An input apparatus includes a handwriting input unit configured to receive a handwritten input using a position of a pen or a user's finger in contact with a display; and a display unit configured to display the handwritten input received by the handwriting input unit on the display as a handwritten object. The input apparatus is configured to, in response to no occurrence of a change in the handwritten object during a first period, display one or more operation commands on the basis of the handwritten object.

Aspects of the present disclosure involve systems and methods for an automated machine learning partitioning of a digital image file into multiple documents. The machine learning system may obtain or receive a digital image file that includes multiple documents merged into the single image file. To determine the different documents included in the image file, the machine learning model may analyze the content of the pages of the image file to determine particular content that may indicate the start and/or end of documents within the image file and partition the image file into multiple documents based on the determined start and/or end of the documents. In one instance, the machine learning partitioning system may generate an analysis window that comprises two pages of the corpus of pages and compare features or content of the two pages or determine if either of the two pages includes one or more features.

An information processing apparatus includes a first designation unit, a second designation unit, a position acquisition unit, a memory, and an extraction unit. The first designation unit designates an extensive area from a first read image, the extensive area including an output area and an object area. The second designation unit designates the output area from the designated extensive area. The position acquisition unit acquires positional information regarding the extensive area with respect to the first read image and positional information regarding the output area with respect to the extensive area. The memory stores the positional information regarding the extensive area and the positional information regarding the output area. The extraction unit identifies a position of the extensive area in a second read image in a format identical to a format of the first read image on a basis of the positional information regarding the extensive area stored by the memory. The extraction unit also extracts the output area in the second read image on a basis of the position of the extensive area and the positional information regarding the output area stored by the memory.

Provided is an information processing apparatus that applies correction using a character recognition error pattern to a character recognition result of a document image, wherein the character recognition error pattern includes error pattern information on a character recognition result of a part where an error occurs in character recognition, correct pattern information applicable to the part where the error occurs, information on a frequency that the error occurs, and information on a state where the error occurs, and wherein the character recognition error pattern to be used in the correction is narrowed down based on the information on the frequency that the error occurs and the information on the state where the error occurs.

In the case of learning a printed character region selected by a user, it is determined whether a handwritten character region is present near the printed character region. If it is determined that the handwritten character region is present near the printed character region, information about the handwritten character region present near the printed character region and information about another printed character region present near the printed character region are learned in association with information about the selected printed character region. This makes it possible to appropriately determine a circled character string and a character string selected with a check mark from among a plurality of options during a scanned image analysis.

On a user interface screen for a user to set a rule relating to property information used for filing a document image and distributing the document image into a folder, at least a first area for editing the rule, a second area displaying a plurality of items selectable by a user, and a third area displaying an image of a sample document are provided. Then, in a case where a particular item being displayed in the second area is activated by a mouse hover, a character area in the image of the sample document being displayed in the third area is highlighted, which corresponds to the particular item activated by the mouse hover.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating marked digital images with content adaptive watermarks. In particular, in one or more embodiments, the disclosed systems intelligently evaluate a plurality of watermark configurations to select one or more content adaptive watermarks for one or more target digital images and generate one or more marked digital images by adding the selected content adaptive watermarks to the one or more target digital images.

Technology is described herein for facilitating a user's interaction with a digital ink document. The technology internally represents the ink document using a data structure having a hierarchy of nodes. The nodes describe respective elements in the ink document. The technology leverages the data structure to identify a set of nodes that grows upon the user's repeated selection of a particular part of the ink document. At each stage of the selection, the technology highlights a set of elements in the ink document that correspond to the current set of identified nodes. According to another illustrative aspect, the technology produces the data structure by modifying an original data structure provided by a text analysis engine. The technology performs this task with the objective of accommodating structured interaction by the user with the ink document.

Technology is described herein for facilitating a user's interaction with a digital ink document. The technology internally represents the ink document using a data structure having a hierarchy of nodes. The nodes describe respective elements in the ink document. The technology leverages the data structure to identify a set of nodes that grows upon the user's repeated selection of a particular part of the ink document. At each stage of the selection, the technology highlights a set of elements in the ink document that correspond to the current set of identified nodes. According to another illustrative aspect, the technology produces the data structure by modifying an original data structure provided by a text analysis engine. The technology performs this task with the objective of accommodating structured interaction by the user with the ink document.

The present disclosure generally relates to methods and user interfaces for managing visual content at a computer system. In some embodiments, methods and user interfaces for managing visual content in media are described. In some embodiments, methods and user interfaces for managing visual indicators for visual content in media are described. In some embodiments, methods and user interfaces for inserting visual content in media are described. In some embodiments, methods and user interfaces for identifying visual content in media are described. In some embodiments, methods and user interfaces for translating visual content in media are described.