An information processing device includes a processor configured to: group electronic documents that have been processed, based on similarity degree of the electronic documents into one or more groups; determine a group, among the one or more groups, to which at least one received electronic document is to belong; determine whether the at least one received document is a modified version of one or more electronic documents belonging to the determined group, the modified version having been partially modified with respect to the one or more electronic documents belonging to the determined group; and specify a blank portion in the at least one received electronic document by comparing the at least one received electronic document with the one or more electronic documents belonging to the determined group.

Organizations and educational institutions are turning towards digitization of their examination processes. The existing devices are costly, time consuming and insecure for scanning the answer sheets. A device for performing secure and automatic flipping and scanning of documents has been provided. The device is configured to be assembled in the form of a box. The device comprising a scanning stand, a page flipping arm, one or more suction cups, one or more rollers, a controller and a mobile device. The controller is configured to control the operation of the scanning stand, the page flipper arm and the roller. The mobile device further comprises a mobile application which is further configured to control controller. The device further configured to scan the handwriting of a candidate to avoid malpractice during the examination.

An image processing device includes: an image classifying section which, through a convolutional neural network, classifies each pixel of input image data as expressing or not expressing a handwritten image to calculate a classification probability of each pixel, the classification probability being a probability that the handwritten image is expressed; a threshold setting section which sets a first threshold when removal processing to remove the handwritten image is performed and a second threshold which is smaller than the first threshold when emphasis processing to emphasize the handwritten image is performed; and an image processor which adjusts a gradation value of pixels with a classification probability no smaller than the first threshold to remove the handwritten image when the removal processing is performed and adjusts the gradation value of pixels with a classification probability no smaller than the second threshold to emphasize the handwritten image when the emphasis processing is performed.

Organizations and educational institutions are turning towards digitization of their examination processes. The existing devices are costly, time consuming and insecure for scanning the answer sheets. A device for performing secure and automatic flipping and scanning of documents has been provided. The device is configured to be assembled in the form of a box. The device comprising a scanning stand, a page flipping arm, one or more suction cups, one or more rollers, a controller and a mobile device. The controller is configured to control the operation of the scanning stand, the page flipper arm and the roller. The mobile device further comprises a mobile application which is further configured to control controller. The device further configured to scan the handwriting of a candidate to avoid malpractice during the examination.

Provided is information processing apparatus that extracts a handwriting comment. A comment acquiring part searches handwriting comment from an image data of a scanned manuscript and acquire the handwriting comment in association with position information indicating the handwriting comment for an area of the manuscript. A filing part converts the handwriting comment acquired by the comment acquiring part into a file. An OCR part performs optical character recognition (OCR). A filing part performs OCR of the comment by the OCR part, and when recognizable as a character, converts character data of the handwriting comment into the file, and when unrecognizable as a character, acquires the area of the handwriting comment from image data of the manuscript and converts into the file.

The present disclosure relates to a system and method to transform character images from one representation to another representation. According to some embodiments of the present disclosure, a form may be processed to separate background data from content data, wherein character images from one or both the background data and the content data may be transformed. In some aspects, one or both handwritten font and type font may be processed in the character images, wherein the original fonts may be transformed into a uniform type font. In some embodiments, the character images may be translated to their correct state, wherein the translation may occur before or after the transformation. In some implementations, the translation and font transformation may allow for more efficient and effective character recognition.

The present disclosure relates to a system and method to transform character images from one representation to another representation. According to some embodiments of the present disclosure, a form may be processed to separate background data from content data, wherein character images from one or both the background data and the content data may be transformed. In some aspects, one or both handwritten font and type font may be processed in the character images, wherein the original fonts may be transformed into a uniform type font. In some embodiments, the character images may be translated to their correct state, wherein the translation may occur before or after the transformation. In some implementations, the translation and font transformation may allow for more efficient and effective character recognition.

A computer-implemented method for handwritten text line wrapping includes: obtaining, from a user, at least two words of handwritten text on a screen; determining an original bounding box for the at least two words; creating at least one line-break character for the at least two words; determining at least one baseline for the at least two words; determining a new bounding box for the at least two words based on the at least one baseline; generating, on the screen, a text box; moving, on the screen, at least one of the at least two words from a first line of at least one line of handwritten text to a second line of the at least one line of handwritten text, wherein the second line of handwritten text fits within the text box; and adjusting at least one gap between the at least one line of handwritten text.

A computer-implemented method for handwritten text line wrapping includes: obtaining, from a user, at least two words of handwritten text on a screen; determining an original bounding box for the at least two words; creating at least one line-break character for the at least two words; determining at least one baseline for the at least two words; determining a new bounding box for the at least two words based on the at least one baseline; generating, on the screen, a text box; moving, on the screen, at least one of the at least two words from a first line of at least one line of handwritten text to a second line of the at least one line of handwritten text, wherein the second line of handwritten text fits within the text box; and adjusting at least one gap between the at least one line of handwritten text.

A system learns the structure of a form. The structure of the form can be learned from a single image (e.g., a photograph that includes the form) without user annotation. The form includes typewritten and handwritten text entries. The system groups text entries in the form based on lines detected in the form. The system then measures a distance and an angle between two text entry locations in the group of text entries. The group of text entries, the distances, and the angles can be captured in a bipartite graph. The bipartite graph represents possible pairing solutions where a typewritten text entry is paired with a handwritten text entry. The system identifies an optimal pairing solution, from the possible pairing solutions, using the distances and angles. The optimal pairing solution is identified by minimizing the standard deviation of the distances and/or by minimizing the circular standard deviation of the angles.