Image analysis – Applications – Personnel identification
Reexamination Certificate
1997-04-11
2002-03-12
Bella, Matthew C. (Department: 2621)
Image analysis
Applications
Personnel identification
C382S116000, C382S191000, C382S254000, C382S275000, C356S071000
Reexamination Certificate
active
06356649
ABSTRACT:
FIELD OF THE INVENTION
This invention relates generally to systems and methods for verifying identity of people, by comparison and interpretation of skin patterns such as fingerprints; and more particularly to novel firmware and software stored in apparatus memories, as portions of apparatus, for interpreting such patterns and controlling utilization devices. With respect to certain of the appended claims, the invention further relates to systems that include such utilization devices.
A utilization device is, for example, a facility, apparatus, means for providing a financial service, or means for providing information. The phrase “utilization device” thus encompasses, but is not limited to, businesses, homes, vehicles, automatic teller machines, time-and-attendance systems, database-searching services, and a great many other practical systems. An apparatus memory for such storage is, for example, a programmable read-only memory (“PROM”), or a computer-readable disc.
BACKGROUND OF THE INVENTION
Classical methods for evaluation of fingerprints. toeprints, palmprints and like skin patterns entail location, categorization and tabulation of minutiae. Efforts to adapt these classical techniques for automated print verification have received great attention and elaboration, but are fundamentally limited by their sensitivity to measurement noise at the location of the minutiae.
Automated analysis based on minutiae also is inherently very dependent on image enhancement—which often breaks down when initial data quality is marginal. For these reasons some workers have explored other methodologies.
Some seemingly promising efforts employ holograms—either direct three-dimensional images of prints, or holographic Fourier transforms (which have the advantage of being position invariant). Some of these techniques, for best results, impose costly demands on special memory devices for storing the holograms. These holographic correlators are in essence modern refinements of much earlier two-dimensional direct-optical-overlay correlators such as that described by Green and Halasz in U.S. Pat. No. 3,928,842.
An intermediate ground is represented by a few relatively sophisticated patents that use digital computers to (1) automatically select one or more distinctive small regions—not necessarily minutiae—in a master print or “template”, and then (2) automatically look for one or more of these selected small regions in a print provided by a person who purports to be the maker of the template. These earlier patents particularly include U.S. Pat. No. 5,067,162 of Driscoll, U.S. Pat. No. 5,040,223 of Kamiya, U.S. Pat. No. 4,982,439 of Castelaz, U.S. Pat. No. 4,805,223 of Denyer, and U.S. Pat. No. 4,803,734 of Onishi.
All of these latter patents describe making final verification decisions based upon such comparisons of small regions exclusively—although in some cases a small number of such regions are considered concurrently. We have confirmed that many fingerprints can be analyzed very quickly and accurately using just one or two regions, but we have also found that provision must be made for a significant number of prints in which such short-form efforts are indeterminate or at least not adequately reliable.
Thus the patents listed just above are flawed in their ultimate dependence upon isolated, small amounts of data—more specifically, very small fractions of the available information in a candidate user's print—for all fingerprints, regardless of the character of the print. The above-mentioned related patent document of Thebaud, on the other hand, takes into account essentially all the available information in a candidate print.
Thebaud's system does so for all prints. We have recognized that for some types of systems this thoroughness and the accompanying time consumption can represent a significant drawback, because—in a large majority of cases—small regions contain sufficiently distinctive information for a reliable analysis.
Some of the patents in the above list do describe sound techniques for one or another part of their respective processes. Some workers, such as Driscoll and Kamiya, use correlation methods (but electronic-data correlation methods, not optical correlation methods) to choose the small reference sections in the enrollment process—i.e., in forming the template—and also in comparison of those regions with features in a candidate user's print. Denyer similarly uses an approximation to such correlation technique.
These patents do generally allow for the possibility that the authorized user's template may be shifted, or in other words translated, in placement of the print image on the sensor. Some (particularly Driscoll and Denyer) allow for the possibility that the template may be rotated too.
Driscoll discusses finding a least-squares-fit between plural reference regions and a potentially corresponding plurality of test regions in the candidate print. He suggests that departures from an ideal rotated pattern of the reference regions is to be accounted for by distortion of the fingertip in the course of placement on a sensor, but by his reliance on a very small number (typically three, as understood) of well-separated reference regions his allowance for distortion—and his overall verification decision as well—inherently make use of only a very small fraction of the available information. Denyer, too, briefly mentions (though in a much more generalized and tangential way) the possibility of somehow accounting for distortion.
All of these patent documents except Thebaud's, however, fail to take account of dilations which an authorized user's fingertip may undergo—relative to the same user's established template. (By the term “dilations” we mean to encompass dilations or contractions as the case may be.) Such dilations may arise from variations in the pressure with which the finger is applied to an optical or other sensor (capacitive, variable-resistance etc.).
Such dilations may be expected to have at least a component which is invariant across the entire image, in other words a dilation without change of fingerprint shape—an isomorphic dilation. Furthermore all the above-mentioned patents fail to make systematic, controlled allowance for dilations and other forms of distortion that are differential—which is to say, nonisomorphic.
Correlation methods, matched-filter methods, and (loosely speaking) related overlay-style techniques of comparison all fail totally in any area where a reference print is mismatched to a candidate print by as little as a quarter of the spacing between ridges. It has been found that dilations and other distortions can and commonly do produce spurious mismatches locally—over sizable areas—exceeding twice the spacing between ridges, that is, many times the minimum disruption which destroys correlation and thereby recognition.
Therefore, failure to account properly for either dilation (isomorphic distortion) or distortion (differential distortion) results in unacceptably high rates of failure to verify or recognize an authorized user—i.e., high rates of the so-called “false rejection” or “type 1 error”. Artificial measures aimed at reducing this failure rate lead inevitably to the converse: unacceptably high rates of failure to reject unauthorized users, impostors—i.e., high rates of the so-called “false acceptance” or “type 2 error”.
For those few cases in which abbreviated analysis is unreliable, it appears unlikely that adequate account of distortions can be made merely by allowing for random variation as between two or three cores or distinctive regions. The full-coverage paradigm of the Thebaud document, by virtue of its ability to use all information available in the entire area of overlap between the reference and test images, has an immunity to such error, but at the cost of a relatively long analysis time—currently several seconds (after the fingerprint data are fully acquired) per determination—even for prints which have very distinctive regions.
Similarly none of the prior-art patents noted makes use of decisional
Harkless Curt R.
Monro, Jr. John A.
Potter Randall E.
Thebaud Lawrence R.
Arete Associate, Inc.
Bella Matthew C.
Chawan Sheela
Smart & Biggar
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