Embodiments are directed to techniques for image content extraction. Some embodiments include extracting contextually structured data from document images, such as by automatically identifying document layout, document data, document metadata, and/or correlations therebetween in a document image, for instance. Some embodiments utilize breakpoints to enable the system to match different documents with internal variations to a common template. Several embodiments include extracting contextually structured data from table images, such as gridded and non-gridded tables. Many embodiments are directed to generating and utilizing a document template database for automatically extracting document image contents into a contextually structured format. Several embodiments are directed to automatically identifying and associating document metadata with corresponding document data in a document image to generate a machine-facilitated annotation of the document image. In some embodiments, the machine-facilitated annotation may be used to generate a template for the template database.

Techniques are disclosed for sharing user markings between digital documents and corresponding physically printed documents. The sharing is facilitated using an Augmented Reality (AR) device, such as a smartphone or a tablet. The device streams images of a page of a book on a display. The device accesses a corresponding digital document that is a digital version of content printed on the book. In an example, the digital document has a digital user marking, e.g., a comment associated with a paragraph of the digital document, wherein a corresponding paragraph of the physical book lacks any such comment. When the device streams the images of the page of the book on the display, the device appends the digital comment on the paragraph of the page of the book within the image stream. Thus, the user can view the digital comment in the AR environment, while reading the physical book.

An image processing apparatus includes an acquisition unit configured to acquire a read image obtained by reading a printed document, and a determination unit configured to determine presence or absence of a streak included in the read image, by tracking a contour of the printed document from each of a plurality of points that are both end points of the read image in a direction orthogonal to a reading direction of the read image.

Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a plurality of filters to the training image to provide a respective plurality of filtered training images, identifying a filter to be associated with the hash pattern based on the plurality of filtered training images, and storing a mapping of the filter to the hash pattern within a set of mapping in a data store.

Systems and methods for identifying landmarks of a document from a digital representation of the document. The method comprises accessing the digital representation of the document and operating a Machine Learning Algorithm (MLA), the MLA having been trained based on a set of training digital representations of documents associated with labels. The operating the MLA comprises down-sampling the digital representation of the document, detecting landmarks, generating fractional pixel coordinates for the detected landmarks. The method further determines the pixel coordinates of the landmarks by upscaling the fractional pixel coordinates from the second resolution to the first resolution and outputs the pixel coordinates of the landmarks.

Systems and methods for overlaying an image of a conference call participant with a shared document are provided. A request is received to initiate a document sharing operation to share a document displayed via a first graphical user interface (GUI) on a first client device associated with a first participant of a conference call with a second participant of the conference call via a second GUI on a second client device. Image data corresponding to a view of the first participant in a surrounding environment is also received. An image depicting the first participant is obtained based on the received image data. One or more regions of the document that satisfy one or more image placement criteria are identified. The document and the image depicting the first participant are provided for presentation via the second GUI on the second client device. The image depicting the first participant is presented at a region of the identified one of more regions of the document.

A computerized system, apparatus, and method of grading collectibles. The system comprises a grading apparatus that receives at least one image of the collectible. The grading apparatus applies at least one processing routine to said at least one image. The grading apparatus generates a grade report of the collectible based at least on results of the at least one processing routine. The system comprises an encasing apparatus configured to encase the graded collectible within a protective slab.

Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image; optionally sampling color information from a second plurality of pixels of the digital image, wherein each of the second plurality of pixels is located in a foreground region of the digital image; assigning each pixel a label of either foreground or background using an adaptive label learning process; binarizing the digital image based on the labels assigned to each pixel; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.

The present disclosure relates to generating fillable digital forms corresponding to paper forms using a form conversion neural network to determine low-level and high-level semantic characteristics of the paper forms. For example, one or more embodiments applies a digitized paper form to an encoder that outputs feature maps to a reconstruction decoder, a low-level semantic decoder, and one or more high-level semantic decoders. The reconstruction decoder generates a reconstructed layout of the digitized paper form. The low-level and high-level semantic decoders determine low-level and high-level semantic characteristics of each pixel of the digitized paper form, which provide a probability of the element type to which the pixel belongs. The semantic decoders then classify each pixel and generate corresponding semantic segmentation maps based on those probabilities. The system then generates a fillable digital form using the reconstructed layout and the semantic segmentation maps.

Systems and methods for automatic generation of a content presentation plan are disclosed herein. The method can include receiving content identification information, retrieving objective information for the one or several objectives identified for inclusion in a content presentation plan, identifying at least one prerequisite skill for completion of at least one of the one or several objectives, generating at least one remediation question configured to delineate between users having mastery of the at least one prerequisite skill and users not having mastery of the at least one prerequisite skill, pre-selecting remedial content for providing to users identified as not having mastery of the at least one prerequisite skill, selecting objective content corresponding to the at least one objectives, and creating a content presentation plan containing the at least one remediation question, the remedial content, and the objective content.