Abstract: Various techniques employ digital fingerprints, alone or in conjunction with other data related to a physical object, to characterize the physical object in a way allows an identity of the physical object to be confirmed or authenticated within a threshold of confidence when the physical object is encountered at a subsequently after a digital fingerprint thereof was previously ingested, without capture, retention and/or reference to certain types or categories of characterizing information which may be of a sensitive nature and/or subject to misuse or abuse. Such digital fingerprints may include feature vectors and non-positional characterization values, while advantageously omitting positional information that would otherwise allow recreation of a recognizable image of the physical object or an image from which one or more immutable characteristics or traits (e.g.

Abstract: Digital fingerprints include data indicative of interior features or structures of an object. The physical object may be rigid or malleable. The digital fingerprints may also include data indicative of features on an exterior surface of the object. Digital fingerprints may uniquely identify an object with respect to other objects, even with respect to other objects of a same type or class of objects. The technology may be relatively invariant to changes in scale, rotation, affine, homography, perspective, and illumination as between a reference digital fingerprint and a later acquired or generated digital fingerprint. Digital fingerprints may be used to authenticate an object as being a second instance or appearance of a previously digitally fingerprinted object.

Abstract: A system and method for better matching of two digital fingerprints when the two digital fingerprints are acquired under different conditions that uses the set of points of interest of the first and second digital fingerprints to perform the matching. A transform pyramiding process is performed using the first and second set of points of interest and a hierarchy of transforms to determine if the first and second set of points of interest are true matches despite the different conditions.

Abstract: Facial biometric systems and methods employ digital fingerprints that represent facial characteristics. These systems and methods may perform various digital fingerprint related processes including induction (acquiring of the facial data, generation of a digital fingerprint and storing in a database) and authentication (a process of using the digital fingerprint of the face to perform biometrics). The facial biometric system and method combines these processes with a particular set of hardware to perform the facial biometrics process that is novel and provides benefits and capabilities not achievable by other biometric systems and methods.

Abstract: The present disclosure teaches a method of utilizing image “match points” to measure and detect changes in a physical object. In some cases “degradation” or “wear and tear” of the physical object is assessed, while in other applications this disclosure is applicable to measuring intentional changes, such as changes made by additive or subtractive manufacturing processes, which may, for example, involve adding a layer or removing a layer by machining. A system may include a scanner, and a digital fingerprinting process, coupled to an object change computer server. The server is coupled to a datastore that stores class digital fingerprints, selected object digital fingerprints collected over time, match measurements, and deterioration metrics.

Abstract: Hand biometric systems and methods use digital fingerprints generated from images of at least a portion of hand. These systems and methods may perform various digital fingerprint related processes including induction (acquiring of the hand biometric data, generation of a digital fingerprint and storing in a database) and authentication (a process of using the digital fingerprint of the hand to perform biometrics which are known processes that may be performed using digital fingerprints, and may even be control anonymous access to controlled areas or vehicle. The hand biometric system and method combines these processes with a particular set of hardware to perform the hand biometrics process that is novel and provides benefits and capabilities not achievable by other existing biometric systems and methods.

Abstract: The present disclosure teaches a method of utilizing image “match points” to measure and detect changes in a physical object. In some cases “degradation” or “wear and tear” of the physical object is assessed, while in other applications this disclosure is applicable to measuring intentional changes, such as changes made by additive or subtractive manufacturing processes, which may, for example, involve adding a layer or removing a layer by machining. A system may include a scanner, and a digital fingerprinting process, coupled to an object change computer server. The server is coupled to a datastore that stores class digital fingerprints, selected object digital fingerprints collected over time, match measurements, and deterioration metrics.

Abstract: A method, system and software for control of data, particularly although not exclusively personal data, through the use of digital fingerprints enables a person to “opt in” to a system containing data about him and secure that data by a biologically-based digital fingerprint (such as of his hand or face). In another case, a user may be automatically (involuntarily) inducted into a system. Either way, the present disclosure enables a user to opt out of the system, again using his digital fingerprint. Upon execution of an opt out process, his digital fingerprint is removed from the system, along with any data solely pertaining to that user.

Abstract: A system and method for authenticating additive-manufactured parts using digital fingerprints. The additive-manufactured parts may be parts in which material is added under computer control to build up a three-dimensional object, such as using 3D printing.

Abstract: Disclosed embodiments include systems for authenticating physical objects using digital fingerprints. The system may be hosted on a digital computing server and may include a storage layer for storing a plurality of digital fingerprints. To authenticate objects, multiple users may securely access an authentication layer of the system through a users layer. The digital fingerprints corresponding to a particular class of objects may then be loaded into working memory and used to authenticate objects in the particular class. The storage layer may store digital fingerprints extracted from many different classes of objects so that many different types of objects may be authenticated using the system.

Abstract: Various techniques employ digital fingerprints, alone or in conjunction with other data related to a physical object, to characterize the physical object in a way allows an identity of the physical object to be confirmed or authenticated within a threshold of confidence when the physical object is encountered at a subsequently after a digital fingerprint thereof was previously ingested, without capture, retention and/or reference to certain types or categories of characterizing information which may be of a sensitive nature and/or subject to misuse or abuse. Such digital fingerprints may include feature vectors and non-positional characterization values, while advantageously omitting positional information that would otherwise allow recreation of a recognizable image of the physical object or an image from which one or more immutable characteristics or traits (e.g.

Abstract: Hand biometric systems and methods use digital fingerprints generated from images of at least a portion of hand. These systems and methods may perform various digital fingerprint related processes including induction (acquiring of the hand biometric data, generation of a digital fingerprint and storing in a database) and authentication (a process of using the digital fingerprint of the hand to perform biometrics which are known processes that may be performed using digital fingerprints, and may even be control anonymous access to controlled areas or vehicle. The hand biometric system and method combines these processes with a particular set of hardware to perform the hand biometrics process that is novel and provides benefits and capabilities not achievable by other existing biometric systems and methods.

Abstract: Facial biometric systems and methods employ digital fingerprints that represent facial characteristics. These systems and methods may perform various digital fingerprint related processes including induction (acquiring of the facial data, generation of a digital fingerprint and storing in a database) and authentication (a process of using the digital fingerprint of the face to perform biometrics). The facial biometric system and method combines these processes with a particular set of hardware to perform the facial biometrics process that is novel and provides benefits and capabilities not achievable by other biometric systems and methods.

Abstract: Digital fingerprints include data indicative of interior features or structures of an object. The physical object may be rigid or malleable. The digital fingerprints may also include data indicative of features on an exterior surface of the object. Digital fingerprints may uniquely identify an object with respect to other objects, even with respect to other objects of a same type or class of objects. The technology may be relatively invariant to changes in scale, rotation, affine, homography, perspective, and illumination as between a reference digital fingerprint and a later acquired or generated digital fingerprint. Digital fingerprints may be used to authenticate an object as being a second instance or appearance of a previously digitally fingerprinted object.

Abstract: The present disclosure teaches a method of utilizing image “match points” to measure and detect changes in a physical object. In some cases “degradation” or “wear and tear” of the physical object is assessed, while in other applications this disclosure is applicable to measuring intentional changes, such as changes made by additive or subtractive manufacturing processes, which may, for example, involve adding a layer or removing a layer by machining. A system may include a scanner, and a digital fingerprinting process, coupled to an object change computer server. The server is coupled to a datastore that stores class digital fingerprints, selected object digital fingerprints collected over time, match measurements, and deterioration metrics.

Abstract: A system and method detect a local change to a region of an object using digital fingerprints of the object acquired at a reference time and at a test time. The two digital fingerprints may be used to authenticate the object, a match density is calculated from a comparison of corresponding portions of the digital fingerprints and the match density is compared to a threshold so that when the match density is below the threshold, a region where a component on the object has been added, subtracted, repositioned, substituted, or altered is identified.

Abstract: The present disclosure teaches a method of utilizing image “match points” to measure and detect changes in a physical object. In some cases “degradation” or “wear and tear” of the physical object is assessed, while in other applications this disclosure is applicable to measuring intentional changes, such as changes made by additive or subtractive manufacturing processes, which may, for example, involve adding a layer or removing a layer by machining. A system may include a scanner, and a digital fingerprinting process, coupled to an object change computer server. The server is coupled to a datastore that stores class digital fingerprints, selected object digital fingerprints collected over time, match measurements, and deterioration metrics.