The present disclosure prevents learning a miscorrection made by a user on an OCR result. Provided is an information processing apparatus including: a character recognition unit configured to extract a character string containing at least one character by performing character recognition on an image obtained by scanning of a document; a display control uniit configured to display the extracted character string on a display apparatus; an obtaining unit configured to receive a user correction on the extracted character string and obtaining a corrected character string based on the user correction; and a learning unit configured to learn a correction characteristic of a difference portion between the extracted character string and the corrected character string. The learning unit does not learn the correction characteristic of the difference portion in a case where a reliability level of the character recognition on the difference portion is equal to or above a predetermined threshold.

The invention comprises a printing method, comprising the steps of: marking a markable surface with a graphical code; loading into a plotter system the markable surface; receiving a print job related to the graphical code; and plotting the set of vectors on the markable surface, such as by identifying a particular media type of the markable surface with the graphical code, receiving into the plotter system a print job, the print job comprising: (1) the set of vectors; and (2) a printable media requirement; scanning, with the plotter system, the printable media code; and confirming the printable media requirement matches the particular media type.

The disclosure discloses a method for character recognition, an electronic device, and a storage medium. The technical solution includes: obtaining a test sample image and a test sample character both corresponding to a test task; performing fine-tuning on a trained meta-learning model based on the test sample image and the test sample character to obtain a test task model; obtaining a test image corresponding to the test task; and generating a test character corresponding to the test image by inputting the test image into the test task model.

A system is provided for a distributed server network with embedded image decoder as a chain code program runtime event. In particular, the system may comprise a distributed computing network comprising one or more decentralized nodes, each of which may store a separate copy of a distributed data register. The system may further comprise one or more specialized nodes which receive, assess, and analyze user input data, where the one or more specialized nodes may include a client identity node comprising an embedded image decoder which may be configured to analyze image portions of the user input data. Once the image data has been analyzed, the client identity node may convert the image data into a text format for storage within the distributed register.

The current modular implant is particularly useful in spinal surgical procedures. The modular implant can be provided with two anchors and a central section.

Systems and methods for automatic enrollment and identity verification based upon processing a captured image of a document are disclosed herein. Various embodiments enable, for example, a user to enroll in a particular service by taking a photograph of a particular document (e.g., his driver license) with a mobile device. One or more algorithms can then extract relevant data from the captured image. The extracted data (e.g., the person's name, gender, date of birth, height, weight, etc.) can then be used to automatically populate various fields of an enrollment application, thereby reducing the amount of information that the user has to manually input into his mobile device in order to complete the enrollment process. In some embodiments, a set of internal and/or external checks can be run against the data to ensure that the data is valid, has been read correctly, and is consistent with other data.

Systems and methods for document analysis. An image containing at least one document is received at a pre-processing stage and the image is analyzed for image quality. If the image quality is insufficient for further processing, this is adjusted until the image is suitable for further processing. After the image quality adjustment, the image is then passed to an initial processing stage. At the initial processing stage, the boundaries of one or more documents within the image are determined. In addition, the orientation of the image may be adjusted and the type of document(s) within the image is determined. From the initial processing stage, the adjusted image is then passed to a data extraction stage. At this stage, clusters of data within the document are determined and bounding boxes are placed around the clusters. Data regarding each of the clusters of data is then gathered.

The invention comprises an apparatus and method of use thereof for processing a machine produced emulated handwritten document prepared on a marking surface, comprising the steps of: receiving a print job order; digitally generating a reference image of the print job order; machine plotting with a plotting pen and a downward force of one-half to forty ounces applied to said plotting pen an indentation trail to form input text on the marking surface; digitally imaging the input text on the marking surface to form an actual image; and in a quality control step, digitally comparing the reference image to the actual image prior to insertion of the print job order into an envelope.

The present subject matter is related in general to the field of image processing, disclosing method and system for evaluating an image quality for Optical Character Recognition (OCR) Image evaluation system receives image comprising optical character data. The image evaluation system determines image parameter value for each of one or more image parameters of the image. The image parameter value for each of the one or more image parameters is determined for plurality of binary image segments identified in the image. The image evaluation system determines suitability value and impact value of the image, based on the image parameter value for each of the image parameters determined for the image. The image evaluation system determines quality score for the image, based on the suitability value and the impact value. The image is transmitted for processing before the OCR, upon determining the quality score to be above overall pre-defined threshold value.

The current modular implant is particularly useful in spinal surgical procedures. The modular implant can be provided with two anchors and a central section.