11 results about "Page footer" patented technology

The invention provides a structural decomposition and information identification method of multi-modal data, a medium and equipment, and the method comprises the steps: obtaining to-be-processed multi-modal literature data, the multi-modal literature data being documents or pictures, the types of the documents including word documents and PDF (Portable Document Format) documents; the method comprises the following steps: converting to-be-processed multi-modal literature data into to-be-processed literature data in an image form, preprocessing the to-be-processed literature data to obtain input image data, inputting the input image data into a field fine-tuning DETR model, identifying a logic region category of the input image data through the field fine-tuning DETR model, obtaining a region category identification result, and outputting the region category identification result. The logic region category comprises a title region, an author region, an abstract region, a text region, an illustration region, a table region, a formula region, a footer region and a reference region; and carrying out differential information extraction on each region category identification result to obtain information corresponding to each region category identification result so as to realize accurate identification of information in the multi-modal data.

The invention discloses a PDF (Portable Document Format) file layout identification method based on mask processing, and aims to realize accurate identification of various layout elements such as titles, texts, page headers, page footers, tables and pictures in PDF files. According to the method, characters and coordinates in a PDF file are analyzed through MuPDF, different color masks are adopted to replace texts and punctuation marks respectively, original content of a non-text area is reserved, a page picture subjected to mask processing is generated, a training data set is constructed based on the page picture, training is conducted through a target detection model (such as YOLO), and a high-precision layout recognition model is obtained. According to the method, the accuracy and the automation level of PDF layout recognition are effectively improved, and the method has a wide application prospect.

The application relates to a contract document difference detection method and device based on an ICR character matrix. The contract document difference detection method based on the ICR character matrix comprises the following steps: extracting text data of an original contract document and a comparison contract document by using ICR technology; dividing the contract document into four parts of a header, a body, a footer and table text, and respectively splicing into long strings; and using a two-section difference detection algorithm to sequentially query difference points from the body and the table text, generating a text comparison result, and returning position information of the difference point type, related strings and related characters. Compared with existing document comparison tools, the application can perform difference detection on scanned copies or even photo-form contract electronic files; when designing comparison rules, the characteristics of structural texts such as headers, footers and tables of the contract are considered, and differences such as text line breaks and page changes that do not affect semantics are ignored, so that a difference comparison result meeting human expectations can be fed back.

This specification relates to file format-based transparent encryption tailored for big data. In some aspects, a method includes receiving, by one or more computing devices, a write request including a table with one or more columns to be stored in a storage device, wherein each column includes a number of pages; generating a column key for each column and a page key for each page including sensitive information; encrypting (i) each page including sensitive information with a corresponding page key and (ii) each column with a corresponding column key; generating wrapped keys for the column keys and page keys and storing the wrapped keys into a key file; storing the encrypted columns into a data file of the storage device and storing the wrapped keys in a separate key file; and storing a reference to the key file in a file footer of the data file.

The invention relates to the technical field of information processing, and provides a file sensitive information processing method and system, a computer and a storage medium, and the file sensitive information processing method comprises the steps: obtaining a first task data set, and converting a to-be-processed file into a plurality of to-be-processed file pictures; based on the second task data set, judging whether header and footer detection is started or not, and if the header and footer detection is started, detecting and generating a plurality of area detection results; whether seal detection is started or not is judged based on the third task data set, and if seal detection is started, a plurality of seal detection results are generated through detection; judging whether text detection is started or not based on the fourth task data set, and if the text detection is started, detecting and generating a plurality of sensitive text detection results; and judging whether fuzzy processing is started or not based on the fifth task data set, and if the fuzzy processing is started, generating a fuzzy file. By adopting the method, the problems of low blind state processing efficiency, inaccurate blind state and artificial leakage risk can be avoided.

The invention relates to the technical field of document merging, in particular to a document merging system and method, equipment and a medium, the system comprises an interaction and configuration module, a document analysis and routing module, a document merging module and a verification and repair module, and the verification and repair module is integrated in the system to be in communication connection with the document merging module. And the verification and repair module is used for verifying and repairing the page header and the page footer of the output document, so that the segments, the page header and the page footer of all the documents in the output document are kept in the original format before merging. By means of the mode, the multi-format documents can be intelligently, automatically and losslessly combined in batches, and it is ensured that the format and header and footer completeness of each document are reserved.

This specification relates to file format-based transparent encryption tailored for big data. In some aspects, a method includes receiving, by one or more computing devices, a write request including a table with one or more columns to be stored in a storage device, wherein each column includes a number of pages; generating a column key for each column and a page key for each page including sensitive information; encrypting (i) each page including sensitive information with a corresponding page key and (ii) each column with a corresponding column key; generating wrapped keys for the column keys and page keys and storing the wrapped keys into a key file; storing the encrypted columns into a data file of the storage device and storing the wrapped keys in a separate key file; and storing a reference to the key file in a file footer of the data file.

The invention relates to the technical field of document processing, and discloses a layout and reading sequence identification method, system and device and a storage medium, and the method comprises the steps: generating a training data set, training a column document layout identification model, and preprocessing an input document image; the output document image comprises columns, image blocks, table blocks, page annotations, label frames of all the universal layout elements, and the positions and confidence degrees of the corresponding label frames, wherein the file image comprises the columns, the image blocks, the table blocks, the page annotations and the universal layout elements; performing post-processing optimization on the identified tab boxes, grouping non-column tab boxes in the page based on the positions of the column tab boxes to form a plurality of grouping blocks, performing local sorting on internal elements of the grouping blocks, and performing global sorting on all the grouping blocks and non-grouped independent tab boxes to generate a global sorting result; and replacing the grouping blocks in the global sorting result with a local sorting result, and endowing all elements with continuous sequence identifiers so as to output a document reading sequence. According to the invention, identification efficiency and accuracy can be improved.

The invention discloses a table picture OCR (Optical Character Recognition) method and tool using an Excel template, and the method comprises the following steps: S1, obtaining a target Excel template file, and analyzing printing information in the target Excel template file, including page headers, page footers, page numbers and edge distances; s2, performing format comparison on a printing image exported from the Excel file and an image to be identified, and determining the position of printing information in the image; s3, preprocessing the to-be-identified image, deleting a printing information area, and reserving a table main body area; and S4, performing OCR identification on the preprocessed image, and extracting a table structure and text content. According to the method, the printing information (such as page header, page footer, page number and the like) in the Excel template is analyzed in advance, the image is preprocessed before OCR recognition, the printing information area is removed, and therefore the accuracy and efficiency of OCR recognition are improved.

The invention discloses a dynamic editable header and footer generation method and system based on chapter granularity, and relates to the dynamic editable header and footer generation method based on the chapter granularity, which comprises the following steps: S1, receiving a target document, decompressing the target document, and creating a basic header and footer template; s2, extracting chapter information and segment character positions of the document; s3, copying and renaming the basic header and footer template to obtain an updated header and footer file; and S4, repackaging all the files containing the updated header and footer into a document in a docx format.

The application discloses a cross-page table intelligent processing and retrieval enhancement system and method, relates to the technical field of document information processing, and comprises the following steps: performing character recognition and table area detection on input documents page by page, identifying candidate table block areas, removing header and footer texts, and generating a purified table block record set; extracting column position structures and table header token sets based on the purified table block record set, constructing cross-page continuous operators, generating cross-page determination thresholds, forming a cross-page connection relationship set, merging cross-page tables through the cross-page connection relationship set, restoring row and column structures, generating logical table records, constructing retrieval enhancement index records, and completing retrieval enhancement storage; and matching natural language queries by using the retrieval enhancement index records, performing hit verification, and outputting logical table structured representation texts and cross-page connection group page number ranges. The application realizes cross-page table structure recognition and natural language retrieval enhancement.