determine if the impressions are from the
same finger or palm.
• The fingerprint recognition problem can
be grouped into two sub-domains:
 Fingerprint verification :
Fingerprint verification is to verify the
authenticity of one person by his
fingerprint.
 Fingerprint identification:
Fingerprint identification is to specify one
person’s identity by his fingerprint(s).
Fig 3.Verification vs. Identification
FINGERPRINT RECOGNITION SYSTEM
• Fingerprint recognition system operates
in three stages:
(i) Fingerprint acquiring device
(ii) Minutia extraction and
(iii) Minutia matching

Fig 4. Fingerprint recognition system
1.Fingerprint acquisition:
For fingerprint acquisition, optical or semiconduct sensors are widely used. They
have high efficiency and acceptable
accuracy except for some cases that the
user’s finger is too dirty or dry.
2.Minutia extractor :
To implement a minutia extractor, a threestage approach is widely used by
researchers which are
 preprocessing
 minutia extraction and
 postprocessing stage.
Fig 5.Minutia extractor
• For the fingerprint image preprocessing
stage:
 Image enhancement
 Image binarization
 Image segmentation
• The job of minutiae extraction closes down
to two operations: Ridge Thinning, Minutiae
Marking,.
• In post-processing stage, false minutia are
removed and bifurcations is proposed to
unify terminations and bifurcations.
3.Minutiae Matching:
• Generally,
an
automatic
fingerprint
verification is achieved with minutia
matching (point pattern matching)instead of
a pixel-wise matching or a ridge pattern
matching of fingerprint images.
• The minutia matcher chooses any two
minutia as a reference minutia pair and then
match their associated ridges first.
• If the ridges match well, two fingerprint
images are aligned and matching is
conducted for all remaining minutia.
ADVANTAGES
Very high accuracy.
Easy to use.
Small storage space required for the
biometric template.
DISADVANTAGES
Dirt , grime and wounds .
Placement of finger.
Can be spoofed .
applications
Banking Security - ATM security,card
transaction
Physical Access Control (e.g. Airport)
Information System Security
National ID Systems
Passport control (INSPASS)
Prisoner, prison visitors, inmate control
Voting
Identification of Criminals
Identification of missing children
Secure E-Commerce (Still under research)
Conclusion
• The implemented minutia extraction
algorithm is accurate and fast in minutia
extraction.
• The algorithm also identifies the
unrecoverable corrupted regions in the
fingerprint and removes them from further
processing.
• This is a very important property because
such unrecoverable regions do appear in
some of the corrupted fingerprint images
and they are extremely harmful to minutiae
extraction.
Fingerprint recognition

Contenu connexe

Tendances

Biometrics iris recognition
Biometrics iris recognitionBiometrics iris recognition
Biometrics iris recognitionsunjaysahu
 
Finger print sensor and its application
Finger print sensor and its applicationFinger print sensor and its application
Finger print sensor and its applicationArnab Podder
 
biometric technology
biometric technologybiometric technology
biometric technologyAnmol Bagga
 
Pattern recognition Hand Geometry
Pattern recognition Hand GeometryPattern recognition Hand Geometry
Pattern recognition Hand GeometryMazin Alwaaly
 
Multimodal Biometric Systems
Multimodal Biometric SystemsMultimodal Biometric Systems
Multimodal Biometric SystemsPiyush Mittal
 
How fingerprint technology work
How fingerprint technology workHow fingerprint technology work
How fingerprint technology workAlisha Korpal
 
Biometrics Technology Intresting PPT
Biometrics Technology Intresting PPT Biometrics Technology Intresting PPT
Biometrics Technology Intresting PPT preeti tripathi
 
BIOMETRICS FINGER PRINT TECHNOLOGY
BIOMETRICS FINGER PRINT TECHNOLOGYBIOMETRICS FINGER PRINT TECHNOLOGY
BIOMETRICS FINGER PRINT TECHNOLOGYsathish sak
 
Ppt on use of biomatrix in secure e trasaction
Ppt on use of biomatrix in secure e trasactionPpt on use of biomatrix in secure e trasaction
Ppt on use of biomatrix in secure e trasactionDevyani Vaidya
 
Biometric slideshare
Biometric slideshareBiometric slideshare
Biometric slideshareprachi
 
Biometric security Presentation
Biometric security PresentationBiometric security Presentation
Biometric security PresentationPrabh Jeet
 
Face recognition ppt
Face recognition pptFace recognition ppt
Face recognition pptSantosh Kumar
 

Tendances (20)

Biometrics iris recognition
Biometrics iris recognitionBiometrics iris recognition
Biometrics iris recognition
 
Finger print sensor and its application
Finger print sensor and its applicationFinger print sensor and its application
Finger print sensor and its application
 
biometric technology
biometric technologybiometric technology
biometric technology
 
Finger Print Sensor
Finger Print SensorFinger Print Sensor
Finger Print Sensor
 
Fingerprint Based Biometric ATM Authentication System
Fingerprint Based Biometric ATM Authentication SystemFingerprint Based Biometric ATM Authentication System
Fingerprint Based Biometric ATM Authentication System
 
Pattern recognition Hand Geometry
Pattern recognition Hand GeometryPattern recognition Hand Geometry
Pattern recognition Hand Geometry
 
Multimodal Biometric Systems
Multimodal Biometric SystemsMultimodal Biometric Systems
Multimodal Biometric Systems
 
How fingerprint technology work
How fingerprint technology workHow fingerprint technology work
How fingerprint technology work
 
Biometrics Technology Intresting PPT
Biometrics Technology Intresting PPT Biometrics Technology Intresting PPT
Biometrics Technology Intresting PPT
 
Iris recognition seminar
Iris recognition seminarIris recognition seminar
Iris recognition seminar
 
Biometric technology
Biometric technologyBiometric technology
Biometric technology
 
Biometrics Technology In the 21st Century
Biometrics Technology In the 21st CenturyBiometrics Technology In the 21st Century
Biometrics Technology In the 21st Century
 
Bio-metrics Technology
Bio-metrics TechnologyBio-metrics Technology
Bio-metrics Technology
 
Keystroke dynamics
Keystroke dynamicsKeystroke dynamics
Keystroke dynamics
 
BIOMETRICS FINGER PRINT TECHNOLOGY
BIOMETRICS FINGER PRINT TECHNOLOGYBIOMETRICS FINGER PRINT TECHNOLOGY
BIOMETRICS FINGER PRINT TECHNOLOGY
 
Ppt on use of biomatrix in secure e trasaction
Ppt on use of biomatrix in secure e trasactionPpt on use of biomatrix in secure e trasaction
Ppt on use of biomatrix in secure e trasaction
 
Biometric slideshare
Biometric slideshareBiometric slideshare
Biometric slideshare
 
Biometrics final ppt
Biometrics final pptBiometrics final ppt
Biometrics final ppt
 
Biometric security Presentation
Biometric security PresentationBiometric security Presentation
Biometric security Presentation
 
Face recognition ppt
Face recognition pptFace recognition ppt
Face recognition ppt
 

En vedette

Fingerprint presentation
Fingerprint presentationFingerprint presentation
Fingerprint presentationrajarose89
 
Fingerprint Recognition Technique(PPT)
Fingerprint Recognition Technique(PPT)Fingerprint Recognition Technique(PPT)
Fingerprint Recognition Technique(PPT)Sandeep Kumar Panda
 
Fingerprint Identification
Fingerprint IdentificationFingerprint Identification
Fingerprint Identificationguest8cbcb02
 
Fingerprint Recognition Technique(PDF)
Fingerprint Recognition Technique(PDF)Fingerprint Recognition Technique(PDF)
Fingerprint Recognition Technique(PDF)Sandeep Kumar Panda
 
50409621003 fingerprint recognition system-ppt
50409621003  fingerprint recognition system-ppt50409621003  fingerprint recognition system-ppt
50409621003 fingerprint recognition system-pptMohankumar Ramachandran
 
Fingerprint classification rules
Fingerprint classification rulesFingerprint classification rules
Fingerprint classification rulesKUL2700
 
fingerprint classification systems Henry and NCIC
fingerprint classification systems Henry and NCICfingerprint classification systems Henry and NCIC
fingerprint classification systems Henry and NCICKUL2700
 
High protection ATM system with fingerprint identification technology
High protection ATM system with fingerprint identification technologyHigh protection ATM system with fingerprint identification technology
High protection ATM system with fingerprint identification technologyAlfred Oboi
 
Biometric's final ppt
Biometric's final pptBiometric's final ppt
Biometric's final pptAnkita Vanage
 
Fingerprint based transaction system
Fingerprint based transaction systemFingerprint based transaction system
Fingerprint based transaction systemsagar solanky
 
Fingerprinting in India
Fingerprinting in IndiaFingerprinting in India
Fingerprinting in IndiaShantanu Basu
 
Fingerprint Classification- Loop Patterns
Fingerprint Classification- Loop PatternsFingerprint Classification- Loop Patterns
Fingerprint Classification- Loop PatternsJury Rocamora
 
Atm using fingerprint
Atm using fingerprintAtm using fingerprint
Atm using fingerprintAnIsh Kumar
 
Biometrics/fingerprint sensors
Biometrics/fingerprint sensorsBiometrics/fingerprint sensors
Biometrics/fingerprint sensorsJeffrey Funk
 

En vedette (20)

Fingerprint presentation
Fingerprint presentationFingerprint presentation
Fingerprint presentation
 
Fingerprint Recognition Technique(PPT)
Fingerprint Recognition Technique(PPT)Fingerprint Recognition Technique(PPT)
Fingerprint Recognition Technique(PPT)
 
Fingerprint
FingerprintFingerprint
Fingerprint
 
Fingerprint Identification
Fingerprint IdentificationFingerprint Identification
Fingerprint Identification
 
Fingerprint Recognition Technique(PDF)
Fingerprint Recognition Technique(PDF)Fingerprint Recognition Technique(PDF)
Fingerprint Recognition Technique(PDF)
 
Fingerprint Pattern
Fingerprint PatternFingerprint Pattern
Fingerprint Pattern
 
50409621003 fingerprint recognition system-ppt
50409621003  fingerprint recognition system-ppt50409621003  fingerprint recognition system-ppt
50409621003 fingerprint recognition system-ppt
 
Fingerprint classification rules
Fingerprint classification rulesFingerprint classification rules
Fingerprint classification rules
 
fingerprint classification systems Henry and NCIC
fingerprint classification systems Henry and NCICfingerprint classification systems Henry and NCIC
fingerprint classification systems Henry and NCIC
 
High protection ATM system with fingerprint identification technology
High protection ATM system with fingerprint identification technologyHigh protection ATM system with fingerprint identification technology
High protection ATM system with fingerprint identification technology
 
Biometric's final ppt
Biometric's final pptBiometric's final ppt
Biometric's final ppt
 
Fingerprint based transaction system
Fingerprint based transaction systemFingerprint based transaction system
Fingerprint based transaction system
 
Fingerprinting in India
Fingerprinting in IndiaFingerprinting in India
Fingerprinting in India
 
Whorl Patterns
Whorl PatternsWhorl Patterns
Whorl Patterns
 
Fingerprint Classification- Loop Patterns
Fingerprint Classification- Loop PatternsFingerprint Classification- Loop Patterns
Fingerprint Classification- Loop Patterns
 
Atm using fingerprint
Atm using fingerprintAtm using fingerprint
Atm using fingerprint
 
Biometrics/fingerprint sensors
Biometrics/fingerprint sensorsBiometrics/fingerprint sensors
Biometrics/fingerprint sensors
 
Ridge counting-and-tracing
Ridge counting-and-tracingRidge counting-and-tracing
Ridge counting-and-tracing
 
Classification
ClassificationClassification
Classification
 
Finger reader
Finger readerFinger reader
Finger reader
 

Similaire à Fingerprint recognition

sagarppt111111-150929182421-lva1-app6891.pptx
sagarppt111111-150929182421-lva1-app6891.pptxsagarppt111111-150929182421-lva1-app6891.pptx
sagarppt111111-150929182421-lva1-app6891.pptxCoreGaming3
 
Fingerprint Authentication Seminar.pptx
Fingerprint Authentication  Seminar.pptxFingerprint Authentication  Seminar.pptx
Fingerprint Authentication Seminar.pptxsahoosabyasachi000
 
Biometics technology
Biometics technologyBiometics technology
Biometics technologyPraween Lakra
 
Fingerprint recognition using minutiae based feature
Fingerprint recognition using minutiae based featureFingerprint recognition using minutiae based feature
Fingerprint recognition using minutiae based featurevarsha mohite
 
2019001791_Fingerprint_Authentication.pptx
2019001791_Fingerprint_Authentication.pptx2019001791_Fingerprint_Authentication.pptx
2019001791_Fingerprint_Authentication.pptxTrushaKyada
 
GANNON UNIVERSITYELECTR.docx
                                     GANNON UNIVERSITYELECTR.docx                                     GANNON UNIVERSITYELECTR.docx
GANNON UNIVERSITYELECTR.docxjoyjonna282
 
Fingerprint scanner
Fingerprint scannerFingerprint scanner
Fingerprint scannerAusaf khan
 
Fingerprint recognition (term paper) Project
Fingerprint recognition (term paper) Project Fingerprint recognition (term paper) Project
Fingerprint recognition (term paper) Project Abhishek Walia
 
Fingerprint Minutiae Extraction and Compression using LZW Algorithm
Fingerprint Minutiae Extraction and Compression using LZW AlgorithmFingerprint Minutiae Extraction and Compression using LZW Algorithm
Fingerprint Minutiae Extraction and Compression using LZW Algorithmijsrd.com
 
Biometrics fingerprint
Biometrics fingerprintBiometrics fingerprint
Biometrics fingerprintSagar Verma
 
Fingerprint Analaysis
Fingerprint AnalaysisFingerprint Analaysis
Fingerprint AnalaysisANIKLAL2
 
BIOMETRIC IDENTIFICATION IN ATM’S PPT
BIOMETRIC IDENTIFICATION IN ATM’S  PPTBIOMETRIC IDENTIFICATION IN ATM’S  PPT
BIOMETRIC IDENTIFICATION IN ATM’S PPTsravya raju
 
Bio-Metric Technology
Bio-Metric TechnologyBio-Metric Technology
Bio-Metric Technologyshyampariyar
 
Bio-Metric Technology
Bio-Metric TechnologyBio-Metric Technology
Bio-Metric Technologyshyampariyar
 
novel method of identifying fingerprint using minutiae matching in biometric ...
novel method of identifying fingerprint using minutiae matching in biometric ...novel method of identifying fingerprint using minutiae matching in biometric ...
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
 
SEMINAR FIRST.pptx
SEMINAR FIRST.pptxSEMINAR FIRST.pptx
SEMINAR FIRST.pptxAlenJames14
 

Similaire à Fingerprint recognition (20)

sagarppt111111-150929182421-lva1-app6891.pptx
sagarppt111111-150929182421-lva1-app6891.pptxsagarppt111111-150929182421-lva1-app6891.pptx
sagarppt111111-150929182421-lva1-app6891.pptx
 
Fingerprint Authentication Seminar.pptx
Fingerprint Authentication  Seminar.pptxFingerprint Authentication  Seminar.pptx
Fingerprint Authentication Seminar.pptx
 
Seminar
SeminarSeminar
Seminar
 
Presentation suresh maurya
Presentation suresh mauryaPresentation suresh maurya
Presentation suresh maurya
 
Biometics technology
Biometics technologyBiometics technology
Biometics technology
 
Fingerprint recognition using minutiae based feature
Fingerprint recognition using minutiae based featureFingerprint recognition using minutiae based feature
Fingerprint recognition using minutiae based feature
 
2019001791_Fingerprint_Authentication.pptx
2019001791_Fingerprint_Authentication.pptx2019001791_Fingerprint_Authentication.pptx
2019001791_Fingerprint_Authentication.pptx
 
GANNON UNIVERSITYELECTR.docx
                                     GANNON UNIVERSITYELECTR.docx                                     GANNON UNIVERSITYELECTR.docx
GANNON UNIVERSITYELECTR.docx
 
Fingerprint scanner
Fingerprint scannerFingerprint scanner
Fingerprint scanner
 
Fingerprint recognition (term paper) Project
Fingerprint recognition (term paper) Project Fingerprint recognition (term paper) Project
Fingerprint recognition (term paper) Project
 
Biometrics
Biometrics Biometrics
Biometrics
 
Dip fingerprint
Dip fingerprintDip fingerprint
Dip fingerprint
 
Fingerprint Minutiae Extraction and Compression using LZW Algorithm
Fingerprint Minutiae Extraction and Compression using LZW AlgorithmFingerprint Minutiae Extraction and Compression using LZW Algorithm
Fingerprint Minutiae Extraction and Compression using LZW Algorithm
 
Biometrics fingerprint
Biometrics fingerprintBiometrics fingerprint
Biometrics fingerprint
 
Fingerprint Analaysis
Fingerprint AnalaysisFingerprint Analaysis
Fingerprint Analaysis
 
BIOMETRIC IDENTIFICATION IN ATM’S PPT
BIOMETRIC IDENTIFICATION IN ATM’S  PPTBIOMETRIC IDENTIFICATION IN ATM’S  PPT
BIOMETRIC IDENTIFICATION IN ATM’S PPT
 
Bio-Metric Technology
Bio-Metric TechnologyBio-Metric Technology
Bio-Metric Technology
 
Bio-Metric Technology
Bio-Metric TechnologyBio-Metric Technology
Bio-Metric Technology
 
novel method of identifying fingerprint using minutiae matching in biometric ...
novel method of identifying fingerprint using minutiae matching in biometric ...novel method of identifying fingerprint using minutiae matching in biometric ...
novel method of identifying fingerprint using minutiae matching in biometric ...
 
SEMINAR FIRST.pptx
SEMINAR FIRST.pptxSEMINAR FIRST.pptx
SEMINAR FIRST.pptx
 

Plus de ranjit banshpal

Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...
Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...
Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...ranjit banshpal
 
SECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHES
SECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHESSECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHES
SECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHESranjit banshpal
 
Secure Image Retrieval based on Hybrid Features and Hashes
Secure Image Retrieval based on Hybrid Features and HashesSecure Image Retrieval based on Hybrid Features and Hashes
Secure Image Retrieval based on Hybrid Features and Hashesranjit banshpal
 
Data mining technique for classification and feature evaluation using stream ...
Data mining technique for classification and feature evaluation using stream ...Data mining technique for classification and feature evaluation using stream ...
Data mining technique for classification and feature evaluation using stream ...ranjit banshpal
 
Parallelization using open mp
Parallelization using open mpParallelization using open mp
Parallelization using open mpranjit banshpal
 
Face recognition technology
Face recognition technologyFace recognition technology
Face recognition technologyranjit banshpal
 
using big-data methods analyse the Cross platform aviation
 using big-data methods analyse the Cross platform aviation using big-data methods analyse the Cross platform aviation
using big-data methods analyse the Cross platform aviationranjit banshpal
 
E mail image spam filtering techniques
E mail image spam filtering techniquesE mail image spam filtering techniques
E mail image spam filtering techniquesranjit banshpal
 

Plus de ranjit banshpal (15)

Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...
Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...
Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...
 
SECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHES
SECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHESSECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHES
SECURE IMAGE RETRIEVAL BASED ON HYBRID FEATURES AND HASHES
 
Secure Image Retrieval based on Hybrid Features and Hashes
Secure Image Retrieval based on Hybrid Features and HashesSecure Image Retrieval based on Hybrid Features and Hashes
Secure Image Retrieval based on Hybrid Features and Hashes
 
LCT in day2 day life
LCT in day2 day lifeLCT in day2 day life
LCT in day2 day life
 
“Web crawler”
“Web crawler”“Web crawler”
“Web crawler”
 
Data mining technique for classification and feature evaluation using stream ...
Data mining technique for classification and feature evaluation using stream ...Data mining technique for classification and feature evaluation using stream ...
Data mining technique for classification and feature evaluation using stream ...
 
Parallelization using open mp
Parallelization using open mpParallelization using open mp
Parallelization using open mp
 
Face recognition technology
Face recognition technologyFace recognition technology
Face recognition technology
 
using big-data methods analyse the Cross platform aviation
 using big-data methods analyse the Cross platform aviation using big-data methods analyse the Cross platform aviation
using big-data methods analyse the Cross platform aviation
 
E mail image spam filtering techniques
E mail image spam filtering techniquesE mail image spam filtering techniques
E mail image spam filtering techniques
 
Hybrid encryption
Hybrid encryption Hybrid encryption
Hybrid encryption
 
Autocorrelators1
Autocorrelators1Autocorrelators1
Autocorrelators1
 
Static Networks
Static NetworksStatic Networks
Static Networks
 
Ranjitbanshpal
RanjitbanshpalRanjitbanshpal
Ranjitbanshpal
 
Ranjitbanshpal1
Ranjitbanshpal1Ranjitbanshpal1
Ranjitbanshpal1
 

Dernier

Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 

Dernier (20)

Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 

Fingerprint recognition

  • 2. Outline • • • • • • • • Introduction to biometrics Fingerprint What is Fingerprint Recognition? Fingerprint recognition system Advantages Disadvantages Applications Conclusion
  • 3. Biometrics • Biometrics is the science and technology of measuring and analyzing biological data • Biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns ,facial patterns and hand measurements, for authentication purposes. • The two categories of biometric identifiers include :  physiological characteristics.  behavioral characteristics.
  • 4. Physiological characteristics :  Fingerprint  face recognition  DNA  palm print  hand geometry  iris recognition(which has largely replaced retina)  Odour /scent. Behavioral characteristics :  Gait  voice
  • 5. Fingerprint • A fingerprint is the feature pattern of one finger. • It is the pattern of ridges and valleys (also called furrows in the fingerprint literature) on the surface of a fingertip. • Each individual has unique fingerprints so the uniqueness of a fingerprint is exclusively determined by the local ridge characteristics and their relationships • These local ridge characteristics are not evenly distributed.
  • 6. Fig 1. A fingerprint image acquired by an Optical Sensor • • Fingerprints are distinguished by Minutiae, which are some abnormal points on the ridges. The two most prominent local ridge characteristics, called minutiae, are 1) ridge ending and 2) ridge bifurcation.
  • 7. • A ridge ending is defined as the point where a ridge ends abruptly. • A ridge bifurcation is defined as the point where a ridge forks or diverges into branch ridges. Fig 2.ridge and valley
  • 8. What is Fingerprint Recognition? • Fingerprint recognition (sometimes referred to as dactyloscopy) is the process of comparing questioned and known fingerprint against another fingerprint to determine if the impressions are from the same finger or palm.
  • 9. • The fingerprint recognition problem can be grouped into two sub-domains:  Fingerprint verification : Fingerprint verification is to verify the authenticity of one person by his fingerprint.  Fingerprint identification: Fingerprint identification is to specify one person’s identity by his fingerprint(s).
  • 10. Fig 3.Verification vs. Identification
  • 11. FINGERPRINT RECOGNITION SYSTEM • Fingerprint recognition system operates in three stages: (i) Fingerprint acquiring device (ii) Minutia extraction and (iii) Minutia matching Fig 4. Fingerprint recognition system
  • 12. 1.Fingerprint acquisition: For fingerprint acquisition, optical or semiconduct sensors are widely used. They have high efficiency and acceptable accuracy except for some cases that the user’s finger is too dirty or dry. 2.Minutia extractor : To implement a minutia extractor, a threestage approach is widely used by researchers which are  preprocessing  minutia extraction and  postprocessing stage.
  • 14. • For the fingerprint image preprocessing stage:  Image enhancement  Image binarization  Image segmentation • The job of minutiae extraction closes down to two operations: Ridge Thinning, Minutiae Marking,. • In post-processing stage, false minutia are removed and bifurcations is proposed to unify terminations and bifurcations.
  • 15. 3.Minutiae Matching: • Generally, an automatic fingerprint verification is achieved with minutia matching (point pattern matching)instead of a pixel-wise matching or a ridge pattern matching of fingerprint images. • The minutia matcher chooses any two minutia as a reference minutia pair and then match their associated ridges first. • If the ridges match well, two fingerprint images are aligned and matching is conducted for all remaining minutia.
  • 16. ADVANTAGES Very high accuracy. Easy to use. Small storage space required for the biometric template.
  • 17. DISADVANTAGES Dirt , grime and wounds . Placement of finger. Can be spoofed .
  • 18. applications Banking Security - ATM security,card transaction Physical Access Control (e.g. Airport) Information System Security National ID Systems Passport control (INSPASS) Prisoner, prison visitors, inmate control Voting Identification of Criminals Identification of missing children Secure E-Commerce (Still under research)
  • 19. Conclusion • The implemented minutia extraction algorithm is accurate and fast in minutia extraction. • The algorithm also identifies the unrecoverable corrupted regions in the fingerprint and removes them from further processing. • This is a very important property because such unrecoverable regions do appear in some of the corrupted fingerprint images and they are extremely harmful to minutiae extraction.