Embodiments of the present disclosure disclose a method and apparatus for extracting information, a device and a storage medium, relate to the field of image processing technology. The method may include: acquiring a location template corresponding to a category of a target document image; determining key point locations on the target document image; generating a transformation matrix based on the key point locations on the target document image and key point locations on the location template; determining locations of information corresponding to the target document image, based on locations of information on the location template and the transformation matrix; and extracting information at the locations of information corresponding to the target document image to obtain information in the target document image.

A system and method for identifying whether an article is properly presented and duly owned by or licensed to a user and releasing assigned content to the user upon confirmation of such verifiably owned or licensed article. A manipulated user device equipped with at least one camera is deployed to determine if the article is properly presented. The device captures images and the system has the ability to determine from the images and any additional spatial information the orientation and/or position parameters of the article to confirm whether a valid spatial relationship exists between the article and the user device. Due ownership or license is verified by relying on tokens (e.g., Non-Fungible Tokens) and blockchain transaction records. The assigned content released to the user can be contextual and can range from items such as images, music, videos, games, virtual content, augmented content, coupons (virtual or physical), promotions, special offers and the like.

A monocular visual simultaneous localization and mapping (SLAM) data processing method. The SLAM data processing method comprises: obtaining rotation angular velocities and accelerations of a camera cyclically; obtaining a plurality of feature point pairs in two frames of images acquired by the camera, and obtaining pixel coordinate values of feature points in the feature point pairs, where each of the feature point pairs includes two feature points that correspond to a same feature of a same object and that are respectively in the two frames of images; obtaining to-be-selected rotation matrices and to-be-selected displacement matrices according to the pixel coordinate values; obtaining a reference rotation matrix of the camera according to the rotation angular velocities, and obtaining a reference displacement matrix of the camera according to the accelerations; and filtering the to-be-selected rotation matrices and the to-be-selected displacement matrices according to the reference rotation matrix and the reference displacement matrix.

An artificial neural network-based method for detecting a surface type of an object includes: receiving a plurality of object images, wherein a plurality of spectra of the plurality of object images are different from one another and each of the object images has one of the spectra; transforming each object image into a matrix, wherein the matrix has a channel value that represents the spectrum of the corresponding object image; and executing a deep learning program by using the matrices to build a predictive model for identifying a target surface type of the object. Accordingly, the speed of identifying the target surface type of the object is increased, further improving the product yield of the object.

Re-usage of part of object or object is highly important in manufacturing industry as it can drastically reduce cost and time spent on manufacturing. However, lack of proper information about availability of similar parts leads to redesigning of similar part. Existing databases for engineering drawings do not store categorized information due to which performing feature-based search is not possible. Present application provides systems and methods for extracting, digitizing, and using engineering drawing data. The system receives engineering drawing document and extracts text data present in each cell of table provided in document. Once table data is extracted, isometric views and views other than isometric views that are present in document are identified by the system using pretrained machine learning based model. The system further extract view labels and coordinate information from identified views. The information extracted from document is then stored by the system as engineering drawing data for document.

Various techniques are provided for efficient bilinear interpolation of rotated pixels. In one example, a method includes identifying a rotation angle for an image; performing a vector load of pixel positions for the image at the rotation angle; performing a vector load of rows of pixels associated with the pixel positions; performing a vector selection of a subset of pixels from the rows of pixels based on the identified pixel positions; performing a vector load of a set of coefficients at the rotation angle; and applying the set of coefficients to the subset of pixels to determine an updated value for the image. Additional methods and systems are also provided.

The present disclosure is directed toward systems and methods that efficiently and effectively generate an enhanced document image of a displayed document in an image frame captured from a live image feed. For example, systems and methods described herein apply a document enhancement process to a displayed document in an image frame that result in an enhanced document image that is cropped, rectified, un-shadowed, and with dark text against a mostly white background. Additionally, systems and method described herein determine whether a stored digital content item includes a displayed document. In response to determining that a stored digital content item does include a displayed document, systems and methods described herein generate an enhanced document image of a displayed document included in the stored digital content item.

Techniques for providing remote messages to mobile devices based on image data and other sensor data are discussed herein. Some embodiments may include one or more servers configured to: receive, from a consumer device via a network, location data indicating a consumer device location of a consumer device; receive, from the consumer device via the network, image data captured by a camera of the consumer device; receive, from the consumer device via the network, orientation data defining an orientation of the camera when the image data was captured, wherein the orientation data is captured by an accelerometer of the consumer device; attempt to extract a merchant identifier from the image based on programmatically processing the image data; determine one or more merchants based on a fuzzy search of available ones of the location data, the merchant identifier, and the orientation data.

An artificial neural network-based method for selecting a surface type of an object includes receiving at least one object image, performing surface type identification on each of the at least one object image by using a first predictive model to categorize the object image to one of a first normal group and a first abnormal group, and performing surface type identification on each output image in the first normal group by using a second predictive model to categorize the output image to one of a second normal group and a second abnormal group.

Disclosed herein is a method and a device that can measure an unknown target coating; can search, based on the measured data of the target coating, a database for one or more best matching coating formulas, i.e. one or more preliminary matching formulas, within the database; and that can refine the search using an image similarity metric between images of the one or more best matching coating formulas on the one side and images of the target coating on the other side, using deep learning techniques.