The present disclosure relates to simulating the capture of images. In some embodiments, a document and a camera are simulated using a three-dimensional modeling engine. In certain embodiments, a plurality of images are captured of the simulated document from a perspective of the simulated camera, each of the plurality of images being captured under a different set of simulated circumstances within the three-dimensional modeling engine. In some embodiments, a model is trained based at least on the plurality of images which determines at least a first technique for adjusting a set of parameters in a separate image to prepare the separate image for optical character recognition (OCR).

Aspects of the present disclosure are directed to extracting textual information from image documents. In one embodiment, a system, upon receiving a request to extract textual information from an image document, a digital processing system performs character recognition based on content of the image document using multiple approaches to generate corresponding texts. The texts are then combined to determine a result text representing the textual information contained in the image document. The result is then provided as a response to the request.

Aspects of the present disclosure are directed to extracting textual information from image documents. In one embodiment, a system, upon receiving a request to extract textual information from an image document, a digital processing system performs character recognition based on content of the image document using multiple approaches to generate corresponding texts. The texts are then combined to determine a result text representing the textual information contained in the image document. The result is then provided as a response to the request.

A digital camera processing system with software to manage taking photos with a digital camera. Camera software controls the digital camera. A downloaded software component controls the digital camera software and causes a handheld mobile device to perform operations. The operations may include instructing a user to have the digital camera take photos of a check; displaying an instruction on a display of the handheld mobile device to assist the user in having the digital camera take the photos; or assisting the user as to an orientation for taking the photos with the digital camera. The digital camera processing system may generate a log file including a bi-tonal image formatted as a TIFF image.

A method involves detecting primary entities in a document, involving determining that a subset of the primary entities are associated with a first primary entity type, and determining a second primary entity type of one of the primary entities. The method further involves processing the primary entity of the second primary entity type to determine a secondary entity type of the primary entity. The secondary entity type is a subcategory of the second primary entity type. The method also involves hierarchically organizing the primary entities into a document layout structure that includes a top level and a child level. The top level is established by the first subset of primary entities based on the first primary entity type identifying the first subset as headings, and the child level is established by the primary entity based on the second primary entity type, the child level identifying the secondary entity type.

A method involves detecting primary entities in a document, involving determining that a subset of the primary entities are associated with a first primary entity type, and determining a second primary entity type of one of the primary entities. The method further involves processing the primary entity of the second primary entity type to determine a secondary entity type of the primary entity. The secondary entity type is a subcategory of the second primary entity type. The method also involves hierarchically organizing the primary entities into a document layout structure that includes a top level and a child level. The top level is established by the first subset of primary entities based on the first primary entity type identifying the first subset as headings, and the child level is established by the primary entity based on the second primary entity type, the child level identifying the secondary entity type.

The APPARATUSES, METHODS AND SYSTEMS FOR A VIDEO REMOTE DEPOSIT CAPTURE PLATFORM (hereinafter RDC-Video) provides a platform for remote deposit by obtaining images of a check from streaming video captured by a video camera, wherein the RDC-Video transforms captured check images and/or entered check deposit information inputs via RDC-Video components into deposit confirmation outputs. For example, in one embodiment, a user may employ a personal computer connected to a web camera, and/or a smartphone with a built-in camera to initiate the remote deposit by holding a check in front of the camera, and the RDC-Video may capture images of the check and send them to a financial institution for deposit processing.

Remote deposit of checks can be facilitated by a financial institution. A customer's general purpose computer and image capture device may be leveraged to capture an image of a check and deliver the image to financial institution electronics. Additional data for the transaction may be collected as necessary. The transaction can be automatically accomplished utilizing the images and data thus acquired.

A projector and a projection method are provided. The projector includes a control device, a projection optical engine, a distance sensing device, and an image capturing device. The projection optical engine projects a first projection image to a projection surface according to first image data. The distance sensing device senses multiple distance parameters of a projection area. The image capturing device captures the first projection image to obtain a first captured image. The control device performs a keystone correction operation and a leveling correction operation on the first image data. The projection optical engine projects a second projection image to the projection surface according to the corrected first image data. The control device obtains a second captured image including the second projection image through the image capturing device, and analyzes the second captured image to project current projection image size information in the second projection image.

Disclosed herein are a text recognition method and apparatus based on hand interaction for AR glasses. The text recognition method based on hand interaction for AR glasses includes collecting RGB images, extracting hand joint information from the RGB images, generating a text image based on the hand joint information, recognizing text from the text image, and outputting the recognized text.