U.S. patent application number 11/084356 was filed with the patent office on 2006-04-27 for comparison.
This patent application is currently assigned to The Secretary of State for the Home Department. Invention is credited to Cedric Neumann, Roberto Puch-Solis.
Application Number | 20060088225 11/084356 |
Document ID | / |
Family ID | 36206232 |
Filed Date | 2006-04-27 |
United States Patent
Application |
20060088225 |
Kind Code |
A1 |
Neumann; Cedric ; et
al. |
April 27, 2006 |
Comparison
Abstract
A method of simulating the effect of distortion on a
representation of a marker, such as a fingerprint is provided. The
method is useful for generating data for use in various processes
concerned with fingerprints and particularly avoids the need to
manually generate and collect such data. The method includes
obtaining a plurality of representations from an individual, the
representations being subject to different distortions relative to
one another. A function, such as a thin plate spline function, is
then used to describe the effects of the different distortions on
the plurality of representations obtained. This generic model of
the effects of distortion can then be used to generate distortions
for a further representation from an individual, preferably another
individual. The simulated distorted representations can be used in
a variety of ways.
Inventors: |
Neumann; Cedric;
(Birmingham, GB) ; Puch-Solis; Roberto;
(Birmingham, GB) |
Correspondence
Address: |
MERCHANT & GOULD PC
P.O. BOX 2903
MINNEAPOLIS
MN
55402-0903
US
|
Assignee: |
The Secretary of State for the Home
Department
Birmingham
GB
|
Family ID: |
36206232 |
Appl. No.: |
11/084356 |
Filed: |
March 18, 2005 |
Current U.S.
Class: |
382/276 ;
382/124 |
Current CPC
Class: |
G06K 9/6255 20130101;
G06K 9/00006 20130101 |
Class at
Publication: |
382/276 ;
382/124 |
International
Class: |
G06K 9/36 20060101
G06K009/36; G06K 9/00 20060101 G06K009/00 |
Foreign Application Data
Date |
Code |
Application Number |
Oct 26, 2004 |
GB |
0423648.5 |
Feb 11, 2005 |
GB |
0502849.3 |
Claims
1. A method of simulating the effect of distortion on a
representation of a marker, the method including obtaining a
plurality of representations from an individual, the
representations being subject to different distortions relative to
one another; describing the effect of the different distortions on
the plurality of representations using a function; taking a further
representation from an individual and preferably another
individual, applying the function to that representation to
generate one or more simulated distorted representations.
2. A method according to claim 1 in which the function is or
includes a non-linear function.
3. A method according to claim 2 in which the function is a
non-linear transformation.
4. A method according to claim 1 in which the function is or
includes one or more matrices.
5. A method according to claim 1 in which the function is defined,
at least in part, by a comparison of a pair of the representations
having different distortions.
6. A method according to claim 5 in which the comparison considers
the position of one or more minutiae in each of the representations
and/or considers the position of one or more points on one or more
ridges.
7. A method according to claim 1 in which the function is defined,
at least in part, by a thin plate spline approach.
8. A method according to claim 1 in which the plurality of
representations are obtained from the individual under controlled
conditions.
9. A method according to claim 8 in which the conditions are
controlled in terms of the finger used and/or substrate used and/or
pressure used and/or extent of distortion used.
10. A method according to claim 1 in which one or more repeats of
each representation are obtained.
11. A method according to claim 1 in which a plurality of
representations are obtained from a plurality of individuals.
12. A method according to claim 1 in which the method is applied to
a plurality of different individuals to provide a plurality of
functions.
13. A method according to claim 12 in which the two or more of the
functions are combined to give a composite function.
14. A method according to claim 12 in which two or more of the
functions are combined to give a general description of
distortion.
15. A method according to claim 12 in which the plurality of
functions and/or composite function are used to generate one or
more simulated distorted representations from a further
representation.
16. A method according to claim 1 in which the function is applied
to a further representation to generate one or more simulated
distorted representations from a further representation.
17. A method according to claim 16 in which the further
representation to which the function is applied being an
undistorted representation.
18. A method according to claim 16 in which the representation to
which the function is applied is from a different individual to the
individual or individuals that the distorted representations are
obtained from.
19. A method according to claim 16 in which a plurality of
simulated distorted representations are obtained from each
representation.
20. A method according to claim 16 in which the function is used to
generate one or more simulated distorted representations for a
plurality of individuals, with the same function being used in for
each individual.
21. A method according to claim 16 in which the simulated distorted
representations are supplied to a data set.
22. A method according to claim 21 in which the data set is used in
a comparison method in which a representation being compared is
considered against within finger variability and/or between finger
variability.
23. A method according to claim 21 in which the data set is used to
form a probability distribution.
24. A method according to claim 23 in which a probability
distribution relates to the distance between different
representations of the same marker and/or in which a probability
distribution relates to the distance between different
representations of different markers.
25. A method according to claim 1 in which the method is repeated
for one or more different types and/or directions of
distortion.
26. A method according to claim 1 in which the distortion arises
from one or more of the following factors: the particular finger
from which the representation arises, the particular hand from
which the representation arises, the gender of the person from whom
the representation arises, the profession of the person from whom
the representation arises, the height of the person from whom the
representation arises, the size of the person from whom the
representation arises, the weight of the person from whom the
representation arises, the age of the person from whom the
representation arises, the type of the substrate on which the
representation arose, the material of the substrate on which the
representation arose, the shape of the substrate on which the
representation arose.
27. A method of forming a data set including distorted
representations of a marker, the method including obtaining a
plurality of representations from an individual, the
representations being subject to different distortions relative to
one another; describing the effect of the different distortions on
the plurality of representations using a function; taking a further
representation from an individual, preferably another individual,
applying the function to that representation to generate one or
more simulated distorted representations; adding the one or more
simulated distorted representations to a data set.
Description
[0001] This invention concerns improvements in and relating to
comparisons, particularly, but not exclusively to comparisons of
biometric markers and the accounting for distortion involved
therein.
[0002] Various approaches for comparing a biometric marker, such as
a fingerprint, from one source with one from another source exist.
Some such systems have attempted to account on a case by case basis
for the effects of distortion.
[0003] The applicant has developed a likelihood ratio based
approach for such a comparison and this takes into account the
variation in representations of the same finger taken under
different conditions.
[0004] The present invention has amongst its aims to provide
additional data for such a process, without undue burden in its
generation.
[0005] According to a first aspect of the invention we provide a
method of simulating the effect of distortion on a representation
of a marker, the method including
[0006] obtaining a plurality of representations from an individual,
the representations being subject to different distortions relative
to one another;
[0007] describing the effect of the different distortions on the
plurality of representations using a function;
[0008] taking a further representation from an individual and
preferably another individual, applying the function to that
representation to generate one or more simulated distorted
representations.
[0009] According to a second aspect of the invention we provide a
method of forming a data set including distorted representations of
a marker, the method including
[0010] obtaining a plurality of representations from an individual,
the representations being subject to different distortions relative
to one another;
[0011] describing the effect of the different distortions on the
plurality of representations using a function;
[0012] taking a further representation from an individual,
preferably another individual, applying the function to that
representation to generate one or more simulated distorted
representations;
[0013] adding the one or more simulated distorted representations
to a data set.
[0014] The first and/or second aspects of the invention may include
any of the features, options or possibilities set out elsewhere in
this application, including from amongst the following.
[0015] The distortion may arise from one or more factors. The
factors may be or include the particular finger and/or the
particular hand from which the representation arises. The factor
may be or include the gender and/or profession and/or height and/or
size and/or weight and/or age of the person from whom the
representation arises. The factor may be the type and/or material
and/or shape of the substrate on which the representation
arose.
[0016] The marker, preferably a biometric marker, may be a
fingerprint, but may be a palm print, ear print, footprint,
footwear print or the like.
[0017] The plurality of representations may be obtained from the
individual under controlled conditions. The conditions may be
controlled in terms of the finger used and/or substrate used and/or
pressure used and/or extent of distortion used. Preferably one or
more repeats of each representation are obtained. Preferably at
least 2 repeats and more preferably at least 5 repeats are obtained
for each of the different distortions. Preferably at least 5
representations with different distortions are obtained from each
individual. Preferably a plurality of representations are obtained
from a plurality of individuals. Preferably at least 20 individuals
are used, more preferably at least 40.
[0018] The function may be or include a non-linear function. The
function may be a non-linear transformation. The function may be or
include one or more matrices. The function may be defined, at least
in part, by a comparison of a pair of the representations having
different distortions. The comparison may consider the position of
one or more minutiae in each of the representations and/or consider
the position of one or more points on one or more ridges. The
function may be defined, at least in part, by a thin plate spline
approach.
[0019] Preferably the method is applied to a plurality of different
individuals to provide a plurality of functions. One or more of the
functions may be used to generate the simulated distorted
representations. One or more of the functions may be combined, for
instance to give a composite function. One or more of the functions
may be combined to give a general description of distortion. The
composite function may be a composite matrix. The plurality of
functions and/or composite function and/or composite matrix may be
used to generate one or more simulated distorted representations
from a further representation.
[0020] The further representation to which the function is applied
is preferably an undistorted representation. The representation to
which the function is applied may be from a different individual to
the individual or individuals that the distorted representations
are obtained from. Preferably a plurality of simulated distorted
representations are obtained from each representation, potentially
nine or more, preferably 10 or more, ideally 25 or more. The
function may be used to generate one or more simulated distorted
representations for a plurality of individuals, ideally with the
same function being used in for each individual.
[0021] Preferably the simulated distorted representations are
supplied to a data set, ideally a data base. Preferably the data
set and/or data base is used in a comparison method, particularly a
comparison method in which a representation being compared is
considered against within finger variability and/or between finger
variability. The data set and/or data base may be used to form a
probability distribution, for instance a probability distribution
related to the distance between different representations of the
same marker and/or a probability distribution related to the
distance between different representations of different
markers.
[0022] The method may be repeated for one or more different types
and/or direction of distortion. The one or more different types of
distortion may include: distortion of and/or towards one end, for
instance a top, of a representation; and/or distortion of and/or
towards another end, for instance a bottom, of a representation;
and/or distortion of and/or towards another end, for instance one
side, of a representation; and/or distortion of and/or towards
another end, for instance another side, of a representation.
[0023] One or more functions may be provided. One or more functions
related to or specific to the finger which was the source of the
representation may be used, for instance where the finger is the
thumb, first finger, index finger, third finger or fourth finger.
One or more functions related to or specific to the hand which was
the source of the representation may be used, for instance where
the hand is the right hand or left hand. One or more functions
related to or specific to the gender of the person who was the
source of the representation may be used, for instance where the
gender is male or female. One or more functions related to or
specific to the size of the person who was the source of the
representation may be used, for instance in respect of one or more
hyped ranges for the person. One or more functions related to or
specific to the age of the person who was the source of the
representation may be used, for instance with respect to one or
more age ranges. One or more functions related to or specific to
the weight of the person who was the source of the representation
may be used, for instance with respect to one or more weight
ranges. One or more functions related to or specific to the
profession of the person who was the source of the representation
may be used.
[0024] Various embodiments of the present invention will now be
described, by way of example only.
[0025] The comparison of fingerprints, or other biometric markers,
obtained from one source with those obtained from another source is
useful for a variety of purposes, including in forensic science. In
the forensic science context, the comparison may seek to suggest
that a representation of a finger mark from a crime scene is linked
to a suspect.
[0026] The applicant has conducted research and developed an
approach which seeks to evaluate the strength of the link between a
crime scene representation of a fingerprint and a representation of
a fingerprint taken from a suspect and to present this evidence
using a likelihood approach. A significant issue in this approach
and in other approaches to the consideration of representations of
fingerprints is the issue of distortion.
[0027] Whilst a suspect's print taken in a controlled manner, using
preferred materials, is fairly consistent in terms of the
representation it gives between occasions, this is not the case in
crime scene cases. Representations of fingerprints left during day
to day activities, including those which are then associated with a
crime, arise under a wide variety of conditions. The pressure
applied, movement during application, the substrate involved and a
variety of other factors can all alter the form of the
representation which arises when compared with others left or with
representations taken under controlled conditions.
[0028] In the approach taken by the applicant, detailed in
applicant's UK patent application number GB0422784.9 filed 14 Oct.
2004 and/or UK patent application number GB 0502900.4 filed 11 Feb.
2005, the representations of interest are considered in the context
of two data sets. A data set representative of the variation in
representations of fingerprints across the population (say based on
2000 fingerprints) and a data set representative of the variation
in representations of the same fingerprint with specific distortion
are used. The existing data set representative of the variation in
the representations of the same fingerprint with distortion has
been compiled by taking a fingerprint from a small number of
individuals (say 4) and obtaining a number of representations for
them under a number of specific different conditions (say 9) with a
number of repeats for each (say 5). In order to ensure that the
different individuals are considered under the same variations in
conditions, an extremely time consuming and rigorous procedure is
followed. In practical terms this limits the number of different
individuals and number of different conditions for each which can
be considered.
[0029] Instead of physically sampling a large number of
individuals, under various conditions and with repeats thereof, the
alternative approach of the present invention simulates a large
number of specific distorted representations from an undistorted
representation. The undistorted representation is easy to collect
or could even be obtained from one of a number of existing data
sets of such representations. The actual generation of the specific
distorted representations is performed by a computer and so is
quick to perform on a large scale. The simulation is repeated on a
large number of undistorted representations.
[0030] Using such an approach, the data set representative of the
variation in representations of the same fingerprint with
distortion can be increased substantially in size with only a
reasonable input effort. This means that the approach and
statistical models which use this data set are more robust as a
result, as more extensive testing and validation is possible. An
additional benefit comes from the approach enabling the creation of
very large data sets of distorted representations without the need
for physical sampling. A powerful research resource results.
[0031] To be able to distort undistorted representations in an
appropriate way, it is necessary to derive an appropriate
description of the distortion process. To do this, the approach
involves an initial investment in further physical representations
of distortion. A significant number of individuals, for instance
40, are used to provide a significant number of distorted
representations of their fingerprints, for instance 50 each. For
each individual, their representations and the distortion of them
are then described using a non-linear mathematical transformation.
Such an approach is more accurate than some prior approaches as the
nature of the distortion itself is non-linear. In the preferred
form the approach establishes a matrix which describes the
distortion. An example of such a matrix description of distortion
is to be found in Ross et al., Proceedings of the International
Conference on Biometric Authentication (ICBA) Hong Kong, July 2004
"Estimating Fingerprint Deformation" the contents of which are
incorporated herein by reference.
[0032] Starting with a pair of representations, these are presented
in a black and white format, preferably skeletonised and subjected
to appropriate cleaning and healing of the representation. The
minutiae locations are then determined and information on them
collected for each representation using a suitable information
format. The location in the representation and orientation of the
associated ridge and grayscale intensity of pixels in the vicinity
may be captured in this way. The degree of correspondence between
minutiae in the two representations can then be obtained and
quantified using one or more techniques, such as an elastic
stringer matcher. Ridge curves can be extended from these points
and the degree of correspondence between points on the curves
established too.
[0033] The global effect of different distortions between the
different representations on these points is then considered. The
Thin Plate Spline approach describes the dependence of point
positions on a thin metal plate with the physical bending energy
applied to the thin metal plate. The Thin Plate Spline approach is
a parametric generalisation from rigid to mild non-rigid
deformations. The parameters of the Thin Plate Spline approach can
be obtained from a matrix equation and various approaches to the
solution of the equation can be taken. An average deformation model
can be obtained from the technique.
[0034] In the Ross et al., paper, a number of representations of a
marker of a particular individual are taken. These are taken under
generally similar but uncontrolled conditions and so reflect the
common extent of variation for that marker of that individual. The
results are used to form the average deformation model for that
individual. The average deformation model can be considered as
modelling the behaviour of the individual. The average deformation
model is used to distort the representation or "baseline
impression" of a particular individual before that is compared with
the other, template representation of a particular individual. As a
result, the comparison process is improved. No use of the distorted
representation is made outside of the one representation versus
another representation comparison for a particular individual. If
another individual is to be considered, then representations must
be collected for him, an average deformation model for that
individual must be generated and that individual's own average
deformation model is used in any comparison. Each model is
individual specific, therefore, and the model for one individual
may be very different to the model for another.
[0035] In contrast, the present approach uses the description of
specific distortion provided by the matrix and takes it in an
alternative direction. Firstly, it differs in terms of the end use
as that is to take undistorted representations, which are not
involved in any authentication process, and deliberately convert
them to distorted representations. These representations are then
used together with other such distorted representations to form a
data-set, and ideally to contribute to or validate the data set or
probability distribution used in the technique of GB0422784.9 filed
14 Oct. 2004 and/or GB0502900.4 filed 11 Feb. 2005. This is a use
and interest not involved in the Ross et al., process. Secondly,
the approach differs because the matrix arrived at for specific
distortion of an individual is considered together with the
matrices arrived at from corresponding distortions of a number of
other individuals so as to provide a composite matrix descriptive
of distortion in a more general sense. The model of deformation is
not specific to an individual, therefore, but instead is applicable
between individuals. The modelling of distortion according to the
invention can address distortion as a whole, but more preferably a
number of different models to cover different directions of
distortion are generated. For instance, a model for distortion of
the top of the representation can be determined and/or a model for
distortion to one side and/or another and/or the bottom can be
determined. The models can be used individually and/or
together.
[0036] The composite matrix which results provides a detailed and
appropriate expression of how specific distortion alters
representations in general. As such, it is then possible to take an
undistorted representation from an individual, who has not provided
distorted representations which have been physically collected and
considered, and simulate a series of distorted representations for
that representation. Repeat uses of the distortion matrix gives
repeat distorted representations. All these are useful in terms of
contributions to the data set on between representation variability
for the same finger and/or person. The approach can equally well be
applied to a set of ten representations collected with one
representation for each finger of the person.
[0037] Whilst a number of non-linear mathematical transformations
are possible, and a number of matrix based approaches are possible,
the preferred matrix form is achieved using a Thin Plate Spline
approach referenced above. Many variations on that particular way
of describing the distortion are possible, however.
[0038] Whilst the approach is described above in the context of
one, preferably composite, matrix, it is possible to develop a
range of such matrices which are expressions of distortion under
various conditions. Thus a matrix for each gender and/or hand
possible for the person from whom the representation arises is
possible. A series of matrices, with individual matrices for
different ages of the person from whom the representation arises,
is possible. A series of matrices, with individual matrices for
different weights of the person from whom the representation
arises, is possible. A series of matrices, with individual matrices
for different professions of the person from whom the
representation arises, is possible.
[0039] By way of validation, it is possible to take one or more
representations under controlled conditions and apply the
distortion matrix to them. The resulting distorted representations
can then be compared with real representations obtained under a
variety of conditions and hence subject to distortion of their
own.
* * * * *