A method and a system are described for performing optical character recognition on an image including a plurality of printed characters. The method includes defining one or more opcodes and direction pointers associated with the plurality of printed characters of a language and a font type, wherein each of the one or more opcodes has an associated unique opcode characterization value. The method includes creating a binary tree comprising a plurality of nodes, wherein each node of the plurality of nodes is assigned the unique opcode characterization value. The method includes retrieving a set of operations associated with the unique opcode characterization value assigned to each of the plurality of nodes. The method includes navigating the binary tree from a root node to a leaf node based on the set of operations, the first pointer value, and the second pointer value until the leaf node is reached.

Methods, systems, and computer-readable media related to a technique for providing handwriting input functionality on a user device. A handwriting recognition module is trained to have a repertoire comprising multiple non-overlapping scripts and capable of recognizing tens of thousands of characters using a single handwriting recognition model. The handwriting input module provides real-time, stroke-order and stroke-direction independent handwriting recognition. User interfaces for providing the handwriting input functionality are also disclosed.

For an identification of packing units, data resulting from an optical recording of at least one surface of a packing unit undergo a text recognition to recognize individual characters. A plurality of characteristic values is determined, each characteristic value being based on another predetermined statistical analysis of the recognized characters. The plurality of characteristic values forms at least one part of an identification of the packing unit. The characteristic values are provided for storage and/or for comparison with previously stored characteristic values.

The technology described herein employs techniques for overlaying (superimposing) translated text on top of (over) scanned text in realtime. The technology recognizes text in an image and identifies a first language in which the text is written. The technology translates the text into a second language and generates an overlay in the second language. The overlay is then inserted into the display over the text in the image.

The present disclosure relates to system(s) and method(s) for compression and decompression of Unicode characters. The system is configured to maintain a set of character tables and a cluster table in a memory. Each character table is configured to store a set of Unicode characters corresponding to a character class of a set of characters classes, wherein each Unicode character from the character table is assigned with a shortened bit representation. Furthermore, the cluster table may be configured to maintain a set of cluster types and a cluster identifier corresponding to each of the cluster type. The system is configured to compress text data in Unicode format using the set of character tables and the cluster table by identifying the different clusters in each word and replacing the clusters with cluster identifier followed by the shorten bit representation of characters in each cluster.

The technology described herein employs techniques for overlaying (superimposing) translated text on top of (over) scanned text in realtime. The technology recognizes text in an image and identifies a first language in which the text is written. The technology translates the text into a second language and generates an overlay in the second language. The overlay is then inserted into the display over the text in the image.

Methods, systems, and computer-readable media related to a technique for providing handwriting input functionality on a user device. A handwriting recognition module is trained to have a repertoire comprising multiple non-overlapping scripts and capable of recognizing tens of thousands of characters using a single handwriting recognition model. The handwriting input module provides real-time, stroke-order and stroke-direction independent handwriting recognition. User interfaces for providing the handwriting input functionality are also disclosed.

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.

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.

In a case where a single image is formed by reading one or more reading sheets multiple times, and if the reading sheets are not appropriately placed on a document platen, images of the plurality of reading sheets formed in the single image do not match each other in up, down, left, and right or vertical and horizontal relationships desired by a user. An image forming apparatus includes a display unit configured to, based on a direction of a character string obtained from an image obtained by reading a first surface and a direction of a character string obtained from an image obtained by reading a second surface, display information regarding whether a direction of a reading sheet relative to a predetermined reference is excellent or poor.