An image processing apparatus that enables easy setting of metadata of image data. The image processing apparatus obtains image data associated with a selected work. A key candidate is identified from t image data based on one or more key types defined according to the selected work. A value candidate corresponding to the identified key candidate is identified based on a value type rule and a value search area rule which are defined for each of the one or more key types, and the identified value candidate is set as the metadata of the image data.

An image processing apparatus that enables easy setting of metadata of image data. The image processing apparatus obtains image data associated with a selected work. A key candidate is identified from t image data based on one or more key types defined according to the selected work. A value candidate corresponding to the identified key candidate is identified based on a value type rule and a value search area rule which are defined for each of the one or more key types, and the identified value candidate is set as the metadata of the image data.

Systems and methods for determining whether an electronic document constitutes vouching evidence is provided. The system may receive ERP item data and generate hypothesis data based thereon, and may receive electronic document data and extract ERP information therefrom. The system may then apply one or more models to compare the hypothesis data to the extracted ERP information to determine whether the electronic document constitutes vouching evidence for the ERP item. Systems and methods for verifying an assertion against a source document are provided. The system may receive first data indicating an unverified assertion and second data comprising a plurality of source documents. The system may apply one or more extraction models to extract a set of key data from the plurality of source documents and may apply one or more matching models to compare the first data to the set of key data to determine whether vouching criteria are met.

Systems and methods for determining whether an electronic document constitutes vouching evidence is provided. The system may receive ERP item data and generate hypothesis data based thereon, and may receive electronic document data and extract ERP information therefrom. The system may then apply one or more models to compare the hypothesis data to the extracted ERP information to determine whether the electronic document constitutes vouching evidence for the ERP item. Systems and methods for verifying an assertion against a source document are provided. The system may receive first data indicating an unverified assertion and second data comprising a plurality of source documents. The system may apply one or more extraction models to extract a set of key data from the plurality of source documents and may apply one or more matching models to compare the first data to the set of key data to determine whether vouching criteria are met.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

An on-image navigation guide can be generated utilizing coordinates of table data of a table in a document image. The on-image navigation guide enables a user to populate a data entry form with the table data by interacting directly with the document image. The data entry form is configured with the same number of columns as the table and the document image and the data entry form share the same data structure. The on-image navigation guide is presented on top of the document image. As a user navigates the document image, a focus point of the on-image navigation guide moves from table cell to table cell, providing an immediate visual feedback on what is captured in a corresponding data entry field. The on-image navigation guide includes an on-image context menu and a pin through which the user can make adjustments and/or corrections without leaving the document image.

An on-image navigation guide can be generated utilizing coordinates of table data of a table in a document image. The on-image navigation guide enables a user to populate a data entry form with the table data by interacting directly with the document image. The data entry form is configured with the same number of columns as the table and the document image and the data entry form share the same data structure. The on-image navigation guide is presented on top of the document image. As a user navigates the document image, a focus point of the on-image navigation guide moves from table cell to table cell, providing an immediate visual feedback on what is captured in a corresponding data entry field. The on-image navigation guide includes an on-image context menu and a pin through which the user can make adjustments and/or corrections without leaving the document image.

The application belongs to the field of big data, and particularly relates to an official document processing method, device, computer equipment and storage medium. The method includes the following steps of: performing format analysis on the to-be-reviewed official document, then acquiring the to-be-reviewed official document of standard file type, and identifying all file components and contents in the to-be-reviewed official document of standard file type; performing text format detection, text content detection and frame layout detection synchronously by a preset text processing model, obtaining a format detection result, a content detection result and a layout detection result; generating a detected error content according to the format detection result, content detection result and layout detection result, calling out a standard writing rule corresponding to the detected error content, marking the detected error content and the standard writing rule in the to-be-reviewed official document.

The application belongs to the field of big data, and particularly relates to an official document processing method, device, computer equipment and storage medium. The method includes the following steps of: performing format analysis on the to-be-reviewed official document, then acquiring the to-be-reviewed official document of standard file type, and identifying all file components and contents in the to-be-reviewed official document of standard file type; performing text format detection, text content detection and frame layout detection synchronously by a preset text processing model, obtaining a format detection result, a content detection result and a layout detection result; generating a detected error content according to the format detection result, content detection result and layout detection result, calling out a standard writing rule corresponding to the detected error content, marking the detected error content and the standard writing rule in the to-be-reviewed official document.