The system prepares PDF documents to be digitally populated or signed. The method may comprise converting a document into an image; detecting words on the document; searching the words for keywords; searching for an object on the document; determining an object field based on the keywords and the object; creating a tag with metadata about the object field; and associating the tag with the object field. The method may also comprise determining, by a processor, metadata about a document; creating, by the processor, a hash from the metadata; storing, by the processor, an association of the hash, the metadata and the document in a knowledge database; creating, by the processor, a new hash for a new document; comparing, by the processor, the hash with the new hash; and determining, by the processor, that the new document has similar characteristics as the document based on the comparing.

Image analysis using visual geometry as an anchor for optical character recognition can be configured to receive an image acquired by a camera. The image is analyzed to detect a location within the image having a specified geometry. The specified geometry can be a predefined, visual geometry. The image is divided to create an image segment, where the image segment is based on the location of the specified geometry within the image. The image segment is analyzed to detect one or more characters within the image segment. The one or more characters in the image segment are decoded. A character string is generated based on decoding the one or more characters in the image segment.

A sales data processing system includes a first reader that reads a code symbol as a visible image included in image information output by an imaging unit, a second reader that reads a code symbol as an invisible image in the image information, and a third reader that recognizes a service image in the image information. The system includes a registrar that registers information as sales data on a commodity identified by the code symbol read by the first or second reader, and a standby processor that suspends reading by the second reader and waits for recognition of a service image by the third reader in response to a commodity being identified by the code symbol read by the second reader. The system includes a service processor that reflects a service in the sales data registered by the registrar in response to the third reader recognizing the service image.

A method for detecting security holograms on documents in a video stream is disclosed, including: searching for interest points and calculating descriptors in a frame; filtering of interest points in the previous frame so that only points located inside the quadrangle of the outer borders of the document remain; matching the descriptors of interest points of the current and previous frames; application of an algorithm for estimating the parameters of projective transformation between the frames; projective transformation of the quadrangle of the outer boundaries of the document from the previous frame to obtain the outer boundaries of the document in the current frame; document image normalization; calculating the color saturation and hue; updating the saturation and hue values; further considering the pixels of the normalized document image with brightness values not exceeding a preset threshold; filtration of the obtained image.

A monitoring device includes an acquisition unit configured to acquire a captured image of a display panel of a control device configured to control an analyzer, an image storage unit configured to store the captured image, and a state determination unit configured to determine a state of the analyzer based on the captured image.

The present disclosure provides a method and apparatus for recognizing a text, a device and a storage medium, and relates to the field of deep learning technology. A specific implementation comprises: receiving a target image; performing a text detection on the target image using a pre-trained lightweight text detection network, to obtain a text detection box; and recognizing a text in the text detection box using a pre-trained lightweight text recognition network, to obtain a text recognition result.

The disclosure herein describes providing signature data of an input document. Text data of the input document is obtained (e.g., OCR data generated from image data) and a first set of signature fields are identified using signature key-value pairs of the text data. A first subset of signed signature fields and a first subset of unsigned signature fields are determined based on mapping to a set of predicted values. A second set of signature fields are determined using a region prediction model applied to image data of the input document. Region images associated with the first subset of unsigned signature fields and with second set of signature fields are obtained and a second set of signed signature fields and a second set of unsigned signature fields are determined using a signature recognition model. Signature output data is provided including signed signature fields and/or unsigned signature fields.

Provided is an information processing apparatus that applies correction using a character recognition error pattern to a character recognition result of a document image, wherein the character recognition error pattern includes error pattern information on a character recognition result of a part where an error occurs in character recognition, correct pattern information applicable to the part where the error occurs, information on a frequency that the error occurs, and information on a state where the error occurs, and wherein the character recognition error pattern to be used in the correction is narrowed down based on the information on the frequency that the error occurs and the information on the state where the error occurs.

A character restoration method and apparatus, a storage medium, and an electronic device are provided. The character restoration method includes: a character identifier of a character in a text region is determined, where the character identifier is used for uniquely identifying the character; and encoding is performed at least according to the character identifier, and encoded data is sent to a receiving end, where the encoded data is used for the receiving end to decode the encoded data and restore the character according to the character identifier obtained after decoding, that is, encoding is performed merely according to a small amount of information, and then the information is obtained by decoding, so as to restore the character.

The accuracy of existing machine learning models, software technologies, and computers are improved by using one or more machine learning models to map data inside structural elements, such as rows or columns, as found within a document to data objects of other documents, where the data objects are at least partially indicative of candidate categories that the data can belong to.