Alitheon, Inc.

Raf Technology, Inc.

Authentec, Inc.

Brian J Elmenhurst

David Justin Ross

Mark Tocci

Heather Wheelock Ross

John Forbes

Richard Clark Teudt

Kevin Saur

David Peter Campbell

Richard H Tyler

Improvements are disclosed for detecting counterfeit objects, based on comparison to digital fingerprints that describe features found in images of objects known to be counterfeit.

Database for detecting counterfeit items using digital fingerprint records

A forgery detection system includes a computer server and a database system of digital fingerprint records corresponding to forged or altered objects of a given object type. Using the computer server, a digital image of a suspect object of the given object type is accessed, an authentication region is selected, and a native feature within the authentication region is extracted. The native feature describes physical characteristics of the authentication region without recognizing content that appears in the authentication region. The computer server forms a feature vector to represent the native feature in a compact form and queries the database system to obtain a result responsive to digital fingerprint records that match the feature vector. Each matching digital fingerprint record is counted, and if the count of fraud indicator matches crosses a predetermined threshold indicating a confidence level that the suspect object is forged or altered, a report based is generated and communicated to a user interface.

Authentication of a suspect object using extracted native features

Methods and systems for detecting changes, alterations and forgeries in documents utilize digital fingerprinting. A set of documents of a given type that are known to be altered or forgeries are scanned and 'fingerprinted' to build a forgery database. Suspect documents are scanned and the resulting fingerprint data is used to query the forgery database to look for matching records, although a match need not be exact. Matches may be counted and compared to a threshold number to assess a confidence that a document is forged or not. The fingerprinting may be directed to at least one authentication region of a document, and one or more features in a region may be incorporated into a fingerprint of the document.

Document authentication using extracted digital fingerprints

A method/apparatus for identifying an object based on a pattern of structural features located in a region of interest wherein the pattern of features comprises at least one fingerprint feature. The region may be recognized and used to identify the object. A first feature vector may be extracted from a first image of the pattern and may be mapped to an object identifier. To authenticate the object, a second feature vector may be extracted from a second image taken of the same region later in time than the first image. The two feature vectors may be compared and differences between one or more feature vector values determined. A match correlation value may be calculated based on the difference(s). The differences may be dampened if associated with expected wear and tear. Thus the impact on the match correlation value of such differences may be reduced. The differences may be enhanced if associated with changes that are not explainable as wear and tear. Thus the impact on the match correlation value of such differences may be increased.

Object identification and inventory management

Methods and systems for tracking a physical object to identify or authenticate it utilizing digital fingerprints which are based on natural features extracted from a digital image of the object. Digital fingerprints do not require or rely on any labels, tags, integrated materials, unique identification characters, codes or other items that may be added to the object specifically for the purpose of identification. Consequently, the disclosed digital fingerprint techniques help to detect or prevent unauthorized alterations of documents, apparel, drugs and pharmaceuticals, etc. Further digital fingerprints can be used to better track and trace a wide variety of objects throughout the distribution chain to demonstrate their provenance and to detect counterfeit objects.

Digital fingerprinting track and trace system

Improvements are disclosed for authentication of an object, verification of its provenance, and certification of the object as compliant with manufacturing standards. Or, an object may be reported as a suspected counterfeit. In one embodiment the system compares a digital fingerprint of the object, based in image capture, to digital fingerprints previously stored in a database and determines if the object has been registered before and is thus authentic. An object feature template may be created which has a list of features and attributes that are relevant for authenticating particular classes of objects. The object feature template can also be used to examine unregistered objects for signs of counterfeiting.

Digital fingerprinting object authentication and anti-counterfeiting system

An automated document processing machine may comprise an electro-mechanical transport subsystem configured to convey a document through the machine, and a camera arranged adjacent the transport and configured to capture an image of a front side of the document. A fingerprinting software component may be configured for processing the captured image of the document to create a unique digital fingerprint of the document based on the front side image, and a software interface may be configured for storing the digital fingerprint in a database of document identifiers in association with a unique alphanumeric identifier so that the document may be subsequently identified in a second processing machine that has access to the database. The digital fingerprint may be responsive to indicia that otherwise appears on the front side of the document, and may comprise data that identifies a document as being unique based on the front side indicia.

Document fingerprinting

A method/apparatus for identifying an object based on a pattern of structural features located in a particular region wherein the pattern comprises at least one fingerprint feature. The region may be recognized and used to identify the object. A first feature vector (FV) may be extracted from a first image of the pattern and may be mapped to an object identifier. To authenticate the object, a second FV may be extracted from a second image of the same region. The FVs may be compared and difference(s) determined. A match correlation value (MCV) may be calculated based on the difference(s). The difference(s) may be dampened if associated with expected wear and tear reducing the impact of the difference(s) on the MCV. The differences may be enhanced if associated with changes that are not explainable as wear and tear increasing the impact of the difference(s) on the MCV.

A method of defining data patterns for object handling includes obtaining an image of an input data area, processing the image to obtain image data, and comparing the image data with a pattern, wherein the pattern identifies spatial information of corresponding pattern fields of the pattern. The method further includes determining a confidence level of the comparison of the image data according to a success in matching the image data with the pattern fields, comparing the confidence level with a confidence threshold associated with the pattern, and selecting the pattern. A pattern output associated with the selected pattern is identified, wherein the pattern output corresponds to a canonical return format, and the pattern output is applied to the image data.

Defined data patterns for object handling

Methods, software and apparatus (FIG.) disclosed to maintain and update an association database () that enables relating updated address information to affected mailpieces (FIG.), and providing the benefits of that information to mailers, especially business or corporate mailers (), and in the case of co-mingled mail, enabling a pre-sort house () to provide the updated information to their customers, or to update mailing lists maintained by or for their customers.

Return address destination discrimination technology

The present invention encompasses a self-orthogonal character recognition engine for executing an iterative method employing a database of predetermined character strings. The method receives a digital representation of a character string. It then generates a proposed result string by applying to the captured digital image a predetermined recognition routine including one or more recognition subroutines. Each recognition subroutine employs an initial parameter setting. Next, if the proposed result string does not match any of the predetermined character strings in the database, the initial parameter setting of a recognition subroutine is changed to a next setting. The recognition process is then repeated using the next parameter setting to generate and test a next result string. The process can be repeated iteratively until a result string is verified or the process times out.

Growing community of inventors

Redmond, WA, United States of America

Brian J Elmenhurst