Handwriting verification methods and related computer systems, and handwriting-based user authentication methods and related computer systems are disclosed. A handwriting verification method comprises obtaining a handwriting test sample containing a plurality of available parameters, extracting geometric parameters, deriving geometric features comprising an x-position value and a y-position value for each of a plurality of feature points in the test sample, performing feature matching between geometric features of the test sample and a reference sample, determining a handwriting verification result based at least in part on the feature matching, and outputting the handwriting verification result. The geometric features may further comprise values derived from the geometric parameters, such as direction and curvature values. The handwriting verification result can be further based on a count of unlinked feature points. Handwriting-based user authentication methods can employ such handwriting verification methods, or other handwriting verification methods.

The subject technology provides for receiving a new input stroke. The subject technology determines whether the new input stroke is associated with an existing line group based on a writing direction estimate of the existing line group. The subject technology merges the new input stroke with the existing line group in response to determining that the new input stroke is associated with the existing line group. The subject technology determines a local orientation of the existing line group including the new input stroke based on an estimate of a direction of writing and a scale of each stroke. The subject technology normalizes the existing line group including the new input stroke using the determined location orientation.

A method of providing a handwriting style correction function and an electronic device adapted to the method are provided. The electronic device includes: a touch screen; a processor electrically connected to the touch screen; and a memory electrically connected to the processor. The memory stores instructions which, when executed by the processor, cause the processor to perform operations comprising: displaying at least one reference character on the touch screen; receiving a touch gesture via the touch screen; displaying a track of the received touch gesture on the touch screen; recognizing the track of the touch gesture as at least one input character corresponding to at least one reference character; identifying at least one reference character and at least one input character, as at least one stroke, based on a preset standard; comparing corresponding strokes of at least one reference character with at least one input character, and determining errors by strokes; and summing the errors by strokes of each of at least one reference character, and determining errors by characters.

A computer-implemented method selectively outputs two types of vector data representative of user-input strokes. Type one stroke objects are generated in a device including a position input sensor, on which a user operates a pointer to generate a type one stroke object representative of a stroke. A stroke starts at a pen-down time at which the pointer is placed on the position input sensor and ends at a pen-up time at which the pointer is removed therefrom. Real-time rendering of a type one stroke object is started after the pen-down time of a stroke without waiting for the pen-up time. After completion of a type one stroke object through its pen-up time, the type one stroke object is converted to a type two stroke object, which is a set of curves defining a boundary of the stroke, and can be exported as a file or rendered on a display.

The invention relates to a method in a computing device for hand-drawing elements, comprising: detecting input elements hand-drawn on an input surface; displaying the input elements in digital ink on a display device; classifying input digital ink as text or non-text and predefining blocks of input elements; selecting one or more input element according to a first selection mode triggered by a first gesture or according to a second selection mode triggered by a second gesture to select input elements within a selection area. Once selection is made, editing may be performed on the selected input elements in a different manner depending of which of the first and second selection mode is used.

A computer-implemented method is provided to selectively output two types of vector data representative of user-input strokes. Type one stroke objects are generated in a device including a position input sensor, on which a user operates a pointer to generate a type one stroke object representative of a stroke. A stroke starts at a pen-down time at which the pointer is placed on the position input sensor and ends at a pen-up time at which the pointer is removed from the position input sensor. Real-time rendering of a type one stroke object is started after the pen-down time of a stroke without waiting for the pen-up time. After completion of a type one stroke object through its pen-up time, the type one stroke object is converted to a type two stroke object, which is a set of curves defining a boundary of the stroke, and can be rendered.

Systems and methods for predicting signature locations include an electronic document to be signed, a user of the electronic document, and a user communication device. The user provides free text inputs in the text input module of the system for the requirements of signatures in the document. A signature fields finder module analyzes inputs of user based on heuristic training patterns and screens and maps all the pages of the document for placing signature boxes. The system then places signature tags in the signature boxes. The user selects the signer parties present in the signature boxes and the system compiles signature tags for that party.

The present disclosure relates to a data processing method and apparatus, and an intelligent interactive device. The data processing method is performed by a display having a touch function. The method include: obtaining a writing track point position when a writing pen writes on the display, and an inclination angle of the writing pen relative to the display during writing; obtaining a touch track point position of a user on the display at a current moment obtaining a holding parameter for holding the writing pen; determining a shielding area for a touch at the current moment according to the holding parameter, the inclination angle and the writing track point position; and when touch track point position is located in the shielding area, not displaying a track of the touch track point position on the display.

A position detection apparatus includes a sensor that detects a position pointed to by an electronic pen and circuitry that acquires pen state information regarding the electronic pen held by a person; a transmitter that transmits to an emotion estimation apparatus an emotional state estimation request including the acquired pen state information, the emotion estimation apparatus including a database that stores information regarding an emotional state of the person holding the electronic pen and range information regarding a range of values that may be taken by the pen state information regarding the electronic pen, the emotional state and the range information being associated with one another; and a processor that receives information corresponding to the emotional state transmitted from the emotion estimation apparatus in response to the pen state information included in the transmitted emotional state estimation request, and performs processing using the received information corresponding to the emotional state.

There is provided an encoding and decoding method and an information recognition device using the same. A code block includes a center coding region and a peripheral coding region arranged around the center coding region. The encoding and decoding method uses the feature of at least one microdot included in the center coding region as codes. The encoding and decoding method uses the feature of at least one microdot included in the peripheral coding region as codes. The encoding and decoding method uses the relative feature between the center coding region and the peripheral coding region as codes. The information recognition device compares the read feature with pre-stored features to decode information such as position codes, object codes, parameter codes and control codes.