Printed matter – Method
Reexamination Certificate
1998-08-03
2001-06-05
Wellington, A. L. (Department: 3722)
Printed matter
Method
C283S069000, C283S078000, C382S116000, C382S124000, C396S015000
Reexamination Certificate
active
06241288
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention relates generally to the field of fingerprint identification/verification systems. More particularly, this invention relates to a fingerprint identification/verification system using two dimensional bitmaps instead of traditional feature extraction.
Two types of matching applications are used for fingerprints. One-to-one verification is used to compare a fingerprint with either a particular template stored on, for example, a smart card, or a template recovered from a database by having the person provide his or her name, Personal Identification Number (PIN) code, or the like. One-to-many identification is used to compare a fingerprint to a database of templates, and is required when a person presents only his or her finger which is then compared to a number of stored images.
Traditional fingerprint identification by feature extraction has been used by institutions like the Federal Bureau of Investigation (FBI) for identifying criminals and is the most common fingerprint identification system. In feature extraction, the pattern of a fingerprint is checked for any special ‘features’ such as ridge bifurcations (splits) and ridge endings amongst the meandering ridges of the fingerprint. Once each such feature is identified, the location, that is, the distance and direction between the features, and perhaps the orientation of each feature, is determined. By storing only the feature location information, a smaller amount of data can be stored compared to storing the complete fingerprint pattern. However, by extracting and storing only the location of each feature, that is, the one-dimensional point on the fingerprint where the feature is located and, perhaps, the type of feature, information for security purposes is lost because all of the non-feature information is then unavailable for comparisons (matching).
Also, in order to determine the absolute location of the features, an unambiguous starting point (reference point) is selected for the fingerprint. Traditional methods locate a ‘core point’ as the reference point. This core point is usually selected according to different criteria depending on the type of fingerprint, for example, whorl, circular or other type. Thus, a fingerprint in such a traditional system must first be classified as a known type before the core point can be determined and the features located.
Another difficulty encountered with automated fingerprint identification or verification systems is the inability of the system to differentiate between a real fingerprint, that is, a fingerprint on a finger, and an image or plastic model of a fingerprint. In traditional systems the type of sensor can help, for example, a heat sensor to detect body heat, but these sensors can be defeated.
In addition, identification presents difficulties when the database of possible fingerprints becomes quite large. In traditional fingerprint systems, each type of fingerprint is categorized and the types of features provide additional subclasses. Nevertheless, the number of classes and subclasses is quite small when compared to the number of fingerprints which may be in any particular class or subclass. Also, once a class or subclass is selected, possible matches in a different class or subclass of the same level of the hierarchy are not checked. Thus, for fingerprints which do not clearly fall within a particular class or subclass, there may be stored fingerprints in the database which are not checked. Accordingly, a search for a matching fingerprint image on file can be both time consuming and result in a false indication that the particular fingerprint is not on file.
OBJECTS AND SUMMARY OF THE INVENTION
An object of the present invention is to provide a fingerprint identification system which identifies fingerprints more accurately than prior systems.
Another object of the present invention is to identify fingerprints by comparing entire two dimensional regions of fingerprint images rather than just the locations of features.
An additional object of the present invention is to accurately and efficiently find a reference point in the image from where to start the identification or verification process.
A further object of the present invention is to determine dynamics of the fingerprint as the image is being made to differentiate a true fingerprint from a false/fake fingerprint placed on the sensor.
Another object of the present invention is to establish a non-hierarchical database which allows for rapid matching of a candidate fingerprint and matching without requiring that the candidate fingerprint belong to a particular class.
A further object of the invention is to provide a fingerprint processing method, and a device for accomplishing the method, having the steps of: (1) obtaining an image of a fingerprint comprising ridges and valleys; (2) searching the image to locate a reference point; and (3) selecting the reference point and a region in the vicinity of the reference point as a recognition template for the image. This method can have the following additional steps: (1) applying the fingerprint to a scanning device; (2) scanning the fingerprint to generate an image signal; and (3) storing the image signal as a digital image. In addition, this method can include any or all of the following sub-methods:
(A)—(1) vectorizing the digital image; (2) selecting a starting sub-area in the vectorized image; (3) scanning from the starting sub-area along an orientation of each subsequent sub-area to locate a first sub-area having a horizontal orientation, the first sub-area included in a first horizontal structure; (4) scanning from the first sub-area across acceptable structures and along a path of acceptable sub-areas until an unacceptable sub-area is located; and (5) selecting the center point of the last scanned acceptable sub-area as the reference point;
(B)—(1) calculating the geographic center of the digital image; and (2) selecting the geographic center as the reference point; or
(C)—(1) binarizing the digital image; (2) determining the row of the digital image which has the greatest number of binary transitions; (3) determining the column of the digital image which has the greatest number of binary transitions; and (4) selecting a point in the image by following a path starting from a point in the image having the row and the column as coordinates.
Also, the searching step of this method can include the following steps: (1) selecting a starting point; (2) following along at least one ridge proximate the starting to locate a ridge of a first type; (3) selecting adjacent ridges of the first type along a predetermined path to locate a ridge of a second type; and (4) selecting a point on the last located ridge of the first type as the reference point.
In addition, the selecting step of this method can include the following steps: (1) selecting the region to include the reference point, the region having a size and a shape; (2) storing the recognition template; (3) selecting the region to include the reference point; (4) selecting other regions, each of the other regions having a respective size and a respective shape, each such other region located with respect to the reference point according to relative location information; and (5) selecting the other regions and the respective relative location information for each respective other region as part of the recognition template for the image.
In addition, this method can include the following steps: (1) storing the recognition template; (2) encrypting one or more of the region, the other regions, and the relative location information; and (3) compressing one or more of the region, the other regions, and the relative location information.
An additional object of this invention is to provide a fingerprint matching method, and a device for accomplishing the method, having the steps of: (1) obtaining an image of a fingerprint comprising ridges and valleys; (2) searching the image to locate a reference point; (3) selecting the reference point and a region in the vicinity of the reference po
Bergenek Jerker
Fåhraeus Christer
Öbrink Mårten
Wiebe Linus
Carter Monica S.
Cooper & Dunham LLP
Precise Biometrics AB
Wellington A. L.
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