The accuracy of existing machine learning models, software technologies, and computers are improved by using one or more machine learning models to map data inside structural elements, such as rows or columns, as found within a document to data objects of other documents, where the data objects are at least partially indicative of candidate categories that the data can belong to.

A method for image processing includes obtaining a mask of a stroke from an image and identifying a plurality of cross edges for the stroke based on the mask and a reference line. The plurality of cross edges includes a group of adjacent cross edges that intersect the reference line. The method further includes (a) calculating a first vector based on positions of at least two of the cross edges in the group, (b) expanding the group, based on the first vector, to include cross edges adjacent to the group that do not intersect the reference line, (c) calculating a second vector based on positions of at least two of the cross edges in the expanded group, and (d) expanding the expanded group, based on the second vector, to include a second group of adjacent cross edges nearby the expanded group that do not intersect the reference line.

Provided is a system and method of electronically identifying a license plate and comparing the results to a predetermined database. The software aspect of the system runs on standard PC hardware and can be linked to other applications or databases. It first uses a series of image manipulation techniques to detect, normalize and enhance the image of the number plate. Optical character recognition (OCR) is used to extract the alpha-numeric characters of the license plate. The recognized characters are then compared to databases containing information about the vehicle and/or owner.

The invention relates to a method for OCR detection of valuable documents in a cash dispenser in the case of which an image of the valuable document is detected by means of a digital video or matrix camera. A Hough transformation is used to calculate edge lines of the valuable document and a rotation angle is calculated therefrom such that the edges of the valuable document are aligned with the image edges. The detected image is homogenized to compensate an inhomogeneous image background. This is followed by OCR detection of alphanumeric information on the valuable document.

A method of training a cycle generative networks model and a method of building a character library are provided, which relate to a field of artificial intelligence, in particular to a computer vision and deep learning technology, and which may be applied to a scene such as image processing and image recognition. A specific implementation scheme includes: inputting a source domain sample character into the cycle generative networks model to obtain a first target domain generated character; calculating a character error loss and a feature loss of the cycle generative networks model by inputting the first target domain generated character and a preset target domain sample character into a character classification model; and adjusting a parameter of the cycle generative networks model according to the character error loss and the feature loss. An electronic device and a storage medium are further provided.

The present disclosure provides systems, methods, and computer program products for generating a digital representation of a system from engineering documents of the system comprising one or more schematics and a components table. An example method can comprise (a) classifying, using a deep learning algorithm, (i) each of a plurality of symbols in the one or more schematics as a component and (ii) each group of related symbols as an assembly, (b) determining connections between the components and the assemblies, (c) associating a subset of the components and the assemblies with entries in the components table; and (d) generating the digital representation of the system from the components, the assemblies, the connections, and the associations. The digital representation of the system can comprise at least a digital model of the system and a machine-readable bill of materials.

The present document describes a system and method for providing augmented reality interactions with printed media, whereby a user looking at a printed media (physical or electronic) with their portable computing device may view augmented reality interactions on their portable device to enrich the media being viewed. The method includes recognizing pages and using interaction capabilities offered atop the page once recognized. The system is also configured to perform an image recognition process which allows for a very quick detection of a preregistered image from the database which matches the image of the page viewed by the user in order to extract the assets associated with the prestored image and send them to the portable device for display.

An multifunction peripheral includes a font dictionary data configured to include an italic font and a non-italic font for each character code, a determination method selection unit that selects, from a plurality of italic determination methods that are used for italic determination for the character, the italic determination method that is associated with the character code that has been acquired, an italic determination unit that determines whether or not the character in the image data is italic using the italic determination method that has been selected by the determination method selection unit, and a font specifying unit that specifies a font of the character by checking the character that has been determined to be italic by the italic determination unit only with the italic font and checking the character that has been determined to be non-italic only with the non-italic font.

The present document describes a system and method for providing augmented reality interactions with printed media, whereby a user looking at a printed media (physical or electronic) with their portable computing device may view augmented reality interactions on their portable device to enrich the media being viewed. The method includes recognizing pages and using interaction capabilities offered atop the page once recognized. The system is also configured to perform an image recognition process which allows for a very quick detection of a preregistered image from the database which matches the image of the page viewed by the user in order to extract the assets associated with the prestored image and send them to the portable device for display.

The accuracy of existing machine learning models, software technologies, and computers are improved by using one or more machine learning models to map data inside structural elements, such as rows or columns, as found within a document to data objects of other documents, where the data objects are at least partially indicative of candidate categories that the data can belong to.