SlideShare ist ein Scribd-Unternehmen logo
1 von 30
Fingerprint Identification
Chapter 10 Fingerprint Classification
Systems
LawTech Custom Publishing, Inc.
Copyright 2005
Overview
 Fingerprint

classification describes an
individual’s fingerprints
 Fingerprint classifications use codes on
fingerprint cards to file and retrieve
manual filing system

Fingerprint
Identification
Chapter Objectives
 Understand

classification of fingerprint
card using Henry system
 Understand classification of fingerprint
card using NCIC system

Fingerprint
Identification
Introduction
 Henry

System of Classification used
for most of 20th Century in U.S. and
most English speaking countries
Named after Sir Edward Henry of
England
 Developed system during late 1800s and
early 1900s


Fingerprint
Identification
Introduction (cont.)
 National

Crime Information Center
(NCIC) Classification System
Computerized database used in U.S.
 Allows law enforcement agencies
nationwide access to wanted bulletins
and warrants for outstanding suspects and
fugitives


Fingerprint
Identification
Introduction (cont.)
 NCIC

Classification System (cont.)

Short cut to Henry System for quick
evaluation and possible elimination of
individuals as suspects
 Further investigation required for
individuals that match NCIC
classification including a full fingerprint
search


Fingerprint
Identification
Introduction (cont.)
Both classification systems based on 10
fingers
 Automation of fingerprint files will render
manual classification filing systems
obsolete
 Knowledge of fingerprint patterns and
anatomy of hand useful and valuable
information for fingerprint examiner


Fingerprint
Identification
Introduction (cont.)



Fingerprint classification not the same as
fingerprint identification
Classification uses class characteristics to group
like fingerprints for filing and retrieval




Many people have same fingerprint classification

Fingerprint identification uses individual
characteristics to individualize a print to a specific
person
Fingerprint
Identification
Introduction (cont.)



Fingerprint classification of suspect may appear
on wanted bulletins and arrest warrants
Law enforcement can use information as a
screening tool to eliminate persons being sought




Classifications that are quite different could be used to
exclude suspected individuals
Classifications that are similar or match would be
submitted to agency holding warrant to compare to
actual fingerprints
Fingerprint
Identification
The Henry System of Classification


Blocking Out the Fingerprint Card



Determine pattern type in each finger block
Indicate pattern using symbols at the bottom middle or
right side of each finger box on fingerprint card
 Plain Arch → A
 Tented Arch → T
 Ulnar Loop → / in direction of the loop
 Radial Loop → R
 All Whorls → W
Fingerprint
Identification
The Henry System of Classification
(cont.)
 Index

finger boxes

Use capital letter of pattern type, except
for ulnar loop
 Ulnar loops designated by a diagonal line
slanting in the direction of loop


 All


other finger boxes

Use small letter to indicate pattern type,
except for ulnar loop (same as above)
Fingerprint
Identification
The Henry System of Classification
(cont.)


Loop type patterns




Place ridge count in top right hand corner of finger box

Whorl patterns




Indicate type in upper right corner of finger box
 P – plain
 C – central pocket
 Small d – double loop
 X – accidental whorl
Indicate tracing (I, M, O) next to letter designating
whorl pattern in top right corner of finger box
Fingerprint
Identification
The Henry System of Classification
(cont.)
Blocked out
fingerprint
card

Fingerprint
Identification
Six Divisions of Fingerprint
Classification
 Primary


Only whorl patterns have value
Finger #1 and #2 → 6
Finger #3 and #4 → 8
Finger #5 and #6 → 4
Finger #7 and #8 → 2
Finger #9 and #10 → 1
Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)
Primary Chart

Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)
Whorl values for odd number fingers are
added up, plus 1 for the total denominator
 Whorl values for even number fingers are
added up, plus 1 for the total numerator
 Primary reported as a fraction
Total numerator (top, even numbered
boxes) over the denominator (bottom,
odd numbered boxes)


Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)
Primary = 1 indicates no whorl patterns
 Primary = 32 and over indicates all whorl
patterns
 Total of 1,024 possible primary
classifications


Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)
 Secondary

Indicated in fraction form
Capital letter of pattern type for right
index (#2) over left index (#7) fingers
 U – ulnar loops
 Example: W/U indicates right index
finger is whorl, and left index finger is
ulanr loop


Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)


Small Letter Group Secondary
Applies to fingerprint cards that have a plain
arch, tented arch, or radial loop
 Excludes index fingers
 Location of plain arch, tented arch or radial
loops by small letter a, t, or r indicated to right
or left of secondary
 Example: small letter a to the left of the top
capital letter of the secondary indicates that a
plain arch is in right thumb


Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)


Dashes used to indicate position of
fingers not containing a plain arch, tented
arch or radial loop in the middle, ring or
little fingers to the left of the secondary
Example: - a in the denominator
(lower) line of the fraction to the right
of the capital letter secondary indicate
a plain arch in left little finger
Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)




Print cards with small letter groups do not need
to add the sub-secondary or major divisions to
the classification formula

Sub-secondary


Value of ridge counts or tracings of right index
(2), right middle (3), and right ring (4) fingers
over the values of the left index (7), left middle
(8), and left ring (9) fingers
Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)
 Key


Ridge count of first loop, excluding little
fingers

 Major


Value of ridge counts or tracings of right
and left thumbs
Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)
 Final


Ridge count of loop in right little finger
(5)
If right little finger #5 is not a loop, use
left little finger #10
If finger #10 is not a loop then there is
no final value
Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)


VALUES TABLE FOR LOOP RIDGE COUNT
CONVERSIONS









Index fingers 1-9 = I; 10 or more = O
Middle fingers 1-10 = I; 11 or more = O
Ring fingers
1-13 = I; 14 or more = O
Right thumb
1-11 = S; 12-16 = M; 17 or more = L
 when the left thumb ridge count is 16 or less
Right thumb
1-17 = S; 18-22 = M; 23 or more = L
 when the left thumb ridge count is 17 or more
Left thumb
1-11 = S; 12-16 = M; 17 or more = L
Fingerprint
Identification
Six Divisions of Fingerprint
Classification (cont.)

Fingerprint card
showing Henry
Classification

Fingerprint
Identification
The NCIC Classification System


Two letter or number codes used to identify
fingerprint pattern type
Plain arch → AA
 Tented arch → TT
 Ulnar loop → ridge count
 Radial loop → ridge count plus 50
 Plain whorl → P, plus the tracing I,M, or O


Fingerprint
Identification
The NCIC Classification System (cont.)


Two letter or number codes (cont.)
Central Pocket → loop C, plus the tracing I, M,
or O
 Double loop whorl → small d plus tracing I, M,
or O
 Accidental → X, plus the tracing I, M, or O
 Missing finger → XX
 Scar or mutilation → SR


Fingerprint
Identification
The NCIC Classification System (cont.)
 Fingers

listed in order of finger
numbers on a ten-finger fingerprint
card
Right thumb is number 1
 Example: A5612CIPM dM661415XX
 Classification placed in twenty small
boxes that appear just above the
fingerprint boxes


Fingerprint
Identification
The NCIC Classification System (cont.)

Fingerprint card
showing NCIC
Classification

Fingerprint
Identification
Discussion Questions
“Blocking out” refers to the marking pattern
types, ridge counts, and whorl type and
tracing on a fingerprint card. True or False?
 A fingerprint card with a primary
classification of 1 over 1 would contain no
whorls. True or False?
 What fingerprint classification is used for
an electronic warrant?


Fingerprint
Identification

Weitere ähnliche Inhalte

Was ist angesagt?

Fingerprint - Everything You Need To Know About Fingerprints
Fingerprint - Everything You Need To Know About FingerprintsFingerprint - Everything You Need To Know About Fingerprints
Fingerprint - Everything You Need To Know About FingerprintsSwaroopSonone
 
Crime scene sketching basics
Crime scene sketching basicsCrime scene sketching basics
Crime scene sketching basicsnruhland
 
introduction to forensic ballistics
introduction to forensic ballisticsintroduction to forensic ballistics
introduction to forensic ballisticschaitra pradeep
 
Fingerprint Identification
Fingerprint IdentificationFingerprint Identification
Fingerprint Identificationguest8cbcb02
 
Examination of glass
Examination of glassExamination of glass
Examination of glassrakesh mishra
 
Automated Fingerprint Identification System (AFIS)
Automated Fingerprint Identification System (AFIS)Automated Fingerprint Identification System (AFIS)
Automated Fingerprint Identification System (AFIS)Alok Yadav
 
restoration of toolmarks
restoration of toolmarksrestoration of toolmarks
restoration of toolmarksHemant Jain
 
Tool marks and its forensic significance
Tool marks and its forensic significanceTool marks and its forensic significance
Tool marks and its forensic significanceStina14
 
Types of bullets
Types of bulletsTypes of bullets
Types of bulletsKetan Patil
 
Poroscopy and edgeoscopy
Poroscopy and edgeoscopyPoroscopy and edgeoscopy
Poroscopy and edgeoscopykiran malik
 
Handwriting and Document Examination
Handwriting and Document ExaminationHandwriting and Document Examination
Handwriting and Document ExaminationPrashant Mehta
 
Forensic examination of signature
Forensic examination of signatureForensic examination of signature
Forensic examination of signatureShivangiRathore8
 

Was ist angesagt? (20)

Fingerprint - Everything You Need To Know About Fingerprints
Fingerprint - Everything You Need To Know About FingerprintsFingerprint - Everything You Need To Know About Fingerprints
Fingerprint - Everything You Need To Know About Fingerprints
 
Crime scene sketching basics
Crime scene sketching basicsCrime scene sketching basics
Crime scene sketching basics
 
introduction to forensic ballistics
introduction to forensic ballisticsintroduction to forensic ballistics
introduction to forensic ballistics
 
Fingerprint Identification
Fingerprint IdentificationFingerprint Identification
Fingerprint Identification
 
Finger print
Finger printFinger print
Finger print
 
Examination of glass
Examination of glassExamination of glass
Examination of glass
 
Automated Fingerprint Identification System (AFIS)
Automated Fingerprint Identification System (AFIS)Automated Fingerprint Identification System (AFIS)
Automated Fingerprint Identification System (AFIS)
 
restoration of toolmarks
restoration of toolmarksrestoration of toolmarks
restoration of toolmarks
 
Disguised writing
Disguised writingDisguised writing
Disguised writing
 
FINGER_PRINT_HISTORY.ppt
FINGER_PRINT_HISTORY.pptFINGER_PRINT_HISTORY.ppt
FINGER_PRINT_HISTORY.ppt
 
Henry’s 10 digit classification of fingerprint
Henry’s 10 digit classification of fingerprintHenry’s 10 digit classification of fingerprint
Henry’s 10 digit classification of fingerprint
 
Fingerprints
FingerprintsFingerprints
Fingerprints
 
Tool marks and its forensic significance
Tool marks and its forensic significanceTool marks and its forensic significance
Tool marks and its forensic significance
 
Types of bullets
Types of bulletsTypes of bullets
Types of bullets
 
Poroscopy and edgeoscopy
Poroscopy and edgeoscopyPoroscopy and edgeoscopy
Poroscopy and edgeoscopy
 
Glass fractures
Glass fracturesGlass fractures
Glass fractures
 
Tool marks
Tool marksTool marks
Tool marks
 
Handwriting and Document Examination
Handwriting and Document ExaminationHandwriting and Document Examination
Handwriting and Document Examination
 
TOOL MARKS
TOOL MARKSTOOL MARKS
TOOL MARKS
 
Forensic examination of signature
Forensic examination of signatureForensic examination of signature
Forensic examination of signature
 

Kürzlich hochgeladen

DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024The Digital Insurer
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityWSO2
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businesspanagenda
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfOrbitshub
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Bhuvaneswari Subramani
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobeapidays
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Angeliki Cooney
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Jeffrey Haguewood
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodJuan lago vázquez
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 

Kürzlich hochgeladen (20)

DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital Adaptability
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 

fingerprint classification systems Henry and NCIC

  • 1. Fingerprint Identification Chapter 10 Fingerprint Classification Systems LawTech Custom Publishing, Inc. Copyright 2005
  • 2. Overview  Fingerprint classification describes an individual’s fingerprints  Fingerprint classifications use codes on fingerprint cards to file and retrieve manual filing system Fingerprint Identification
  • 3. Chapter Objectives  Understand classification of fingerprint card using Henry system  Understand classification of fingerprint card using NCIC system Fingerprint Identification
  • 4. Introduction  Henry System of Classification used for most of 20th Century in U.S. and most English speaking countries Named after Sir Edward Henry of England  Developed system during late 1800s and early 1900s  Fingerprint Identification
  • 5. Introduction (cont.)  National Crime Information Center (NCIC) Classification System Computerized database used in U.S.  Allows law enforcement agencies nationwide access to wanted bulletins and warrants for outstanding suspects and fugitives  Fingerprint Identification
  • 6. Introduction (cont.)  NCIC Classification System (cont.) Short cut to Henry System for quick evaluation and possible elimination of individuals as suspects  Further investigation required for individuals that match NCIC classification including a full fingerprint search  Fingerprint Identification
  • 7. Introduction (cont.) Both classification systems based on 10 fingers  Automation of fingerprint files will render manual classification filing systems obsolete  Knowledge of fingerprint patterns and anatomy of hand useful and valuable information for fingerprint examiner  Fingerprint Identification
  • 8. Introduction (cont.)   Fingerprint classification not the same as fingerprint identification Classification uses class characteristics to group like fingerprints for filing and retrieval   Many people have same fingerprint classification Fingerprint identification uses individual characteristics to individualize a print to a specific person Fingerprint Identification
  • 9. Introduction (cont.)   Fingerprint classification of suspect may appear on wanted bulletins and arrest warrants Law enforcement can use information as a screening tool to eliminate persons being sought   Classifications that are quite different could be used to exclude suspected individuals Classifications that are similar or match would be submitted to agency holding warrant to compare to actual fingerprints Fingerprint Identification
  • 10. The Henry System of Classification  Blocking Out the Fingerprint Card   Determine pattern type in each finger block Indicate pattern using symbols at the bottom middle or right side of each finger box on fingerprint card  Plain Arch → A  Tented Arch → T  Ulnar Loop → / in direction of the loop  Radial Loop → R  All Whorls → W Fingerprint Identification
  • 11. The Henry System of Classification (cont.)  Index finger boxes Use capital letter of pattern type, except for ulnar loop  Ulnar loops designated by a diagonal line slanting in the direction of loop   All  other finger boxes Use small letter to indicate pattern type, except for ulnar loop (same as above) Fingerprint Identification
  • 12. The Henry System of Classification (cont.)  Loop type patterns   Place ridge count in top right hand corner of finger box Whorl patterns   Indicate type in upper right corner of finger box  P – plain  C – central pocket  Small d – double loop  X – accidental whorl Indicate tracing (I, M, O) next to letter designating whorl pattern in top right corner of finger box Fingerprint Identification
  • 13. The Henry System of Classification (cont.) Blocked out fingerprint card Fingerprint Identification
  • 14. Six Divisions of Fingerprint Classification  Primary  Only whorl patterns have value Finger #1 and #2 → 6 Finger #3 and #4 → 8 Finger #5 and #6 → 4 Finger #7 and #8 → 2 Finger #9 and #10 → 1 Fingerprint Identification
  • 15. Six Divisions of Fingerprint Classification (cont.) Primary Chart Fingerprint Identification
  • 16. Six Divisions of Fingerprint Classification (cont.) Whorl values for odd number fingers are added up, plus 1 for the total denominator  Whorl values for even number fingers are added up, plus 1 for the total numerator  Primary reported as a fraction Total numerator (top, even numbered boxes) over the denominator (bottom, odd numbered boxes)  Fingerprint Identification
  • 17. Six Divisions of Fingerprint Classification (cont.) Primary = 1 indicates no whorl patterns  Primary = 32 and over indicates all whorl patterns  Total of 1,024 possible primary classifications  Fingerprint Identification
  • 18. Six Divisions of Fingerprint Classification (cont.)  Secondary Indicated in fraction form Capital letter of pattern type for right index (#2) over left index (#7) fingers  U – ulnar loops  Example: W/U indicates right index finger is whorl, and left index finger is ulanr loop  Fingerprint Identification
  • 19. Six Divisions of Fingerprint Classification (cont.)  Small Letter Group Secondary Applies to fingerprint cards that have a plain arch, tented arch, or radial loop  Excludes index fingers  Location of plain arch, tented arch or radial loops by small letter a, t, or r indicated to right or left of secondary  Example: small letter a to the left of the top capital letter of the secondary indicates that a plain arch is in right thumb  Fingerprint Identification
  • 20. Six Divisions of Fingerprint Classification (cont.)  Dashes used to indicate position of fingers not containing a plain arch, tented arch or radial loop in the middle, ring or little fingers to the left of the secondary Example: - a in the denominator (lower) line of the fraction to the right of the capital letter secondary indicate a plain arch in left little finger Fingerprint Identification
  • 21. Six Divisions of Fingerprint Classification (cont.)   Print cards with small letter groups do not need to add the sub-secondary or major divisions to the classification formula Sub-secondary  Value of ridge counts or tracings of right index (2), right middle (3), and right ring (4) fingers over the values of the left index (7), left middle (8), and left ring (9) fingers Fingerprint Identification
  • 22. Six Divisions of Fingerprint Classification (cont.)  Key  Ridge count of first loop, excluding little fingers  Major  Value of ridge counts or tracings of right and left thumbs Fingerprint Identification
  • 23. Six Divisions of Fingerprint Classification (cont.)  Final  Ridge count of loop in right little finger (5) If right little finger #5 is not a loop, use left little finger #10 If finger #10 is not a loop then there is no final value Fingerprint Identification
  • 24. Six Divisions of Fingerprint Classification (cont.)  VALUES TABLE FOR LOOP RIDGE COUNT CONVERSIONS       Index fingers 1-9 = I; 10 or more = O Middle fingers 1-10 = I; 11 or more = O Ring fingers 1-13 = I; 14 or more = O Right thumb 1-11 = S; 12-16 = M; 17 or more = L  when the left thumb ridge count is 16 or less Right thumb 1-17 = S; 18-22 = M; 23 or more = L  when the left thumb ridge count is 17 or more Left thumb 1-11 = S; 12-16 = M; 17 or more = L Fingerprint Identification
  • 25. Six Divisions of Fingerprint Classification (cont.) Fingerprint card showing Henry Classification Fingerprint Identification
  • 26. The NCIC Classification System  Two letter or number codes used to identify fingerprint pattern type Plain arch → AA  Tented arch → TT  Ulnar loop → ridge count  Radial loop → ridge count plus 50  Plain whorl → P, plus the tracing I,M, or O  Fingerprint Identification
  • 27. The NCIC Classification System (cont.)  Two letter or number codes (cont.) Central Pocket → loop C, plus the tracing I, M, or O  Double loop whorl → small d plus tracing I, M, or O  Accidental → X, plus the tracing I, M, or O  Missing finger → XX  Scar or mutilation → SR  Fingerprint Identification
  • 28. The NCIC Classification System (cont.)  Fingers listed in order of finger numbers on a ten-finger fingerprint card Right thumb is number 1  Example: A5612CIPM dM661415XX  Classification placed in twenty small boxes that appear just above the fingerprint boxes  Fingerprint Identification
  • 29. The NCIC Classification System (cont.) Fingerprint card showing NCIC Classification Fingerprint Identification
  • 30. Discussion Questions “Blocking out” refers to the marking pattern types, ridge counts, and whorl type and tracing on a fingerprint card. True or False?  A fingerprint card with a primary classification of 1 over 1 would contain no whorls. True or False?  What fingerprint classification is used for an electronic warrant?  Fingerprint Identification