An image processing apparatus obtains a read image of a document including a handwritten character, generates a first image formed by pixels of the handwritten character by extracting the pixels of the handwritten character from pixels of the read image using a first learning model for extracting the pixels of the handwritten character, estimates a handwriting area including the handwritten character using a second learning model for estimating the handwriting area, and performs handwriting OCR processing based on the generated first image and the estimated handwriting area.

Character recognition processing suitable to a handwritten character area and a printed character area among character areas in a scanned image of a document is performed. Next, character recognition results for the handwritten character area and character recognition results for the printed character area are integrated and a likelihood indicating a probability of being an extraction target is calculated for a candidate character string that is an extraction candidate among the integrated character recognition results and a character string that is the item value is determined. Then, at the time of the determination, different evaluation indications are used in a case where a character originating from the handwritten character area is included in characters constituting the candidate character string and in a case where such a character is not included.

Systems and methods for performing OCR of an image depicting text symbols and imaging a document having a plurality of planar regions are disclosed. An example method comprises: receiving a first image of a document having a plurality of planar regions and one or more second images of the document; identifying a plurality of coordinate transformations corresponding to each of the planar regions of the first image of the document; identifying, using the plurality of coordinate transformations, a cluster of symbol sequences of the text in the first image and in the one or more second images; and producing a resulting OCR text comprising a median symbol sequence for the cluster of symbol sequences.

An electronic apparatus and a data transmission method thereof are provided. The data transmission method is adapted to the electronic apparatus including a touch screen, and the data transmission method includes the following steps. An image frame is displayed through the touch screen. A connection with another electronic apparatus placed on the touch screen is established. Position information of said another electronic apparatus on the touch screen is detected through the touch screen, to capture a partial frame from the image frame according to the position information of said another electronic apparatus. Feature information of data to be transmitted is obtained from the partial frame. The data to be transmitted is sent to said another electronic apparatus via the connection according to the feature information.

An electronic device is provided. The electronic device includes a display, a sensing panel, and a processor operatively connected with the display and the sensing panel, wherein the processor is configured to display content on the display, display an object corresponding to a handwriting input on the content, based on the handwriting input sensed by the sensing panel, in response to a first keyword being recognized based on at least part of the handwriting input, perform character recognition on an additional handwriting input entered after input of the first keyword, and in response to a character recognition end event being identified, provide text obtained by the character recognition on the additional handwriting input as a hashtag for the displayed content.

The present disclosure discloses a method for recognizing text, an apparatus and a terminal device. The method for recognizing text includes: acquiring a sample text dataset, preprocessing text image in the sample text dataset, and generating a label image; inputting the label image into a text recognition model for training, extracting image features, performing down-sampling, restoring an image resolution, normalizing an output probability for the last layer using a sigmoid layer to output a multiple prediction maps with different scales, and optimizing a loss function of the text recognition model to obtain a trained text recognition model; preprocessing a text image to be recognized, inputting the text image to be recognized which is preprocessed into the trained text recognition model, and outputting a clear-scale prediction map; and analyzing the clear-scale prediction map to obtain a text sequence of the text image to be recognized.

Disclosed are systems, computer-readable mediums, and methods for creating a flexible structure description. To create the flexible structure description an image of a document of a particular document type that contains a table is received. An entry describing an item in the table is received. Title elements within the document are searched for based upon the entry. Data fields and anchor elements are detected for the entry. A flexible structure description for the particular document type is generated that includes a set of search elements for each data field in the image of the document and the title elements. The flexible structure description is matched against the image. Data from the image is extracted based upon the matching of the flexible structure description against the image.

Systems and methods for performing OCR of an image depicting text symbols and imaging a document having a plurality of planar regions are disclosed. An example method comprises: receiving a first image of a document having a plurality of planar regions and one or more second images of the document; identifying a plurality of coordinate transformations corresponding to each of the planar regions of the first image of the document; identifying, using the plurality of coordinate transformations, a cluster of symbol sequences of the text in the first image and in the one or more second images; and producing a resulting OCR text comprising a median symbol sequence for the cluster of symbol sequences.

The current modular implant is particularly useful in spinal surgical procedures. The modular implant can be provided with two anchors and a central section.

A system for capturing a product tag image, extracting product information, and validating information. The extracted information is then utilized to populate a universal (brand independent) product registration database. To incentivize end users to register their new and in service products, entry is simplified by the use of an application on a smartphone, tablet or personal computer. A user downloads an application and enters their information then takes at least one picture/scan/image of the product label(s) that contain: 1) manufacturer name (and/or brand name), 2) model number, 3) serial number; and 4) date of production. Said information is extracted by Optical Character Recognition (OCR) and then validated before entering said database.