According to one embodiment, an electronic apparatus performs a character recognition process, uses, if a stroke in a first area of the first handwritten document and a stroke in a second area are the same, a character recognition result of the first handwritten document, and performs, if a stroke in the first area and a stroke in the second area are different, the character recognition process for the second area including the different stroke.

The subject technology provides for receiving a new input stroke. The subject technology determines whether the new input stroke is associated with an existing line group based on a writing direction estimate of the existing line group. The subject technology merges the new input stroke with the existing line group in response to determining that the new input stroke is associated with the existing line group. The subject technology determines a local orientation of the existing line group including the new input stroke based on an estimate of a direction of writing and a scale of each stroke. The subject technology normalizes the existing line group including the new input stroke using the determined location orientation.

An information processing apparatus includes a processor configured to acquire each recognition result output by each of plural different recognition processes for the same image, and execute, in relation to the recognition result selected from among the recognition results output by each of the plural recognition processes, a postprocess corresponding to the recognition process from which the selected recognition result is output.

A system and method for classifying images of an evidence, the method including: generating an unlabeled template based on a first received image, wherein the unlabeled template includes a first set of regions of interest (ROIs); selecting a labeled template that includes a second set of ROIs from a plurality of labeled templates determined to be a best match for the unlabeled template; checking at least an ROI of the first set of ROIs for content that corresponds to a label of an equivalent ROI of the second set of ROIs; and, classifying the first image upon determination that the content checked corresponds to the label according to the labeled template.

A position detection apparatus includes a sensor that detects a position pointed to by an electronic pen and circuitry that acquires pen state information regarding the electronic pen held by a person; a transmitter that transmits to an emotion estimation apparatus an emotional state estimation request including the acquired pen state information, the emotion estimation apparatus including a database that stores information regarding an emotional state of the person holding the electronic pen and range information regarding a range of values that may be taken by the pen state information regarding the electronic pen, the emotional state and the range information being associated with one another; and a processor that receives information corresponding to the emotional state transmitted from the emotion estimation apparatus in response to the pen state information included in the transmitted emotional state estimation request, and performs processing using the received information corresponding to the emotional state.

Provided is an input feedback-based smart pen including: a main body having a shape that enables manipulation of a user; an input unit connected to the main body and performing an input operation by a manipulation of the user; an input information recognition unit configured to recognize information input by a user through the manipulation of the input unit; and an expression unit including one or more expression members formed in an area of an outer surface of the main body to be detectable by the user to express information corresponding to input information recognized by the input information recognition unit.

An electronic device includes an input configured to receive a signature from a user; a communication interface configured to communicate with a server; and a controller configured to classify the signature into at least one stroke, to transmit authentication information for the at least one stroke to the server, and to control the communication interface to receive a result of authentication of the signature from the server.

An information processing apparatus includes a receiving unit and a controller. The receiving unit receives an extraction-area image indicating an extraction area. The extraction area includes a fill-in area in which a writer handwrites information. When an instruction to correct a recognition result for the information written in the fill-in area indicated by the extraction-area image is given, the controller causes a display unit to display a different extraction-area image similar to the extraction-area image.

In some implementations, a device may receive an image that depicts handwritten text. The device may determine that a section of the image includes the handwritten text. The device may analyze, using a first image processing technique, the section to identify subsections of the section that include individual words of the handwritten text. The device may reconfigure, using a second image processing technique, the subsections to create preprocessed word images associated with the individual words. The device may analyze, using a word recognition model, the preprocessed word images to generate digitized words that are associated with the preprocessed word images. The device may verify, based on a reference data structure, that the digitized words correspond to recognized words of the word recognition model. The device may generate, based on verifying the digitized words, digital text according to a sequence of the digitized words in the section.

Technology is descried herein for parsing an ink document having a plurality of ink strokes. The technology performs stroke-level processing on the plurality of ink strokes to produce stroke-level information, the stroke-level information identifying at least one characteristic associated with each ink stroke. The technology also performs object-level processing on individual objects within the ink document to produce object-level information, the object-level information identifying one or more groupings of ink strokes in the ink document. The technology then parses the ink document into constituent parts based on the stroke-level information and the object-level information. In some implementations, the technology converts the ink stroke data into an ink image. The stroke-level processing and/or the object-level processing may operate on the ink image using one or more neural networks. More specifically the stroke-level processing can classify pixels in the input image, while the object-level processing can identify bounding boxes containing possible objects.