A method for recognizing online handwriting comprising acquiring, by a handwriting instrument comprising a module comprising at least one motion sensor, motion data on the handwriting of the user when the user is writing a sequence of characters with the handwriting instrument, the handwriting instrument further including a body extending longitudinally between a first end and a second end, the first end having a writing tip which is able to write on a support, analyzing the motion data with a machine learning model trained in a multi-task way, the machine learning model being configured to deliver as an output the sequence of characters which was written by the user with the handwriting instrument.

Systems and methods for performing spatial line grouping on digital ink stokes. The system includes an electronic processor configured to access a set of hypothetical lines in an electronic document and determine a set of hypothetical line pairings. The electronic processor is also configured to determine, via a gradient boosting tree model, a merge confidence score for each hypothetical line pairing and compare a first merge confidence score with a merge threshold. The first merge confidence score is associated with a first hypothetical line and a first neighboring hypothetical line. The electronic processor is also configured to, in response to the first merge confidence score satisfying the merge threshold, merge the first hypothetical line and the first neighboring hypothetical line to form a first line grouping. The electronic processor is also configured to perform a digital ink stroke analysis on the electronic document based on the first line grouping.

The present disclosure relates to a handwritten text recognition method, including: acquiring an information sequence including a plurality of track points of handwritten text, wherein information on each track point comprises its abscissa, writing time and writing state value; dividing the plurality of track points into a plurality of strokes according to the writing state value of each track point, the writing state value including a first value representative of stroke pen-up and a second value representative of stroke pen-down, respectively; calculating a first segmentation threshold of the handwritten text; determining a first text segmentation point according to a result of comparison between an absolute value of a difference between abscissas of a start track point of one stroke and an end track point of its previous stroke and the first segmentation threshold; and performing text segmentation according to the first text segmentation point to obtain a text segmentation result.

Systems and methods for performing spatial line grouping on digital ink stokes. The system includes an electronic processor configured to access a set of hypothetical lines in an electronic document and determine a set of hypothetical line pairings. The electronic processor is also configured to determine, via a gradient boosting tree model, a merge confidence score for each hypothetical line pairing and compare a first merge confidence score with a merge threshold. The first merge confidence score is associated with a first hypothetical line and a first neighboring hypothetical line. The electronic processor is also configured to, in response to the first merge confidence score satisfying the merge threshold, merge the first hypothetical line and the first neighboring hypothetical line to form a first line grouping. The electronic processor is also configured to perform a digital ink stroke analysis on the electronic document based on the first line grouping.

An electronic handwriting device (e.g., a tablet device or smart phone) detects a first touch and a second touch (e.g., from a pen device) on or near a writing surface of the electronic handwriting device. The electronic handwriting device determines whether the first touch is a dropped touch. Upon determining that the first touch is a dropped touch, the electronic handwriting device applies data filtering to data that is potentially associated with the second touch. After the data filtering step, the electronic handwriting device determines whether to generate a stitching segment between a first line segment associated with the dropped touch and a second line segment associated with the second touch. The determination of whether to generate the stitching segment also may be based on other factors, such as the proximity of the second touch to the dropped touch.

Systems and methods for restoring the appearances of scans of damaged physical documents. Ink bleed is removed and/or ink added to portions of a scanned image based on determining an ink bleed model by analyzing colors of pixels in the scanned image. Gaps in strokes are reconstructed based on analyzing pixel color at multiple angles around individual pixels in the scanned image to determine whether the individual pixels are part of a stroke. The appearance of the scanned image is also enhanced by comparing pixels that are not already close to a background color or ink color with other nearby pixels and, based on the nearby pixels, adjusting colors of the pixels that are not already close to the background color or ink color. These techniques are used individually or in combination to improve the appearance of the scanned image.

Some embodiments of the invention provide a novel method for recognizing characters that are input through touch strokes on a touch-sensitive sensor (e.g., a touch-sensitive display screen or a touch-sensitive surface) of a device (e.g., a mobile device, a remote control, a trackpad, etc.). In some embodiments, the sensor has a space-constrained area for receiving the touch input. In some embodiments, the method places no limitations on where the user can write in the space provided by the device. As such, successive characters might not follow each other in the space. In fact, later characters might overlap earlier characters or they might appear before earlier characters.

The present disclosure relates to a method and system of processing original handwriting input, the system and method being capable of recognize a plurality of strokes provided on the input recognition interface, the method including: determining a stroke box around each stroke; determining overlap between the stroke boxes; correlating overlapping stroke boxes to one or more characters; providing a character box around each of the one or more characters; determining overlap between character boxes; correlating overlapping character boxes to one or more words; providing a word box around each of the one or more words; provide a word margin around each of the one or more word boxes; determining overlap between each word box to determine a line; wherein each of the characters, words, or lines can be individually selected and rearranged, the system automatically adjusting spacing or placement of surrounding elements to allow for the rearrangement.

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.

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.