Estimating a material property parameter of fabric involves receiving information including a three-dimensional (3D) contour shape of fabric placed over a 3D geometric object, estimating a material property parameter of the fabric used for representing drape shapes of 3D clothes made by the fabric by applying the information to a trained artificial neural network, and providing the material property parameter of the fabric.

A system and method for correcting image data is disclosed. The method includes receiving one or more documents from one or more electronic mediums. The method further includes determining a primary character and one or more alternate characters corresponding to the mis-captured character image, extracting one or more confident instances of the primary character and the one or more alternate characters from the one or more documents and generating one or more scores corresponding to the primary character and the one or more alternate characters. Further, the method includes predicting a correct character corresponding to the mis-captured character image by using a trained image prediction-based ML model and automatically replacing the mis-captured character image with the predicted correct character.

Methods and systems for extracting and processing data using optical character recognition in real-time environments. For example, the methods and systems provide novel techniques during extracting data using OCR and for a mechanism to process that data. These methods and systems are particularly relevant in real-time environments as the methods and system limit the need for manual review.

An image processing apparatus includes a control unit configured to acquire image data generated through reading of an original document, and acquire, through character recognition, a character string included in the image data. The control unit performs a first process and a second process. The first process is configured to acquire, through character recognition, the character string of which region is designated with a first identification mark in the image data, and a second identification mark differing from the first identification mark is further added to the character string. The second process uses the character string acquired in the first process.

Apparatuses and methods of operating apparatuses are disclosed. An apparatus comprises a flexible substrate and circuitry fabricated on the flexible substrate to perform data processing. At least one strain detector generates a strain signal which is dependent on a flexing state of the strain detector on the flexible substrate. A strain history control unit samples the at least one strain signal from the at least one strain detector at a plurality of time points and records a strain snapshot at each time point comprising data dependent on the at least one strain signal from the at least one strain detector. The data processing performed by the circuitry is dependent on the plurality of strain snapshots recorded.

The present invention is directed to a computer application for analyzing handwriting. The handwriting is digitized by being captured by a computing device such as a tablet. The application analyzes four components of the digitized handwriting. The initial component provides real-time writing speed feedback to the subject. The second fully automated component computes a variety of kinematic measures based on periods of time when the subject is writing versus the pen being off the tablet. A third component is able to concatenate pen strokes into user defined characters and assesses character and/or word spacing based on preset distances. For the fourth component, a 2-dimensional version of the large deformation diffeomorphic metric mapping (LDDMM) method is used to compare each character to a template character. Together, these components can be used to assess handwriting for a broad range of applications.

Methods and systems for extracting and processing data using optical character recognition in real-time environments. For example, the methods and systems provide novel techniques during extracting data using OCR and for a mechanism to process that data. These methods and systems are particularly relevant in real-time environments as the methods and system limit the need for manual review.

Systems and methods of verifying pairings of price tag labels and products at a product storage facility include an image capture device that moves about and captures images of product storage structures at the product storage facility, and a database that stores inventory data associated with the products stocked at the product storage facility. A computing device processes the images to extract one or more characters from the price tag labels and products detected in the images, correlates the extracted characters to the inventory data to identify a product code and a product name that matches the characters extracted from the price tag labels and the products. If the characters extracted from the price tag and from the on-shelf product to which the price tag label is allocated match, the database is updated to reflect that the price tag label is properly allocated to the appropriate on-shelf product.

A document creation support apparatus comprising at least one processor, wherein the processor is configured to: acquire an image and a character string related to the image; extract at least one feature region included in the image; specify a specific region that is a region corresponding to a phrase included in the character string, in the feature region; and present information for supporting creation of a document including the character string based on a result of the specifying.

Embodiments are described for a system comprising a memory and at least one processor coupled to the memory. The at least one processor is configured to receive optical character recognition (OCR) information of a document and determine a beginning, inside, and outside (BIO) tags and labels of the one or more word boxes based on the OCR information. The at least one processor is further configured to group a first word box and a second word box based on BIO tags of the first and the second word boxes and merge the first and the second word boxes into a combined word box based on a label of the first word box matching a label of the second word box. Finally, the at least one processor is configured to output the combined word box and the label of the first word box.