A system for automated user input alignment receives the user input at a touchscreen display. A skew of the user input is identified as the user input is being received at a touchscreen display. A skew correction is determined based on the identified skew. The skew correction is applied to the user input to align the user input on the touchscreen display. The skew correction applied in an automated alignment process that. The user input is displayed with the applied skew correction on the touchscreen display with improved efficiency and without user manipulation to perform the alignment.

Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding. An example apparatus for processing a receipt associated with a user disclosed herein includes an optical character recognition engine to generate bounding boxes, respective ones of the bounding boxes associated with groups of characters detected in the receipt, the bounding boxes including a first bounding box, a second bounding box and a third bounding box, a word connector to connect the first bounding box to the second bounding box based on (1) an adjacency of the first bounding box to the second bounding box and (2) a difference value from a comparison of a location of the first bounding box to a location of the second bounding box, a line connector to form a line of the ones of the bounding boxes by connecting the third bounding box to the second bounding based on a relationship between the first bounding box and the second bounding box, the line of the ones of the bounding boxes indicative of related receipt fields, and a creditor to generate a report based on the line.

A method, a device, a terminal and a storage medium for acquiring slant value of slant image are provided. The method for acquiring slant value of a slant image comprises: analyzing the slant image and acquiring coordinate information of a plurality of boundary lines of the slant image; acquiring first slant values of the boundary lines by analysing and calculating the coordinate information; acquiring a correction value; calculating difference values between the first slant values and the correction value respectively; determining the first slant value corresponding to the minimum difference value as the slant value of the slant image. The technical solution of the present disclosure can uniquely determine a slant value of slant image.

Devices and methods are disclosed generating input. In one implementation, a stylus is provided for generating writing input. The stylus includes an elongated body having a distal end, and a light source configured to project coherent light on an opposing surface adjacent the distal end. The stylus further includes at least one sensor configured to measure first reflections of the coherent light from the opposing surface while the distal end moves in contact with the opposing surface, and to measure second reflections of the coherent light from the opposing surface while the distal end moves above the opposing surface and out of contact with the opposing surface. The stylus also includes at least one processor configured to receive input from the at least one sensor and to enable determining three dimensional positions of the distal end based on the first reflections and the second reflections.

This disclosure relates generally to a system and method for masking text within images. Conventionally, image masking approaches have enabled masking but masking PI data which contains sensitive data is still a challenge. The present disclosure includes training and masking phase, wherein during training phase the PI label and values of the input image are captured and stored as co-ordinates in the database. During masking, the test image and the words comprised in the test image are optimized using an OCR technique. The label and value of each pairs are compared with the words comprised in the optimized test image. The comparison results in one or more matching labels and then a masking area is calculated for each matching label. The masking string is generated for each matching label based on the calculated masking area and the original text is masked with the generated string.

A method for identifying information carried on a sheet is disclosed. The method comprises: identifying, using one or more computing devices, each of one or more areas on the sheet based on an image of the sheet and a pre-trained first model, wherein each of the one or more areas is associated with all or part of the information carried on the sheet, and the first model is a neural network based model; and identifying, using one or more computing devices, characters in each of the one or more areas based on the image of the sheet, each of the one or more areas and a pre-trained second model so as to determine the information carried on the sheet, wherein the second model is a neural network based model.

A text extraction computing method that comprises calculating an estimated character pixel height of text from a digital image. The method may scale the digital image using the estimated character pixel height and a preferred character pixel height. The method may binarizes the digital image. The method may remove distortions using a neural network trained by a cycle GAN on a set of source text images and a set of clean text images. The set of source text images and clean text images are unpaired. The source text images may be distorted images of text. Calculating the estimated character pixel height may include summarizing the rows of pixels into a horizontal projection, and determining a line-repetition period from the projection, and quantifying the portion of the line-repetition period that corresponds to the text as the estimated character pixel height. The method may extract characters from the digital image using OCR.

Biometric data are obtained from biometric sensors on a stand-alone computing device, which may contain an ASIC, connected to or incorporated within it. The computing device and ASIC, in combination or individually, capture biometric samples, extract biometric features and match them to one or more locally stored, encrypted templates. The biometric matching may be enhanced by the use of an entered PIN. The biometric templates and other sensitive data at rest are encrypted using hardware elements of the computing device and ASIC, and/or a PIN hash. A stored obfuscated Password is de-obfuscated and may be released to the authentication mechanism in response to successfully decrypted templates and matching biometric samples. A different de-obfuscated password may be released to authenticate the user to a remote or local computer and to encrypt data in transit. This eliminates the need for the user to remember and enter complex passwords on the device.

A data ingestion system normalizes ingested documents and extracts data based on a template that is applied to the documents. In an aspect, the system accesses a document of a document type and determines a template to apply to the document. The system normalizes the document, extracts data values from the document based at least in part on the template, and generates structured data based at least partly on the extracted data.

The present application discloses an image processing method, apparatus, electronic device and computer readable storage medium. The image processing method comprises detecting a text region in an image to be processed, recognizing the text region to obtain a text recognition result. In this application, the text recognition in the image to be processed is realized, the recognition manner for the text in the image is simplified, and the recognition effect for the text is improved.