Automated Fingerprint Identification Systems by pptfiles


									Automated Fingerprint Identification
                          Goals of Module
   Understanding of the basic concept
    of the AFIS
   Database
   Image
   Coder
   Matcher
   Arrest/Applicant Fingerprint and
    Palm Card Processing in AFIS
    Two Finger vs. Tenprint File
    Tenprint vs. Tenprint File
    Tenprint vs. Unsolved Latent File
   Expert Matching currently used in
    the state system
   System Accuracy
   Impact of agency workflow design
   Current Issue’s/Limitations of AFIS
   Mobile AFIS
                                   Goals of Module
   Brief description of a latent crime scene
   Latent Acquisition in AFIS.
   Latent Finger/Palm Searches
       Latent vs. Latent Cognizant File/Latent vs. Unsolved
       File/Palm print vs. Unsolved Latent Palm
       Latent Palm vs. Palm print Filet/
       Latent Palm vs. Unsolved Latent PalmTP
   Accuracy and how it is established in a
    latent system.
   Image Resolution.
   Differences in the state and FBI latent
   Current Issue’s/Limitations of latent
    search systems.
          Automation of Fingerprint Search
         FBI / National Bureau of Standards Begin a Long Term Collaboration to Automate
1963     Fingerprint Search Process
         R&D Intentionally in the Public Domain

1979     FBI Introduces Initial Automated Processing

         Commercial AFIS Systems Emerge and are Rapidly Adopted
1980’s   Unable to Exchange Fingerprints Between Vendors
         FBI Processing Times and Backlogs Fall Behind States

1986     ANSI/NBS-ICST 1-1986 Fingerprint Identification - Data Format for Information

1989     FBI and Advisory Board Conceive National Search Hierarchy
         And Plan to Revitalize FBI Identification Services

1992     Advisory Policy Board Approves FBI IAFIS System requirements.

              Goals of Automating the Fingerprint
Automation of the Fingerprint Search Process

   Ability to effectively Search Crime Scene

               Cardless System

•Cost Savings (no files or storage required )
•Ability to search Crime scene prints
•Improve quality of prints captured

                                    FBI Files 1997

   “The basis of fingerprint identification is the
    premise that the configurations formed by the
    raised ridges of the palmar surface of the
    hands are unique and do not undergo any
    natural changes, except growth, from fetal life
    until decomposition.”
                   Ridge Characteristics
                       a.k.a. Minutiae or Points

   Specific traits found in friction ridges used to establish an
    identification by their relative location to each other.
   The Average finger has between 75 and 175 points of
    identification. Palmar area approximately to 2,000 points of
   e.g. ending ridges, dots, bifurcations, islands
                    Core Systems in all
         Automated Fingerprint Identification Systems

    Input               Coder               Matchers            Database
                     Manual/system                              Finger/Palm

No matter what size the system, a small SPEX system or the FBI, they all have these
Core components.
Latent Input from Lincoln PD, Omaha PD, Douglas Co. and Stat Patrol
Input of Latent Print
   The examiner will enter the
    latent examiner will enter the
    latent lift/photograph into the
    system. The image is
    designed for the fingerprint
    to be captured with the
    camera. The camera
    produces the better images.
    The scanner captures a
    larger area and is better
    suited for a latent palm. The
    scanner samples the image
    at intervals to create the
    image so using the scanner
    you do have a slight loss in
    image quality.
The Search (Coders & Matchers)
   The examiner has a choice to manually select the points of identification (minutiae) or allow
    the system to select it.
   Search database is approximately 350,000 records in Ne. and 60 million at the FBI.
   Other helpful parameters that can be set are age, classification and gender.
   Search takes 4-13 minutes depending on search parameters in Ne.
   All 20 images rolled & flats are searched, if available.
   Current system is 85% accurate when the latent has 15 points of identification and the
    target (exemplar) ten print card has the corresponding 15 points.
   Avg. Latent has between 10 & 30 points.
   Approximately 30% of crime scenes produce useable latent images. 21% of the crime
    scenes have latent fingerprints. The Other 9% are latent palm images
Search Results
   The system uses expert matching to develop a list of viable candidates for the examiner to
   Accuracy ranges from 85% with the target print in the 1st. 5 candidates to 88% that the target is in
    the top 15 candidates.
   System creates a candidate list of the most likely suspects and the latent examiner determines hit
    or no hit.
   If the lift is not identified it can be added to the unsolved latent file.
     Latent Palm Print Searching
   The new systems now have the ability to
    search latent palm images.
   30% of the useable latent prints developed at
    a crime scene are palms.
   Palm system accuracy is 70 to 90 % if the
    latent has 15 points of identification and the
    target (exemplar) ten print card has the
    corresponding 15 points.
   Palms have in approximately 2,000 points of
   Palms have dedicated matchers and coders.
   Application software supports 360 degrees
   Lower palm (thenar, hypo-thenar and
    interdigital) Upper palm and Writers Latent
    palm searching will use a distribution point,
    segment, and hand areas to improve
    performance palm.
                   Unsolved Latent Files
                (latent finger & latent palm)
   The latent finger and palm print files in Ne. are sized to hold 75,000 latent
    records including both latent fingerprints and latent palm prints.
   Regardless of whether the record was entered from a ten print inked card or
    submitted via LSS, workflow capabilities are provided for automated search of
    the unsolved latent file.
   When a new fingerprint card is processed through the ten print system and it is
    not identified the minutiae are compared with the unidentified latent stored in the
    UL file on AFIS.
   Latent finger against the Unsolved accuracy 88-93%, a palm is 73-93%.
                  Accuracy Clarification
Accuracy figures used in this presentation are from a controlled environment and
are probably significantly higher than the results obtained in every day searching.
There are a number of factors that will influence accuracy:
   Quality of the ten print card.
   Quality of database , current database contains images captured at 500 ppi and
    1,000 ppi.
   Work flow
   Quality of the examiner
Universal Latent Workstation
   If a latent is serious enough it can be
    searched against the FBI IAFIS system.
    FBI system consists of :
   The image captured for the state afis
    search can be used for the FBI search but
    new minutiae needs to be plotted.
   50+ million arrest fingerprint cards from
    every state in the union at 500ppi.
   Database penetration less than 30 %
   Search database is created from the 1st.
    Card received. The minutiae however is
    updated when subsequent cards are
    processed, so they have a composite of
    the best minutiae.
   FBI has an unsolved latent file.
Core IAFIS Service
Latent Submission

           Search Database Make Up

   Copy of all/specific # of cards processed

   Copy of the 1st. Card processed (composite of all minutia

   Composite of the best fingerprint images.
              System Accuracy

System accuracy is influenced by:
 Quality of images in the database
 Workflow design

 Training program

 Proficiency testing/ remediation training

The FBI accuracy is 95 to 98%. The database
has the best quality images of any database in
the country. I would estimate the other state
and local databases around 90%
Lives can Unit

   Today over 70% of the
    fingerprint cards are
    captured and digitized
    by lives can units.
    Inked cards are the
    accepted at state level.
    Images are captured at
    either 500 or 1,000 ppi
                       Quality Control
Good quality finger/palm images
are critical to the AFIS database.

Prints sent from the coder are
viewed by a trained technician.

Thresholds monitored by the
system administrator who deter-
mines the amount of work going to

The current system is designed for
5-10% of the transactions to go to
Advanced Fingerprint Processor (Coder)

   1)The original captured fingerprint
   2) The enhanced image is then “thinned” so that a “skeleton” image
   3) Individual minutiae are then extracted from the thinned image
   4) minutiae processing algorithm contains special procedures that
    minimize the number of “false” minutiae arising from over-inking,
    under inking, or smudges.

   The newer systems are now using the 8 best rolled images for
    the ten print search. Older systems oft used 2 fingers, NYC
    used the thumbs while NYS used the index fingers. The index
    and thumbs usually have large numbers of minutia so this
    was a pretty accurate system when storage costs were more
           Lights Out Functionality

   This allows the system to make a determination
    of Identification or Non-Identification. Currently
    NYS is using this on non-criminal transactions
    with excellent results. It could be a way for a
    small state system like Nebraska to supplement
    ten print examiners. Us the lights out for the
    initial verification. The system administrator
    would be required to monitor thresholds more
    closely but it would improve system accuracy
    without increasing staffing requirements.
                  Ten print Results

The results of the ten print search are the basis
Used to:

   Create criminal history (state rap, NCIC etc.)

   Insure no criminal history (applicant record check)

An error in either of the above can dramatically
impact public safety.

All live scan sites in Nebraska are required to capture a
mugshot at printing. This will allow the state to move into
Facial recognition in the future. In the current system
 mugshots are available to any latent workstation
or live scan unit. This for example would allow Lincoln to get a mugshot
from Scotts Bluff on a current arrest.
Currently not all sits are following NIST guidelines for taking mugshot
photographs. In the future all agencies will b required to follow the guidelines
 to share photo’s as well as creating a facial recognition database.


                      HUMAN FORMS AND FEATURES
                      ANIMALS AND ANIMAL FEATURES
                      BNATIONAL SYMBOLS
                      POLITICAL SYMBOLS
                      MILITARY SYMBOLS
                      FRATERNAL SYMBOLS
                      REMOVED & SYMBOLS
                      INSIGNIAS TATTOO
                      PROFESSIONAL SYMBOLS
                      ARM , LEFT
                      SCARS IMAGES
                      ARM , RIGHT
                      FOOT , LEFT
                      FOOT , RIGHT
                      HAND , LEFT
                      HAND , RIGHT
                      HEAD , NON SPECIFIC
             Quick ID/Verification

   Allows the Livescan operator to
    verify an identity using
   The system uses a form of lights
    out and if the person has a
    fingerprint record it can confirm
   Returns information and a
   Mobile AFIS

Increases Officer safety :
 Obtains an accurate record of a subject in
 Identify potentially dangerous/wanted
   individuals in the field.
 Utilizes multi-biometrics for increased
 Operates using cellular phone technology.

 24/7 availability.

 Lights out Operation, fingerprint expert not
 Mobile Units which can work anywhere there
   is cellular availability
Remote Single Finger Identification Pilot

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