Methods and supporting systems for representing and searching characters, comprising: obtaining an image of the character, labelling a structure of the character by defining a plurality of nodes and a plurality of edges on the character in the image, and generating a representation of the character by extracting a set of two-dimensional coordinates to represent the plurality of nodes and by extracting a matrix to represent the plurality of edges, and providing the representation in a searchable database.

An object is to provide a polygon detection device, a polygon detection method, and a polygon detection program to accurately detect a polygon resembling a reference polygon from an image. The polygon detection device acquires a ratio among lengths of sides of a reference polygon included in an appearance of a predetermined object. The polygon detection device acquires a photographic image of the predetermined object. The polygon detection device detects line segments from the acquired photographic image. The polygon detection device forms at least one polygon based on the detected line segments. The polygon detection device identifies, from the formed polygon, a polygon corresponding to the reference polygon based on a degree of similarity between a ratio among lengths of sides of the formed polygon and the acquired ratio among the lengths of sides of the reference polygon, among from the formed polygon.

Methods, systems, articles of manufacture and apparatus are disclosed to label text on images. An example apparatus includes colorizer circuitry to apply color to text boxes corresponding to optical character recognition (OCR) data associated with an image, OCR manager circuitry to render an OCR text prompt associated with the OCR data, the OCR text prompt to be rendered proximate to respective ones of the text boxes, the OCR text prompt to display a text portion of the OCR data, and edit circuitry to (a) render an interface in response to selection of the OCR text prompt, the interface populated with the text portion of the OCR data, and (b) in response to an overwrite input to the interface, update the text portion of the OCR data in a memory corresponding to the image.

An ink data modification or correction method, and an information processing device and a program for implementing the method are provided, which allow automatic correction of ink data including a spelling error in a handwritten character string. An ink data modification method according to the present disclosure includes determining a modification method of ink data by detecting a spelling error included in a handwritten character string represented by the ink data, and modifying the ink data by manipulating the ink data on the basis of the determined modification method. For example, the determined modification method may be to add a missing character, or to delete a superfluous character, or to correct a typo by replacing an erroneous character with a correct character.

A computer-implemented method, a computer system and a computer program product mitigate the impact of broken web links. The method includes receiving a web link request from a source website. The web link request includes a broken URL. The method also includes determining an intent of the web link request. In addition, the method includes selecting a relevant substitute webpage, wherein the relevant substitute webpage includes an address, based on the determined intent. Lastly, the method includes routing the web link request to the address of the relevant substitute webpage.

An image processing method, an image processing device, an electronic device, and a non-transitory computer readable storage medium are provided. The image processing method includes: obtaining an input image which includes M character rows; performing global correction processing on the input image to obtain an intermediate corrected image; determining the M character row lower boundaries corresponding to the M character rows according to the intermediate corrected image; and determining the local adjustment reference line and M retention coefficient groups based on the intermediate corrected image and the M character row lower boundaries; determining M local adjustment offset groups corresponding to the M character rows according to the M character row lower boundaries, the local adjustment reference line and the M retention coefficient groups; performing local adjustment on the M character rows in the intermediate corrected image according to the M local adjustment offset groups to obtain the target corrected image.

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.

A system for extraction and verification of handwritten signatures from arbitrary documents. The system comprises one or more computing devices configured to: receive a digital image of a document; perform a dilating transformation via convolution matrix on the digital image to obtain a modified image; determine a plurality of regions of connected markings in the digital image; based at least in part on a pixel density or proximity to an anchor substring of each region, determine whether any region contains any handwritten signature; extract first image data of the region containing a handwritten signature from the digital image; retrieve second image data of a confirmed example signature for a purported signer of the handwritten signature; and based on a comparison of the first image data with the second image data, forward a determination of whether the first image data and second image data are similar.

The present disclosure discloses a method for recognizing text, an apparatus and a terminal device. The method for recognizing text includes: acquiring a sample text dataset, preprocessing text image in the sample text dataset, and generating a label image; inputting the label image into a text recognition model for training, extracting image features, performing down-sampling, restoring an image resolution, normalizing an output probability for the last layer using a sigmoid layer to output a multiple prediction maps with different scales, and optimizing a loss function of the text recognition model to obtain a trained text recognition model; preprocessing a text image to be recognized, inputting the text image to be recognized which is preprocessed into the trained text recognition model, and outputting a clear-scale prediction map; and analyzing the clear-scale prediction map to obtain a text sequence of the text image to be recognized.

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.