9 results about "Document capture" patented technology

A system and methodology is provided in which image and video injection attack attempts, which may occur in connection with document or individual verification processes, can be detected and handled. The system and methodology of the present invention, in some embodiments, employs functionalities such as haptic vibration generation and accelerometer data typically present in existing user devices to implement attack detection and response.

The invention relates to a document scanner (10) comprising a housing (12) in which a document capture device (14) is arranged. The housing (12) has a scan opening (18) for the capture area (16) of the capture device (14), wherein the scan opening (18) is surrounded by a receiving area (20) of the housing (12) for a transparent support plate (22). The support plate (22) covers the scan opening (18) and serves to support a document to be scanned. According to the invention, a polymer seal (26) surrounding the scan opening (18) is arranged between the support plate (22) and the receiving area (20), making the document scanner (10) dustproof and splashproof according to protection class IP54 and thus suitable for outdoor use.

The invention relates to the technical field of deep learning and logistics document identification, in particular to a circular packaging logistics document identification and data processing method based on deep learning. The method includes: acquiring an original document image captured on site; obtaining a service context; performing physical state analysis processing on the original document image to obtain a physical state mask and a key information area physical entropy increase index; original data fragments, optical character recognition confidence and model uncertainty are obtained; combining the physical entropy increase index of the key information region, the optical character recognition confidence coefficient and the model uncertainty to solve a coupling data credibility score; based on the coupling data credibility score, the original data fragment and the service context, obtaining credible data; and generating structured data and actionable service suggestions according to credibility scores of the credible data and the coupled data. According to the method, the robustness and the environmental adaptability of circular packaging document identification in a complex field environment are remarkably improved.

Techniques are disclosed relating to automatically determining image quality for images of documents. In some embodiments, a computer system receives an image of a document captured at a user computing device. Using a neural network, the computer system analyzes the image to determine whether the image satisfies a quality threshold, where the analyzing includes determining whether one or more features in the image used in an authentication process are obscured. The computer system transmits, to the user computing device, a quality result, where the quality result is generated based on an image classification output by the neural network. Automatically determining whether a received image of a document satisfies a quality threshold may advantageously improve the chances of a system being able to complete an authentication process quickly, which in turn may improve user experience while reducing fraudulent activity.

An interactive terminal, comprising: a camera; a document capture system; an input-output interface; a display; a loudspeaker; a network interface; and a processing entity. The processing entity is configured for: transmitting a document captured by the document capture system to a remote server via the network interface; guiding a user through a transaction sequence that includes steps during which the user provides requested input via the input-output interface and steps during which the interactive terminal provides the user with audiovisual playback via the display and the loudspeaker; taking in-progress images of the user with the camera during the transaction sequence, the in-progress images used for validation of continued physical proximity of the user to the interactive terminal during the transaction sequence; and, in response to the validation being successful, proceeding to digital signing of documents via the input-output interface to complete the transaction. Certain embodiments disclosed herein contribute to making transactions more secure and efficient.

Embodiments are disclosed for automated bulk document capture. The method may include receiving an input video comprising a plurality of frames. The input video depicts a plurality of document pages to be captured. A first machine learning model is used to determine a page turn event has been depicted in the input video based at least on a first frame of the input video. A second machine learning model is used to determine that a first frame of the input video is ready for capture. An image of a document page depicted in the first frame is then captured.

An example system may include a document snapshot circuit structured to generate a document snapshot configured to capture a state of a document at a time marker and a document sharding circuit structured to analyze the document snapshot, and generate a first plurality of shard documents capturing the state of the document at the time marker. The system may include a document serving circuit structured to access the first plurality of shard documents, and provide at least a subset of the first plurality of shard documents to a client serving circuit structured to implement a unified document surface interface in response to the at least a subset of the first plurality of shard documents. The document serving circuit is configured to provide the subset of the first plurality of shard documents in an order determined to prioritize shards related to a last accessed location of the document.

A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and / or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.