Source: http://patents.com/us-7962467.html
Timestamp: 2019-10-17 17:41:46
Document Index: 295573076

Matched Legal Cases: ['Application No. 60', 'Application No. 60', 'Application No. 60', 'Application No. 60', 'Application No. 60', 'application No. 60']

US Patent # 7,962,467. Systems and methods for recognition of individuals using multiple biometric searches - Patents.com
United States Patent 7,962,467
Howard , et al. June 14, 2011
The search results of a first iteration of a biometric search are used to form a probe for subsequent iterations searches in a biometric database. his enables the search methodology to "drill down" into the database to find matching biometric templates. In addition, the results of a search using a template of first biometric type are used to limit the search applied using a template of a second biometric type to improve the effectiveness of a one to many search for matching data in a biometric database. These search methods are used in various combinations with different types of biometric templates and demographic information of an individual who is subject of the one to many search.
Inventors: Howard; James V. (Saugus, MA), Frazier; Francis (Belmont, MA)
Assignee: L-1 Secure Credentialing, Inc. (Billerica, MA)
Appl. No.: 11/866,315
10686005 Oct., 2003 7277891
60418129 Oct., 2002
60429501 Nov., 2002
Field of Search: 707/2,3,104.1,706
6072894 June 2000 Payne
6963659 November 2005 Tumey et al.
This application is a Continuation of U.S. application Ser. No. 10/686,005, filed Oct. 14, 2003 (now U.S. Pat. No. 7,277,891) which claims priority to the following U.S. Provisional patent applications: Systems and Methods for Recognition of Individuals Using Combination of Biometric Techniques (Application No. 60/418,129, filed Oct. 11, 2002); and Systems and Methods for Managing and Detecting Fraud in Image Databases Used With Identification Documents (Application No. 60/429,501, filed Nov. 26, 2002).
1. A computer-implemented method for determining whether an individual should receive an identification document comprising: (a) providing a computer system and a database, the database being operatively connected to the computer system; (b) the database containing a database of biometric templates of individuals; (c) providing at least one device for inputting at least a first and second biometric template of at least one individual into the computer system; (d) receiving an initial probe data set, the first probe data set comprising first and second biometric templates associated with at least one individual; (e) inputting at least a first and second biometric template into the computer system using the device; (f) searching the database of biometric templates using the first biometric template to retrieve a first results set, the first results set comprising a data set for any individual who has a biometric template that satisfies a predetermined first criteria, the data set comprising biometric template information that is searchable using the second biometric template; (g) selecting a first portion of the first results set that satisfies a match criteria; (h) searching the first portion of the results set using the second biometric template to retrieve a second results set, the second results set comprising a data set for any individuals who have a biometric template that satisfies a predetermined second criteria, the data set comprising biometric template information that is searchable using the first and second biometric templates; (i) selecting a first portion of the second results set to be a refined probe data set; (j) searching the database of biometric templates using the refined probe data set to return a results set, the results set comprising biometric templates that satisfy a predetermined third criteria; and (k) analyzing the results set that satisfy the predetermined third criteria to determine whether the individual is attempting to fraudulently obtain an identification document.
2. The method of claim 1, further comprising denying the individual an identification document if, after analysis, the determination is that the individual is attempting to fraudulently obtain an identification document.
6. The method of claim 1, wherein at least one of the first and second biometric templates is a facial image.
7. The method of claim 1, wherein both of the first and second biometric templates are facial images.
8. The method of claim 1, wherein one of the first and second biometric templates is a facial image and the second of the first and second templates is a fingerprint.
This application also is related to the following U.S. provisional and non-provisional patent applications: Integrating and Enhancing Searching of Media Content and Biometric Databases (Application No. 60/451,840, filed Mar. 3, 2003); and Systems and Methods for Detecting Skin, Eye Region, and Pupils (Application No. 60/480,257, filed Jun. 20, 2003). Identification Card Printed With Jet Inks and Systems and Methods of Making Same (application Ser. No. 10/289,962, Inventors Robert Jones, Dennis Mailloux, and Daoshen Bi, filed Nov. 6, 2002, Publication No. 2003-0211296); Laser Engraving Methods and Compositions, and Articles Having Laser Engraving Thereon (application Ser. No. 10/326,886, filed Dec. 20, 2002, Publication No. 2003-0234286--Inventors Brian Labrec and Robert Jones); Multiple Image Security Features for Identification Documents and Methods of Making Same (application Ser. No. 10/325,434, filed Dec. 18, 2002 (now Pat. No. 6,817,530)--Inventors Brian Labrec, Joseph Anderson, Robert Jones, and Danielle Batey); Covert Variable Information on Identification Documents and Methods of Making Same (application Ser. No. 10/3301032, filed Dec. 24, 2002 (now Pat. No. 7,063,264)--Inventors: Robert Jones and Daoshen Bi); Image Processing Techniques for Printing Identification Cards and Documents (application Ser. No. 10/411,354, filed Apr. 9, 2003, Publication No. 2004-0074973 --Inventors Chuck Duggan and Nelson Schneck); Enhanced Shadow Reduction System and Related Technologies for Digital Image Capture (Application No. 60/447,502, filed Feb. 13, 2003--Inventors Scott D. Haigh, Tuan A. Hoang, Charles R. Duggan, David Bohaker, and Leo M. Kenen); and Enhanced Shadow Reduction System and Related Technologies for Digital Image Capture (application Ser. No. 10/663,439, filed Sep. 15, 2003, Publication No. 2004-0140459-Inventors Scott D. Haigh, Tuan A. Hoang, Charles R. Duggan, David Bohaker, and Leo M. Kenen);
Identity theft and other related fraudulent identification activity has the potential to become a major problem to the economy, safety and stability of the United States. Identity theft refers to one individual fraudulently assuming the identity of another and may include activities such as opening credit cards in the name of another, obtaining loans, obtaining identification documents (e.g., drivers licenses, passports), obtaining entitlement/benefits cards (e.g., Social Security Cards, welfare cards, etc.), and the like. Often, these activities are performed without the consent or knowledge of the victim. Other fraudulent identification activity can also be problematic. An individual may, for example, use either his or her "real" identity to obtain a document, such as an identification card, but may further obtain additional identification cards using one or more identification credentials that belong to another and/or one or more fictitious identification credentials.
For example, to obtain an identification document such as a drivers license, a given individual may attempt to obtain multiple drivers licenses under different identities, may attempt to obtain a drivers license using false (e.g., "made up"), identification information, or may attempt to assume the identity of another to obtain a drivers license in that individual's name. In addition, individuals may alter legitimate identification documents to contain fraudulent information and may create wholly false identification documents that purport to be genuine documents.
In some databases, part or all of the database record is digitally encoded, which helps to make it possible to perform automated searches on the database. The databases themselves, however, can still be so large that automated searching is time consuming and error prone. For example, some states do not delete "old" images taken of a given individual. Each database record might be associated with a plurality of images. Thus, a database that contains records for 10 million individuals, could, in fact, contain 50-100 million images. If a given motor vehicle registry uses both facial and fingerprint images, the total number of images may be doubled still.
Another potential problem with searching large databases of biometric images can be the processing delays that can accompany so-called "one to many" searches (comparing a probe image with an "unidentified" image, such as a face or finger image presented for authentication, to a large database of previously enrolled "known" images. In addition, the "many" part of "one-to-many" can vary depending on the application and/or the biometric being used. In some types of applications (such as surveillance, terrorist watch lists, authentication for admission to a facility), the "many" can be as few as a few hundred individuals, whereas for other applications (e.g., issuance of security documents, such as passports, drivers licenses, etc.), the "many" can be many millions of images.
Further, some types of biometric technologies, such as facial recognition, have a few key differences from other types of biometric technologies, such as fingerprint technologies. For example, one difference between face recognition systems and fingerprint recognition systems can be cost. At the present time, for one to many type searching in identification document environments (where "many" at least means a million or more records), facial recognition systems are far less costly than fingerprint recognition systems. The more affordable fingerprint recognition systems, at the present time, generally include those adapted for one to few type searching (where "few" at least means fewer than a million records and includes, for example, systems adapted for use with tens of thousands of records).
Another difference between facial recognition systems and fingerprint recognition (and other systems, such as iris and retina identification systems, voice recognition systems, etc.) systems can be the error rates. In an exemplary biometric identification system, a given image (referred to as the "probe image") is compared to one or more stored image to generate a candidate list of possible matches ordered by a match score. Like some types of automated fingerprint searches, at least some types of automated searches of facial images generate a candidate list of possible matches ordered by a match score. The score is a measure of the level of confidence that the probe facial image and a target image from the candidate list are portraits of the same person. With facial recognition systems, however, separating the true matches from the false matches can be much more difficult than with fingerprinting. Camera angles, angles at which the subject's head and/or eyes are turned, shadows, lighting, hats, glasses, beards, jewelry, etc., each have the potential to affect facial recognition results for at least some types of facial recognition systems. Thus, manual review of facial recognition results can be necessary.
Although face recognition systems can generate a relatively high percentage of matches in the candidate lists (with some facial recognition systems, the match percentage can be--90%), face recognition systems can also generate a very high number of false match results. Using a match threshold to define what constitutes a match may be less effective with face recognition than with other biometrics technologies (e.g., fingerprint recognition) because of the very high False Match Rates. Unless investigators are willing to manually verify matches in a face recognition candidate list, or a better technique is developed to differentiate between matches and non-matches, face recognition is likely to remain less effective than fingerprinting.
In a first aspect, we have found that a biometrics system that utilizes two different biometrics (a so-called "hybrid" biometrics system) can further automate and improve the biometrics search process, especially for (but not limited to) applications involving the production of identification documents such as drivers licenses. In one embodiment, the hybrid solution we propose combines the benefits of two biometric technologies: the speed of facial recognition and the accuracy of fingerprint matching. This blending of two biometrics can result in faster processing time and reduced costs. In one embodiment, this hybrid biometrics processing uses two different biometrics during the searching process, where the two different biometrics are used sequentially. The first biometric (e.g., a facial image) is used to retrieve a first set of results, and the first set of results are then searched using the second biometric (e.g., a fingerprint).
Depending on the particular pairing of biometric templates used, this process can provide a first biometric recognition process adapted for a one to many level "coarse" search to result in a candidate set of results that are usable by a second "one to few" type biometric recognition process. The set of results from the first biometric search process are therefore used by the second biometric search process. The inventors have found that use of two successive biometrics recognition processes (e.g., one to many facial for a first search, followed by one to (relatively) few fingerprint search) can significantly improve the accuracy of the overall recognition and may reduce the number of images that ultimately must be manually reviewed. This type of combination can result in higher accuracy searches at lower costs and/or in less time.
Selecting an appropriate combination also may result in higher accuracy searches at lower costs. For example, one to many fingerprint systems, at the present time, are so expensive that sometimes entities such as departments of Motor Vehicles (DMV's) cannot afford them, even though such one to many fingerprint searches often have desirable accuracy and may be easier to tune. In contrast, one to few fingerprint systems, at the present time, are significantly less expensive than one to many fingerprint systems, but are difficult to use with large databases. In contrast, one to many type facial recognition systems are relatively less expensive than one to many fingerprint systems, although they may be difficult to "tune" (as described above). In at least one embodiment of the invention, a system and method is provided that successively combines a one to many facial recognition system with a one to few fingerprint recognition system to achieve accuracy comparable to a one to many fingerprint system at about one third the cost of such a system.
This application describes additional inventive systems and methods for conducting biometrics searches and/or improving the accuracy of biometrics searching. We have found, for example, that using at least some of the returned biometric search results from a first initial probe image(whether or not the search is a hybrid type search) as second probe images can be used to "drill down" even further in the database and return even more high probability matches to the first probe image.
Before describing various embodiments in detail, it is helpful to define some terms used herein and explain further some of the environments and applications in which at least some embodiments can be used.
In the foregoing discussion, the use of the word "ID document" or "identification document" or "security document" is broadly defined and intended to include all types of ID documents, including (but not limited to), documents, magnetic disks, credit cards, bank cards, phone cards, stored value cards, prepaid cards, smart cards (e.g., cards that include one more semiconductor chips, such as memory devices, microprocessors, and microcontrollers), contact cards, contactless cards, proximity cards (e.g., radio frequency (RFID) cards), passports, driver's licenses, network access cards, employee badges, debit cards, security cards, visas, immigration documentation, national ID cards, citizenship cards, social security cards, security badges, certificates, identification cards or documents, voter registration and/or identification cards, police ID cards, border crossing cards, security clearance badges and cards, legal instruments, gun permits, badges, gift certificates or cards, membership cards or badges, and tags. Also, the terms "document," "card," "badge" and "documentation" are used interchangeably throughout this patent application.). ID document can include any item of value (e.g., currency, bank notes, and checks) where authenticity of the item is important and/or where counterfeiting or fraud is an issue.
In addition, in the foregoing discussion, "identification" at least refers to the use of an ID document to provide identification and/or authentication of a user and/or the ID document itself. For example, in a conventional driver's license, one or more portrait images on the card are intended to show a likeness of the authorized holder of the card. For purposes of identification, at least one portrait on the card (regardless of whether or not the portrait is visible to a human eye without appropriate stimulation) preferably shows an "identification quality" likeness of the holder such that someone viewing the card can determine with reasonable confidence whether the holder of the card actually is the person whose image is on the card. "Identification quality" images, in at least one embodiment, include covert images that, when viewed using the proper facilitator (e.g., an appropriate light or temperature source), provide a discernable image that is usable for identification or authentication purposes.
Further, in at least some embodiments, "identification" and "authentication" are intended to include (in addition to the conventional meanings of these words), functions such as recognition, information, decoration, and any other purpose for which an indicia can be placed upon an article in the article's raw, partially prepared, or final state. Also, instead of ID documents, the inventive techniques can be employed with product tags, product packaging, business cards, bags, charts, maps, labels, etc., etc., particularly those items including marking of an laminate or over-laminate structure. The term ID document thus is broadly defined herein to include these tags, labels, packaging, cards, etc.
Many types of identification cards and documents, such as driving licenses, national or government identification cards, bank cards, credit cards, controlled access cards and smart cards, carry thereon certain items of information which relate to the identity of the bearer. Examples of such information include name, address, birth date, signature and photographic image; the cards or documents may in addition carry other variant data (i.e., data specific to a particular card or document, for example an employee number) and invariant data (i.e., data common to a large number of cards, for example the name of an employer). All of the cards described above will hereinafter be generically referred to as "ID documents".
An exemplary ID document can comprise a core layer (which can be pre-printed), such as a light-colored, opaque material (e.g., TESLIN (available from PPG Industries) or polyvinyl chloride (PVC) material). The core is laminated with a transparent material, such as clear PVC to form a so-called "card blank". Information, such as variable personal information (e.g., photographic information), is printed on the card blank using a method such as Dye Diffusion Thermal Transfer ("D2T2") printing (described further below and also described in commonly assigned U.S. Pat. No. 6,066,594, which is incorporated herein by reference in its entirety.) The information can, for example, comprise an indicium or indicia, such as the invariant or nonvarying information common to a large number of identification documents, for example the name and logo of the organization issuing the documents. The information may be formed by any known process capable of forming the indicium on the specific core material used.
Commercial systems for issuing ID documents are of two main types, namely so-called "central" issue (CI), and so-called "on-the-spot" or "over-the-counter" (OTC) issue. CI type ID documents are not immediately provided to the bearer, but are later issued to the bearer from a central location. For example, in one type of CI environment, a bearer reports to a document station where data is collected, the data are forwarded to a central location where the card is produced, and the card is forwarded to the bearer, often by mail. In contrast to CI identification documents, OTC identification documents are issued immediately to a bearer who is present at a document-issuing station. An OTC assembling process provides an ID document "on-the-spot". (An illustrative example of an OTC assembling process is a Department of Motor Vehicles ("DMV") setting where a driver's license is issued to person, on the spot, after a successful exam.). Further details relating to various methods for printing and production of identification documents can be found in the following commonly assigned patent applications, which are hereby incorporated by reference in their entirety: Identification Card Printed With Jet Inks and Systems and Methods of Making Same (application Ser. No. 10/289,962, Inventors Robert Jones, Dennis Mailloux, and Daoshen Bi, filed Nov. 6, 2002, Publication No. 2003-0211296); Laser Engraving Methods and Compositions, and Articles Having Laser Engraving Thereon (application Ser. No. 10/326,886, filed Dec. 20, 2002, Publication No. 2003-0234286--Inventors Brian Labrec and Robert Jones); Multiple Image Security Features for Identification Documents and Methods of Making Same (application Ser. No. 10/325,434, filed Dec. 18, 2002(now Pat. No. 6,817,530)--Inventors Brian Labrec, Joseph Anderson, Robert Jones, and Danielle Batey); and Identification Card Printer-Assembler for Over the Counter Card Issuing (application Ser. No. 10/436,729, filed May 12, 2003--Inventors Dennis Mailloux, Robert Jones, and Daoshen Bi).
FIG. 1 is a block diagram of a first system 5 for biometric searching, in accordance with one embodiment. The system 5 includes a workstation 10 (described more fully in FIG. 2) which is capable of receiving inputs from a number of sources, including image and/or data capture systems 15, external data systems 17 (such as remote clients in communication with the workstation 10 and/or which conduct searches using the workstation 10, data acquisition devices such as scanners, palm top computers, etc.), manual inputs 19 (which can be provided locally or remotely via virtually any input device, such as a keyboard, mouse, scanner, etc.), and operator inputs 21 (e.g., voice commands, selections from a menu, etc.). The workstation in this embodiment is programmed to convert captured images and/or received data into templates usable by the biometric search systems 31, 25 (described further below). However, those skilled in the art will appreciate that the function of converting captured data into biometric templates can, of course, be performed by a separate system (not shown). Biometric templates, after being created at (or otherwise inputted to) the workstation can be added to the database of enrolled biometric templates 25.
In one embodiment, the first biometric search system is system that is relatively economical, efficient, quick, and reasonably accurate for one-to-many type searching, such as a facial recognition system and the second biometric search system is a system (such as a fingerprint recognition system) that is very accurate and reasonably quick for one to few (or one to "not so many") searching, but which may be not as quick or inexpensive as the first biometric search system. For clarity in explanation, many of the embodiments described herein are explained using face and fingerprint biometrics; however, the invention is not so limited, and virtually any biometric can be usable. For example, in one embodiment, the first biometric search system is a facial recognition system employing a local features analysis (LFA) methodology, such as the FACE-IT facial recognition system available from Identix of Minnesota. Other facial recognition systems available from other vendors (e.g., Cognitec, Imagis, Viisage, Eyematic, VisionSphere, DreamMirth, C-VIS, etc.) are usable with at least some embodiments, as those skilled in the art will appreciate. In one embodiment, the second biometric search system is an AFIS or AFIS-lite compatible system available from NEC. Other fingerprint recognition systems available from other vendors (e.g., BioScript, SecuGen, Identix, Digital Persona, Sagem, Motorola, BAC, Indivos, etc.), including both AFIS and non-AFIS type systems, are, of course, usable (note that AFIS systems can sometimes be restricted to use by law enforcement personnel only).
As those skilled in the art will appreciate, the search results database 23, biometric template database 25 and the demographic database 37 can be implemented using any type of memory device capable of storing data records or electrical signals representative of data and permitting the data records or electrical signals to be retrieved, including but not limited to semiconductor memory devices (e.g., RAM, ROM, EEPROM, EPROM, PROM, etc), flash memory, memory "sticks" (e.g., those manufactured by Sony), mass storage devices (e.g., optical disks, tapes, disks), floppy disk, a digital versatile disk (DVD), a compact disk (CD), RAID type memory systems, etc.
In an advantageous embodiment, the image/data capture system 15 can be implemented to automatically locate and capture biometric information in an image that it receives. For example, in one embodiment that implements a face recognition biometric, we utilize proprietary Find-A-Face.TM. software available from the assignee of the present invention (Digimarc Corporation of Burlington, MA). Find-A-Face.TM. software has the intelligence to automatically (without the need for any operator intervention): (i) follow a multitude of instructions and extensive decision and judgment logic to reliably perform the difficult task of locating human faces (with their many variations) within captured digital data (a digital picture); (ii) once the particular human face is found within the captured digital data, evaluate multiple aspects of the found human face in the image; (iii) determine, based upon this face location and evaluation work, how the system should position the human face in the center of the digital image, adjust the gamma level of the image, and provide contrast, color correction and color calibration and other related adjustments and enhancements to the image; and (iv) repeatedly and reliably implement these and other functions for the relatively large volume of image captures associated with producing a large volume of identification documents
In another advantageous embodiment, we have found that biometric templates created based on the data captured using the image/data capture system 15 can be further improved by utilizing of various methods to improve finding particular biometric features, such as eyes, can further be used to improve the performance of biometric searches that use facial recognition. For example, in one embodiment we use systems and methods described in commonly assigned provisional patent application No. 60/480,257, entitled "Systems and Methods for Detecting Skin, Eye Region, and Pupils," the contents of which are hereby incorporated by reference in their entirety. The systems and methods described in this patent application are, in one embodiment, implemented using a computer, such as the workstation 10.
Referring again to FIG. 1, in at least some embodiments the workstation 10 can be in operable communication with an ID document production system 39, which can, for example, include a printer controller 27 that controls the printing of ID documents by an ID document printing system 29. The ID document production system 39 can, for example, be a CI or OTC type document production system (as described previously and also as described in commonly assigned U.S. patent application Ser. No. 10/325,434, entitled "Multiple Image Security Features for Identification Documents and Methods of Making Same".) In at least some embodiments, the workstation 10 communicates with the ID document production system 39 to control whether or not a given ID document will be created (for issuance to an individual) based on the results of biometric searching.
The server can be any entity, such as the workstation 10, a computer platform, an adjunct to a computer or platform, or any component thereof, such as a program that can respond to requests from a client. Of course, a "client" can be broadly construed to mean one who requests or gets the file, and "server" can be broadly construed to be the entity that sends or forwards the file. The server also may include a display supporting a graphical user interface (GUI) for management and administration, and an Application Programming Interface (API) that provides extensions to enable application developers to extend and/or customize the core functionality thereof through software programs including Common Gateway Interface (CGI) programs, plug-ins, servlets, active server pages, server side include (SSI) functions and the like.
FIG. 3 is a flow chart of a first method for conducting a biometric search, in accordance with one embodiment. The method of FIG. 3 is an illustrative example of one embodiment of our "hybrid" biometrics searching system. The embodiment of FIG. 3 uses two different biometrics (shown for illustrative purposes only to be face and fingerprint) to help determine whether an individual's biometric images match one or more previously enrolled images. However, it should be understood that the two biometrics used in the method of FIG. 3 can be any two biometrics, e.g. face and iris, retina and finger, etc. The method of FIG. 3 can be used to help detect when a single individual has multiple records in a database, whether or not such multiple records are appropriate--such as previous legitimate records associated with an individual (e.g., images taken of an individual over the years as an individual renews a driver's license). The method of FIG. 3 likewise can be used to confirm that a single individual has no other non-authorized records in a database. Sometimes the multiple records of the individual can be present in the database through error or by accident. However, in some instances the multiple records of the individual can be present in the database because of fraud, including fraud by the individual and/or fraud by others attempting to use the personal information of the individual (e.g., identity theft).
When the search is complete, the first biometric search system returns first level search results (step 55) to the workstation 10. FIG. 4B is an illustrative example of part of the search results 102 through 116 that could be returned as part of step 55 (note that the total number of search results and the type of search results provided are provided by way of example only and are not limiting). Each search result 102 through 116 of FIG. 4B can also include other data (e.g., other biometrics such as fingerprints, demographic data, etc.) from the data record associated with each search result. For simplicity of illustration, this additional data is not illustrated in FIG. 4B. In the example of FIG. 4B, the search results 102 through 116 are each returned with a "Face Score" indicating a degree of match to the probe image 100. As the search results 102 through 116 illustrate, images that appear to substantially match the probe image generally (but not necessarily) will score higher than those images that do not appear to substantially match. The images of FIG. 4B may or may not be displayed to an operator 21 of the system 5; this can depend, in one embodiment, on how many results are retrieved. For example, in one embodiment, the results returned in step 55 can be many hundreds of thousands of images, which may be impractical for the operator 21 to review.
Note that in at least some embodiments, the one to many biometric search performed in step 45 can itself comprise more than one search or "pass" of the database it is searching. For example, some facial recognition search systems, such as the Identix FACE IT product, can utilize one or more biometric facial templates as part of its searching. For example, one implementation of the FACE IT product employs a first facial biometric template (a so-called "vector template") of about 84 bytes, for "coarse" searching, followed by a "fine" search using a larger second facial biometric template of about 3500 bytes. Thus, in one embodiment, the one to many facial search of step 45 actually comprises two search passes, one using the 84 byte template and the other using the 3500 byte template. Depending on the processing power available to conduct the searching, the time for this search may be quick or may be relatively long. In another embodiment, the 1: many facial search step 45 of FIG. 3 actually utilizes only one or the other of the 84 and 3500 byte templates. Using just one of the templates can help to increase the overall search speed, especially for large databases. For example, using the small (84-byte) facial recognition template and parallel processing techniques, a single individual can be matched against a relatively large (e.g., a million or more records) database of faces in less than fifteen seconds.
We have also discovered other techniques for improving the accuracy, reliability, and/or efficiency of biometric searching. At least some of these techniques also involve multiple biometric searches. During our testing of various biometric searching systems, we have fount that in at least some instances, when we use one or more of the "closest" matches to an original probe as a probe itself, this "new" probe can itself be used find additional good matches to the original probe, and these matches can also be used as further probes, and so on. FIG. 6 is a flow chart of a second method for conducting a biometric search, in accordance with one embodiment. In FIG. 6, a type of progressive searching (which is sometimes referred to as "drill down") can be used to refine the search process and improve search accuracy.
Referring to FIG. 6, after a probe set containing at least one biometric template is received (step 300), the database is searched using the biometric template (step 305), and a first set of ranked results is returned (step 310). A subset of the first results is selected (step 315), based on a first rule (step 320) to be used as additional probes. The first rule can be similar to the criteria described for step 65 of FIG. 3. In one embodiment, as shown in FIG. 6, the first rule can be based on one ore more of predetermined/automatic system settings (step 325) (e.g., a threshold) and user input (step 330). For example, user input may be useful where manual review of results helps to select the best images to be used as new probes. In at least some embodiments, steps 300 through 315 can be conducted in a "batch" mode with results awaiting manual user input in step 330, then the remaining steps can later be performed in "batch" mode.
After the subset of the first results is selected, providing a stop condition has not been reached (step 345), the subset is used as new probes and the search process is repeated until the stop condition is reached (steps 350, 350). Stop conditions can be any condition that is deemed sufficient to stop the search. For example, a stop condition can be one or more of the following conditions: (i) no matches are retrieved that meet a predetermined criteria; (ii) all matches that are retrieved have been retrieved previously (e.g., no "new" matches); (iii) a predetermined number of searches has been reached ( e.g., steps and 355 have been repeated a predetermined number of times); (iv) a substantial portion of the results set comprises biometric templates that have been retrieved in at least one previous results set; (v) an instruction to stop searching (e.g., manual or automatic interrupt) is received.
As an illustrative example of the FIG. 6 method's operation, assume that the facial image 100 of FIG. 4A was used to generate a biometric probe for step 300 of FIG. 5A, and assume that the results 102 through 116 of FIG. 4B were received as the first set of ranked results of step 310. Assume that the first rule (step 320) is that results in the first set of ranked results having a face score greater than or equal to 90 are to be selected from the first set of ranked results and used as the first subset of step 315. In the results of FIG. 4B, that would mean that the result image 102 (the only result having a score greater than or equal to 90) is used to generate a new biometric probe to search the database (steps 540 and 550 of FIG. 6). An illustrative example of the results that can be retrieved using the result image 102 as a probe can be seen in FIG. 8B. As the results 122 through 128 of FIG. 8B show, use of the "new" probe 102 has returned results that may be a closer match to the original probe 100 than were the original results. In fact, at least one of the results of FIG. 8B (namely, result 124) was not retrieved in the first set of results of FIG. 4B, but was retrieved in the results set of 8B, and is clearly a good match to the original probe image. Detailed information relating to the probe image and the retrieved results can be compared, as shown in FIGS. 9A and 9B, which shows the probe image 120, demographic data 130 and fingerprint 134 of the probe image in a side by side comparison with one of the result images (namely, result image 124). As FIGS. 8A and 8B show, although the facial appearance and fingerprint appear to be substantially identical, the personal information is clearly not matching. An investigator can determine whether this is due to error or fraud.
The method of FIG. 6 can also be adapted to systems using more than one biometric template, as shown in FIG. 7. The method of FIG. 7 is substantially similar to the method of FIG. 6 except that a second biometric (steps 490 and 500) is used to help generate a probe set that is used for "drill down" searching. In this probe set, both the first and second biometrics are used as the method repeats steps 430-510.
Consequently, a biometric template created based on a "tilted head" image might not retrieve all images of the same individual in a database, especially images where the individual's head is tilted in a different way, or is untilted, etc. Such a template might, however, might retrieve at least one duplicate image (and associated record) for the individual (such as an image where the individual's head is slightly tilted, but not as much as in the original image). That retrieved image might be of a quality such that it can create a slightly different biometric template, which may result in a different (and, potentially more accurate) set of results to be retrieved. Of course, this is but one example, and those skilled in the art will appreciate that a given result used as a new probe may return results that are more or less closely matched to an original image, and for widely varying reasons.
In another embodiment, the methods of either FIG. 6 or FIG. 7 may unintentionally detect duplicate records that, while not being substantially close matches to the probe m image, might actually be very close matches to each other. The method of FIG. 6, can be adapted, for example, to flag such "inter results" matching and initiate a separate search, using those results as new probes. This separate search can take place while the original search is occurring or can wait until the original search is complete, depending on computational and database availability.
We even anticipate that the method of FIG. 6 can be used to implement functionality as disparate as computer dating, searching for models and/or actors, and law enforcement searching. For example, in a computer dating or model/actor search implementation, an individual may be desirous of finding a person in the database who "looks like" their ideal (which ideal may be an image resembling, for example, an ex-girlfriend or boyfriend, a celebrity or model, an idealized image created by the individual, an image that closely resembles the individual himself or herself, etc. An individual can, after retrieving one or two potential match images, then use those images to locate more candidates who resemble the ideal. The results be filtered and refined, manually or automatically, in accordance with age, geographical location, etc.
The methods we have discovered also can be adapted for a mix of biometric and non-biometric searching. FIG. 10 is a flow chart of a third method for conducting a biometric search, in accordance with one embodiment. In FIG. 10, the database is initially searched using non-biometric probe data (step 1100). For example, a non-biometric probe data set can be used to retrieve all data records having a specific matching demographic and/or administrative feature (e.g., all records showing the same name and birthdate). The results that are retrieved for this search can include biometric data (step 130). A subset of the biometric data can be further reviewed and searched (steps 1140 through 1160), in a manner similar to that described in FIGS. 6 and 7, based on a predetermined criteria. The predetermined criteria can be selected to help further discover fraud and/or errors. For example, if multiple records have the same name and birthdate but show low biometric match scores with each other (based on any biometric), further review may be necessary to determine whether a given "identity" is being used by multiple different individuals. In another example, if multiple records have the same name and birthdate and high biometric match scores, it may be indicative of a record erroneously being entered more than once in a database
One advantageous application that we have found for the methods of FIGS. 3, 6 and 7 is in the issuance of identification documents such as driver's licenses. Referring to FIG. 3, if, at step 80, there are any unexpected matches found in the database (e.g., matches that are not legitimate previous records of the individual), the workstation 10 (FIG. 1) can tell the printing system 39 to not print an identification document for the individual until an investigation is conducted Similarly, in FIG. 6 (step 350) and FIG. 7 (step 520), if there are "match results" for review), the workstation 10 (FIG. 1) can tell the printing system 39 to not print an identification document for the individual until an investigation occurs. FIG. 11 is an illustrative a block diagram of a system we have implemented for the issuance if identification documents that implements the methods of FIG. 3.
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