Biometric data are obtained from biometric sensors on a stand-alone computing device, which may contain an ASIC, connected to or incorporated within it. The computing device and ASIC, in combination or individually, capture biometric samples, extract biometric features and match them to one or more locally stored, encrypted templates. The biometric matching may be enhanced by the use of an entered PIN. The biometric templates and other sensitive data at rest are encrypted using hardware elements of the computing device and ASIC, and/or a PIN hash. A stored obfuscated Password is de-obfuscated and may be released to the authentication mechanism in response to successfully decrypted templates and matching biometric samples. A different de-obfuscated password may be released to authenticate the user to a remote or local computer and to encrypt data in transit. This eliminates the need for the user to remember and enter complex passwords on the device.

Methods, systems, and computer program products are provided for signature verification. Signature verification may be provided for target signatures using genuine signatures. A signature verification model pipeline may extract features from a target signature and a genuine signature, encode and submit both to a neural network to generate a similarity score, which may be repeated for each genuine signature. A target signature may be classified as genuine, for example, when one or more similarity scores exceed a genuine threshold. A signature verification model may be updated or calibrated at any time with new genuine signatures. A signature verification model may be implemented with multiple trainable neural networks (e.g., for feature extraction, transformation, encoding, and/or classification).

A handwriting input apparatus includes processing circuitry configured to cause control data with respect to an input device to be stored in association with identification information of the input device received from the input device; and reflect the control data associated with the identification information of the input device received from the input device in stroke data that is handwritten on the basis of a position of the input device in contact with a touch panel and displayed, and display information based on the stroke data on a display unit.

Methods, systems, and computer program products are provided for signature verification. Signature verification may be provided for target signatures using genuine signatures. A signature verification model pipeline may extract features from a target signature and a genuine signature, encode and submit both to a neural network to generate a similarity score, which may be repeated for each genuine signature. A target signature may be classified as genuine, for example, when one or more similarity scores exceed a genuine threshold. A signature verification model may be updated or calibrated at any time with new genuine signatures. A signature verification model may be implemented with multiple trainable neural networks (e.g., for feature extraction, transformation, encoding, and/or classification).

Biometric data are obtained from biometric sensors on a stand-alone computing device, which may contain an ASIC, connected to or incorporated within it. The computing device and ASIC, in combination or individually, capture biometric samples, extract biometric features and match them to one or more locally stored, encrypted templates. The biometric matching may be enhanced by the use of an entered PIN. The biometric templates and other sensitive data at rest are encrypted using hardware elements of the computing device and ASIC, and/or a PIN hash. A stored obfuscated Password is de-obfuscated and may be released to the authentication mechanism in response to successfully decrypted templates and matching biometric samples. A different de-obfuscated password may be released to authenticate the user to a remote or local computer and to encrypt data in transit. This eliminates the need for the user to remember and enter complex passwords on the device.

A user's signature may be decomposed into one or more components. The components may be described using one or more control points. A user may sign with their eyes by focusing their gaze on a set of these control points that make up the signature. If the user's gaze is within a threshold distance from a control point the signature is validated. Moreover, by modifying the control points based upon the actual gaze location (which is within the threshold distance), the signature may be slightly modified. For example, the signature may be decomposed into one or more components as Bezier curves and the user may be asked to focus on each control point of each of the one or more Bezier curves. Modifying the control points of a Bezier curve slightly still produces a smooth curve, but introduces natural variations.

Biometric data are obtained from biometric sensors on a stand-alone computing device, which may contain an ASIC, connected to or incorporated within it. The computing device and ASIC, in combination or individually, capture biometric samples, extract biometric features and match them to one or more locally stored, encrypted templates. The biometric matching may be enhanced by the use of an entered PIN. The biometric templates and other sensitive data at rest are encrypted using hardware elements of the computing device and ASIC, and/or a PIN hash. A stored obfuscated Password is de-obfuscated and may be released to the authentication mechanism in response to successfully decrypted templates and matching biometric samples. A different de-obfuscated password may be released to authenticate the user to a remote or local computer and to encrypt data in transit. This eliminates the need for the user to remember and enter complex passwords on the device.

A handwriting input apparatus includes processing circuitry configured to cause control data with respect to an input device to be stored in association with identification information of the input device received from the input device; and reflect the control data associated with the identification information of the input device received from the input device in stroke data that is handwritten on the basis of a position of the input device in contact with a touch panel and displayed, and display information based on the stroke data on a display unit.

Biometric data are obtained from biometric sensors on a stand-alone computing device, which may contain an ASIC, connected to or incorporated within it. The computing device and ASIC, in combination or individually, capture biometric samples, extract biometric features and match them to one or more locally stored, encrypted templates. The biometric matching may be enhanced by the use of an entered PIN. The biometric templates and other sensitive data at rest are encrypted using hardware elements of the computing device and ASIC, and/or a PIN hash. A stored obfuscated Password is de-obfuscated and may be released to the authentication mechanism in response to successfully decrypted templates and matching biometric samples. A different de-obfuscated password may be released to authenticate the user to a remote or local computer and to encrypt data in transit. This eliminates the need for the user to remember and enter complex passwords on the device.

A method for the electronic signature of an electronic document (DOC) by means of a handwritten signature, wherein detection means (EM) detect the handwritten signature and at least one biometric feature characterizing the handwritten signature electronically. A characterizing means (KM1, KM2, KM3) generates a character sequence (HED, HES1, HES2) characterizing the electronic document (DOC). An output means (AM1, AM2) exposes the characterizing character sequence (HED, HES1, HES2) for the signer for the handwritten copying. The detection means (EM) electronically detects a character sequence (SBH) copied in handwriting and at least one biometric feature (BMH) characterizing the character sequence (SBH) copied in handwriting. An electronic signature means (SM) generates an electronic data record (SIG) at least based on the characterizing character sequence (HED, HES1, HES2) and at least one biometric feature (BMH) characterizing the character sequence copied in handwriting (SBH). Furthermore, the invention comprises a signature generating system for application of the method according to the invention and a unit for a signature generating system according to the invention.