A system for processing a handwritten message received by a messaging app can modify playback over time of the handwritten message based on a set of rules to determine how to modify the playback. In one embodiment, graphics data (e.g. vector graphics data) that represents the handwritten message is processed using the rules to determine how to modify the playback such that the resulting playback includes at least one modification over a portion of time of the playback.

An ink file output method is provided, which includes: generating M (M is an integer of 1 or more) pieces of stroke data SD on the basis of event data generated as M input devices move, respectively; generating N (N is an integer of 1 or more and M or less) kinds of logical names LN (metadata) identifying the M number of input devices; generating a metadata block associating the M pieces of stroke data SD with the N kinds of logical names LN; and writing the M pieces of stroke data SD and the metadata block to an ink file.

Technology is described herein for parsing an ink document having a plurality of ink strokes. The technology performs stroke-level processing on the plurality of ink strokes to produce stroke-level information, the stroke-level information identifying at least one characteristic associated with each ink stroke. The technology also performs object-level processing on individual objects within the ink document to produce object-level information, the object-level information identifying one or more groupings of ink strokes in the ink document. The technology then parses the ink document into constituent parts based on the stroke-level information and the object-level information. In some implementations, the technology converts the ink stroke data into an ink image. The stroke-level processing and/or the object-level processing may operate on the ink image using one or more neural networks. More specifically the stroke-level processing can classify pixels in the input image, while the object-level processing can identify bounding boxes containing possible objects.

A method and an electronic device for inputting handwriting character are provided. The electronic device comprises a touch screen, a memory, and a processor. The processor is configured to perform the functions of the method. The method comprises steps of: adding a handwriting input on the touch screen; detecting a position of an initial point of the handwriting input; determining an input area for the handwriting input among the plurality of input areas of the touch screen based on the position of the initial point of the handwriting input; determining an operation of the handwriting input based on the position of the initial point of the handwriting input and performing the determined operation; and upon completion of the handwriting input, recognizing the input as a character and displaying the recognized character in the determined input area on the touch screen.

A non-transitory computer readable medium stores a program causing a computer to execute a process. The process includes: generating a first path which represents positions on a medium specified by a digital pen; obtaining a second path which represents positions on the medium specified by the digital pen and which satisfies a predetermined condition; obtaining information for specifying an area on the medium, the area having a predetermined positional relationship with the second path; and erasing the first path in accordance with a positional relationship between the area and the first path.

A method for image processing includes obtaining a mask of a stroke from an image; determining a plurality of cross edges for the stroke based on the mask; generating a histogram comprising a plurality of widths of the cross edges and a plurality of frequencies of the plurality of widths from the cross edges; estimating a lower bound of a width range for the stroke based on a mode width of the plurality of widths, a first subset of the plurality of widths below the mode width, and a first plurality of weights assigned to the first subset of the plurality of widths; and estimating an upper bound of the width range for the stroke based on the mode width, a second subset of the plurality of widths above the mode width, and a second plurality of weights assigned to the second subset of the widths.

The invention provides an offline handwriting individual recognition system and method based on two-dimensional dynamic features. The method comprises: obtaining a first handwriting image corresponding to suspicious handwriting and second handwriting images corresponding to a plurality of sample handwriting; pre-processing the first handwriting image and the second handwriting images to obtain a first pre-processed image and second pre-processed images; extracting a first skeleton image and second skeleton images from the first pre-processed image and the second pre-processed images; obtaining a first writing trajectory and second writing trajectories according to the first skeleton image and the second skeleton images; extracting first dynamic features and second dynamic features according to the first writing trajectory and the second writing trajectories; performing processing to obtain a correlation coefficient between the suspicious handwriting and the sample handwriting, and performing processing to obtain an individual recognition result according to the correlation coefficient.

There is provided an information processing apparatus including an operation unit acquiring an input operation for a message composed of at least one of text and an image, a recording control unit recording the message in accordance with the acquired input operation, and a reproduction control unit reproducing the recorded message to display the message on a display unit.

A handwritten text processing system processes a digitized document including handwritten text input to generate an output version of the digitized document that allows users to execute text processing functions on the textual content of the digitized document. Each word of the digitized data is extracted by converting the digitized document into images, binarizing the images, and segmenting the images into binary image patches. Each binary image patch is further processed to identify if the word is machine-generated or if the word is handwritten. The output version is generated by combining underlying images of the pages of the digitized document with words from the pages superimposed in a transparent font at positions that coincide with the positions of the words in the underlying images.

An input display device includes a display unit that displays a screen for handwriting input on an input screen including a plurality of input fields, a stroke data processing unit that groups stroke data which is input to a capture screen by handwriting into stroke data representing characters to generate grouped stroke data as grouping stroke data, a character recognition unit that conducts character recognition on the grouping stroke data to convert the grouping stroke data into at least one recognized character, and a control processing unit that displays the at least one recognized character at the plurality of input fields of the input screen correlated with positions, at which handwriting input was performed, in the screen for handwriting input.