finger print pore extraction methods
TRANSCRIPT
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
ADAPTIVE FINGERPRINT
PORE MODELING
AND
EXTACTION
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Introduction
• Biometrics:
Biometrics is a study of methods for uniquely recognizing
humans based upon one or more intrinsic physical or
behavioral characteristics.
• Biometrics can be sorted into two classes:
• Physiological
Examples: face, fingerprint, hand geometry and iris recognition
• Behavioral
Examples: signature and voice
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Introduction• Properties of biometrics 1. Universality Every person should have the biometric characteristic2. Uniqueness No two persons should be the same in terms of the biometric characteristic3. Permanence The biometric characteristic should be invariant over time4. Collectability The biometric characteristic should be measurable with some (practical) sensing device5. Acceptability One would want to minimize the objections of the users to the measuring/collection of the biometric6. Circumvention which reflects how easy it is to fool the system by fraudulent methods.
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
General Biometric System
Database
BiometricSensor Feature Extraction
BiometricSensor Feature Extraction
Matching
ID : 8809
Authentication
Enrollment
ResultAuthentication Result
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
FINGERPRINT AS A BIOMETRIC
• A fingerprint is an impression of the friction ridges, from the surface
of a fingertip.
• It is used for personal identification
• Easy in acquisition
• High matching accuracy rate
• Do not change over time
• Dominate biometric market by accounting for 52% of authentication
systems
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
FINGERPRINT AS A BIOMETRIC
Fingerprint representation The types of information that can be collected from a fingerprint’s
friction ridge impression can be categorized as level 1, Level 2, Level 3.
• Level 1
The fingerprint pattern exhibits one or more regions where the ridges lines assume distinctive shapes characterized by high curvature, frequent termination.
• Level 2
ridge ending and ridge bifurcations
• Level 3
Fine intra ridge details
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
FINGERPRINT AS A BIOMETRIC
FINGERPRINT AS A BIOMETRIC
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
FINGERPRINT AS A BIOMETRIC
“Most of fingerprint identification systems (like AFIS)
rely on minutiae (Level 1&2) only. While this information
is sufficient for matching fingerprints in small databases,
it is not discriminatory enough to provide good results
on large collections of fingerprint images.“
[M. Ray, P. Meenen, R. Adhami - “A Novel Approach to Fingerprint Pore Extraction“, IEEE, Mar. 2005]
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
FINGERPRINT AS A BIOMETRIC
• both show a bifurcation at the same location
– Examination based on Level 1&2 features – match– In combination with Level 3 features (e.g. relative pore position) – no match
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Physiology – Fingerprint formation
• Fingerprints begin forming on the fetus 13th week of development
• Ridge units are fusing together as they grow forming ridges
• Each ridge unit contains a pore which originates from a sweat gland from the dermis
• Pores are only found on ridges not in valleys
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Physiology – Some facts
• typical fingerprint: 150 ridges
• A ridge ~ 5 mm long contains appr. 10 ridge units
• Ridge width: ~ 0.5 mm
• Average number of pores / cm ridge ~ 9-18 pores
• Pores do not disappear, move or generate over time
[Ashbaugh, D., Quantitative-Qualitative Friction Ridge Analysis, 1999, CRC Press]
[Locard, Les pores et l'identification des criminals, Biologica, vol.2, pp. 257-365, 1912]
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Pore Extraction methods
1. skeleton-tracking-based methods
- First binaries and skeletonize the fingerprint image and then track
the fingerprint skeletons.
- Computationally expensive.
- very sensitive to noise.
- work well on very high resolution fingerprint images.
2. Filtering-based methods
- filter fingerprint images
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Isotropic pore models
Invariant with respective to direction
1. Ray’s Model:-
which is used 2-dimensional Gaussian functions for pore extraction.
2. Jain’s model:-
Jain proposed to use the Mexican hat wavelet transform to extract pores based on the observation that pore regions.
3. DoG Model:- (Difference of Gaussian filter )
Is to use a band-pass filter to detect circle-like features.
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Proposed system
Propose to develop a novel dynamic anisotropic pore model
which describes the pores more flexibly and accurately by
using orientation and scale parameters and an adaptive
pore extraction method can detect pores more accurately
and robustly.
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Dynamic anisotropic pore model (DAPM)
• Previous models are isotropic and static (uses unitary scale)
• This new pore model has two parameters to adjust scale and orientation,
• These two parameters are adaptively determined according to the
local ridge features (i.e. ridge orientation and frequency)
• DAPM is defined
Eq. (1) is the Reference Model (i.e. the zero-degree model)
Eq. (2) is the rotated modelHere, is the scale parameter which is used to control the pore size. It can be determined by the local ridge frequency. Is the orientation parameter which is used to control the direction of the pore model.
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Adaptive pore extraction method
• Pore extraction is essentially a problem of object detection.
• DAPM parameter estimation:-
To instantiate the pore model initialize two parameters orientation and scale.
- Orientation parameter :-Set the local fingerprint ridge orientation
- Scale parameters :- Use the maximum valid pore scale
• Implementation issue:-With estimated parameter an adaptive pore model can be instantiated for each pixel and apply to matched
Filter to extracted pore from the fingerprint image.
- computational cost:-
Calculations as pixel wise way
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Adaptive pore extraction method
• Implementation issue:-
- Accurate estimate
Difficult to get accurate estimate by pixel wise
• To deal with these issue, propose Block wise approach
• Three kinds of blocks on fingerprint image
1) Well-defined blocks
2) Ill-posed blocks Foreground fingerprint
region
3) Background blocks
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Adaptive pore extraction method
• well- defined block: It is able to directly estimate a dominant ridge orientation and a ridge frequency.• Ill-posed block: There is not a dominant ridge orientation but the ridge frequency can be estimated by interpolation of the frequencies on its neighboring blocks.
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Adaptive pore extraction method
• Pore Extraction algorithm:
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Adaptive pore extraction method
• Partition:
The first step is to partition the fingerprint image into a number of blocks, each being a well-defined block, an ill-posed block or a background block
• Ridge orientation and frequency estimation:
The ridge orientation field of the fingerprint image is calculated. Meanwhile, the mean ridge frequencies on all foreground blocks are estimated, which form the ridge frequency map of the fingerprint image.
• Ridge map extraction
The binary ridge map of the fingerprint image is calculated
• Pore detection:
The foreground fingerprint blocks are processed one by one to detect pores
on them
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Adaptive pore extraction method
• Post Processing
Record the extracted pores by recording the coordinates of their mass centers
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ARVIND S. SARDAR 10.10.2012 Adaptive fingerprint pore modelling and extraction
Thank you