Abstract: Disclosed are systems, computer-readable mediums, and methods for creating a flexible structure description. To create the flexible structure description an image of a document of a particular document type that contains a table is received. An entry describing an item in the table is received. Title elements within the document are searched for based upon the entry. Data fields and anchor elements are detected for the entry. A flexible structure description for the particular document type is generated that includes a set of search elements for each data field in the image of the document and the title elements. The flexible structure description is matched against the image. Data from the image is extracted based upon the matching of the flexible structure description against the image.

Abstract: Automatic classification of different types of documents is disclosed. An image of a form or document is captured. The document is assigned to one or more type definitions by identifying one or more objects within the image of the document. A matching model is selected via identification of the document image. In the case of multiple identifications, a profound analysis of the document type is performed—either automatically or manually. An automatic classifier may be trained with document samples of each of a plurality of document classes or document types where the types are known in advance or a system of classes may be formed automatically without a priori information about types of samples. An automatic classifier determines possible features and calculates a range of feature values and possible other feature parameters for each type or class of document. A decision tree, based on rules specified by a user, may be used for classifying documents.

Abstract: A method for processing a batch of scanned images is provided. The method comprises processing the scanned images into documents. For documents of multiple pages, the method comprises maintaining a page-based coordinate system to specify a location of structures within a page and joining the pages to form a multi-page sheet having a sheet-based coordinate system to specify a location of structures within the multi-page sheet. The method comprises performing a data extraction operation to extract data from each document, said data extraction operation including a page mode wherein structures are detected on individual pages using the page-based coordinate system and a document mode wherein structures are detected within the entire document using the sheet-based coordinate system.

Abstract: Disclosed are systems, computer-readable mediums, and methods for creating a flexible structure description. To create the flexible structure description an image of a document of a particular document type that contains a table is received. An entry describing an item in the table is received. Title elements within the document are searched for based upon the entry. Data fields and anchor elements are detected for the entry. A flexible structure description for the particular document type is generated that includes a set of search elements for each data field in the image of the document and the title elements. The flexible structure description is matched against the image. Data from the image is extracted based upon the matching of the flexible structure description against the image.

Abstract: In one embodiment, the invention provides a method, comprising detecting data fields on a scanned document image; generating a flexible document description based on the detected data fields, including creating a set of search elements for each data field, each search element having associated search criteria; and training or modifying the flexible document description using, for example, a search algorithm to detect the data fields on additional training images based on the set of search elements.

Abstract: Automatic classification of different types of documents is disclosed. An image of a form or document is captured. The document is assigned to one or more type definitions by identifying one or more objects within the image of the document. A matching model is selected via identification of the document image. In the case of multiple identifications, a profound analysis of the document type is performed—either automatically or manually. An automatic classifier may be trained with document samples of each of a plurality of document classes or document types where the types are known in advance or a system of classes may be formed automatically without a priori information about types of samples. An automatic classifier determines possible features and calculates a range of feature values and possible other feature parameters for each type or class of document. A decision tree, based on rules specified by a user, may be used for classifying documents.

Abstract: In one embodiment, the invention provides a method for a machine to perform machine-readable form pre-recognition analysis. The method comprises preliminarily assigning at least one graphic image in a form for identification of form type, preliminarily creating at least one model of the said graphic image for identification of the form type, parsing a form image into regions, determining an image form type for the form image, comprising: (a) detecting on the form image at least one of said graphic images for identification of the form type, (b) performing a primary identification of the form image type based on a comparison of the detected graphic image with the said model, and(c) performing a profound analysis using a supplementary data said-primary identification results in multiple possibilities for the form image type.

Abstract: A method for processing a batch of scanned images is provided. The method comprises processing the scanned images into documents; for documents comprising multiple pages maintaining a page-based coordinate system to specify a location of structures within a page and joining the pages to form a multi-page sheet having a sheet-based coordinate system to specify a location of structures within the multi-page sheet; performing a data extraction operation to extract data from each document, said data extraction operation comprising a page mode wherein structures are detected on individual pages using the page-based coordinate system and a document mode wherein structures are detected within the entire document using the sheet-based coordinate system.

Abstract: A method for processing a batch of scanned images is disclosed. The method includes processing the scanned images into documents. For documents of multiple pages, the method maintains a page-based coordinate system to specify a location of structures within a page and joins the pages to form a multi-page sheet associated with a sheet-based coordinate system to specify a location of structures within the multi-page sheet. Data may be extracted from each document through a page mode wherein structures are detected on individual pages using the page-based coordinate system and a document mode wherein structures are detected within the entire document using the sheet-based coordinate system.

Abstract: In one embodiment, the invention provides a method, comprising detecting data fields on a scanned document image; generating a flexible document description based on the detected data fields, including creating a set of search elements for each data field, each search element having associated search criteria; and training or modifying the flexible document description using, for example, a search algorithm to detect the data fields on additional training images based on the set of search elements.

Abstract: A method and system for creating a form template for a form are disclosed. The method comprises analyzing an image of a form to detect object demarcations in the form. The method also comprises classifying the object demarcations into one of a plurality of predefined object categories and processing each object demarcation based on the object category into which it has been classified, thereby to create the form template automatically.

Abstract: In one embodiment, there is disclosed a method capturing data from a document image. The method 300 comprises processing the document image to identify at least one repetitive structure and performing a capturing operation including creating a plurality of instances of the repetitive structure based on once-described structure properties of the repetitive structure in a document template, and populating each instance with corresponding data from the document image. The method may also include creating a document template for capturing data from a document image.

Abstract: A method for processing a batch of scanned images is provided. The method comprises processing the scanned images into documents. For documents of multiple pages, the method comprises maintaining a page-based coordinate system to specify a location of structures within a page and joining the pages to form a multi-page sheet having a sheet-based coordinate system to specify a location of structures within the multi-page sheet. The method comprises performing a data extraction operation to extract data from each document, said data extraction operation including a page mode wherein structures are detected on individual pages using the page-based coordinate system and a document mode wherein structures are detected within the entire document using the sheet-based coordinate system.

Abstract: A method related to data capture from forms involving optical character recognition comprises detecting data fields on a scanned image; generating a flexible document description based on the detected data fields, including creating a set of search elements for each data field, each search element having associated search criteria; and training the flexible document description using a search algorithm to detect the data fields on additional training images based on the set of search elements.

Abstract: A method for processing a batch of scanned images is provided. The method comprises processing the scanned images into documents. For documents comprising multiple pages, the method maintains a page-based coordinate system to specify a location of structures within a page and joins the pages to form a multi-page sheet having a sheet-based coordinate system to specify a location of structures within the multi-page sheet. Data may be extracted from each document, such operation comprising a page mode wherein structures are detected on individual pages using the page-based coordinate system and a document mode wherein structures are detected within the entire document using the sheet-based coordinate system.

Abstract: Automatic classification of different types of documents is disclosed. An image of a form or document is captured. The document is assigned to one or more type definitions by identifying one or more objects within the image of the document. A matching model is selected via identification of the document image. In the case of multiple identifications, a profound analysis of the document type is performed—either automatically or manually. An automatic classifier may be trained with document samples of each of a plurality of document classes or document types where the types are known in advance or a system of classes may be formed automatically without a priori information about types of samples. An automatic classifier determines possible features and calculates a range of feature values and possible other feature parameters for each type or class of document. A decision tree, based on rules specified by a user, may be used for classifying documents.

Abstract: In one embodiment, the invention provides a method for a machine to perform machine-readable form pre-recognition analysis. The method comprises preliminarily assigning at least one graphic image in a form for identification of form type, preliminarily creating at least one model of the said graphic image for identification of the form type, parsing a form image into regions, determining an image form type for the form image, comprising: (a) detecting on the form image at least one of said graphic images for identification of the form type, (b) performing a primary identification of the form image type based on a comparison of the detected graphic image with the said model, and(c) performing a profound analysis using a supplementary data said-primary identification results in multiple possibilities for the form image type.

Abstract: The present invention relates generally to an optical character recognition of machine-readable forms, and in particular to a verification of a direction of spatial orientation and a definition of a form type of the document electronic image. The goals of the invention are achieved by preliminarily assigning one or more form objects as elements composing a graphic image unambiguously defining its direction of spatial orientation. Similarly, one or more form objects are preliminarily assigned as elements composing a graphic image unambiguously defining its type. The direction of spatial orientation and the type of the form are verified via identification of said images. The models of graphic images either for verification the direction of spatial orientation or for defining the form type are stored in a special data storage means, one of the embodiment of which is form model description.

Abstract: A method for processing a batch of scanned images is provided. The method comprises processing the scanned images into documents; for documents comprising multiple pages maintaining a page-based coordinate system to specify a location of structures within a page and joining the pages to form a multi-page sheet having a sheet-based coordinate system to specify a location of structures within the multi-page sheet; performing a data extraction operation to extract data from each document, said data extraction operation comprising a page mode wherein structures are detected on individual pages using the page-based coordinate system and a document mode wherein structures are detected within the entire document using the sheet-based coordinate system.

Abstract: In one embodiment, the invention provides a method, comprising detecting data fields on a scanned image; generating a flexible document description based on the detected data fields, including creating a set of search elements for each data field, each search element having associated search criteria; and training the flexible document description using a search algorithm to detect the data fields on additional training images based on the set of search elements.