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.

A system may include a processor configured to: obtain an image of an airport terminal chart; based on a latitudinal set of characters, determine a latitude for each line of latitude; based on the latitude for each line of latitude and a first image distance between the lines of latitude, determine a first ratio of latitudinal degrees between the lines of latitude to the first image distance; based on a longitudinal set of characters, determine a longitude for each line of longitude; based on the longitude for each line of longitude and a second image distance between the lines of longitude, determine a second ratio of longitudinal degrees between the lines of longitude to the second image distance; and output information associated with the first ratio, the second ratio, the determined latitude for each line of latitude, and the determined longitude for each line of longitude.

Disclosed herein are devices and methods for determining the identity of markings on tires. A portable tire scanner can comprise one or more light sources and detector that reflect light off tire markings and capture imagery of them. The scanner is operable to process the imagery to determine the identity of the markings. The marking can be the same color as the area of the tire around the marking (e.g., black-on-black) and the scanner can identify the marking by determining angular edges of the markings. Plural light sources and/or detectors can be used to provide plural perspectives to better determine the edges of the markings. The housing can have a form factor that allows the scanner to be hand-held, such that a user can aim the scanner at tires even while on a vehicle or in hard to reach positions. The scanner can be used to scan and identify several tire marking in succession.

Methods, devices, and systems associated with identifying data to transform are described. A method can include receiving, at a model stored on a computing device, data comprising a number of images, receiving, at the model, an input from a user, identifying, via the model, a number of attributes based on the input from the user, and identifying, via the model, a portion of an image of the number of images including at least one of the number of attributes to transform.

Solutions for more efficient and effective optical character recognition with respect to an input text segment are disclosed. In one example, a method includes processing an input text image using a deep character overlap detection machine learning model in order to generate a character map for the input text image, an overlap map for the input text image, and an affinity map for the input text image; generating an overlap-aware word boundary recognition output based at least in part on the character map, the overlap map, and the affinity map, wherein the overlap-aware word boundary recognition output describes one or more inferred word regions of the input text image; and performing one or more prediction-based actions based at least in part on the overlap-aware word boundary recognition output.

A system, method and computer program product for use in managing collaboration on documents having digital ink on a network of computing devices is disclosed. Each computing device has a processor and at least one system application for processing handwriting input under control of the processor. The system application displays, on a display associated with one of the computing devices, a document having digital ink based on a journal of the document, defines the journal to have journal entries associated with at least handwriting input to the document represented by the digital ink, and communicates the journal entries of the journal with one or more of the other networked computing devices displaying the document. The handwriting input associated with the journal entries is handwriting input to the document via the input interface of any of the computing devices displaying the document based on the communicated journal entries.

An embodiment discloses an electronic device which includes a display and a processor electrically connected with the display. The processor may be configured to detect a designated event, identify text to be outputted on the display and a font applied to the text in response to detecting the designated event, the text including a plurality of characters, determine an animation effect to be applied to the text based on the font, where in applying the animation effect, the processor may be configured to display each of the plurality of the characters for a designated time period along a path corresponding to a character shape from a start point toward an end point of each of the plurality of the characters, and display the text to which the animation effect is applied on the display for the designated time period in response to detecting the designated event.

There are provided an image analysis apparatus, an image analysis method, and a program for implementing an image analysis method that can, when text information about a structural formula of a compound is generated from an image showing the structural formula, cope with a change in the way of drawing of the structural formula.

An image analysis apparatus according to one embodiment of the present invention includes a processor, and the processor is configured to generate, on the basis of a feature value of a subject image showing a structural formula of a subject compound, symbol information representing the structural formula of the subject compound with a line notation, by using an analysis model. The analysis model is a model created through machine learning using a learning image and symbol information representing a structural formula of a compound shown by the learning image with a line notation.

In accordance with some embodiments, systems, methods and media for directly recovering planar surfaces in a scene using structured light are provided. In some embodiments, a system comprises: a light source; an image sensor; a processor programmed to: cause the light source to emit a pattern comprising a pattern feature with two line segments that intersect on an epipolar line; cause the image sensor to capture an image including the pattern; identify an image feature in the image, the image feature comprising two intersecting line segments that intersect at a point in the image that corresponds to the first epipolar line; estimate a plane hypothesis associated with the pattern feature based on properties of the pattern feature and properties of the image feature, the plane hypothesis associated with a set of parameters characterizing a plane; and identify a planar surface in the scene based on the plane hypothesis.

In accordance with some embodiments, systems, methods and media for directly recovering planar surfaces in a scene using structured light are provided. In some embodiments, a system comprises: a light source; an image sensor; a processor programmed to: cause the light source to emit a pattern comprising a pattern feature with two line segments that intersect on an epipolar line; cause the image sensor to capture an image including the pattern; identify an image feature in the image, the image feature comprising two intersecting line segments that intersect at a point in the image that corresponds to the first epipolar line; estimate a plane hypothesis associated with the pattern feature based on properties of the pattern feature and properties of the image feature, the plane hypothesis associated with a set of parameters characterizing a plane; and identify a planar surface in the scene based on the plane hypothesis.